From 2d004f4247e6249cd84ce1c33b7378de5cb84310 Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Sat, 2 Nov 2024 04:56:48 +0000 Subject: [PATCH] Updated datasets 2024-11-02 UTC --- gee_catalog.json | 202 ++++----- gee_catalog.tsv | 202 ++++----- nasa_cmr_catalog.json | 973 +++++++++++++++++++++++------------------- nasa_cmr_catalog.tsv | 103 +++-- 4 files changed, 803 insertions(+), 677 deletions(-) diff --git a/gee_catalog.json b/gee_catalog.json index ab01c3c..6051ff2 100644 --- a/gee_catalog.json +++ b/gee_catalog.json @@ -114,7 +114,7 @@ "snippet": "ee.ImageCollection('ASTER/AST_L1T_003')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-03-04", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aster, eos, imagery, nasa, nir, radiance, swir, terra, thermal, tir, toa, usgs, vnir", @@ -726,7 +726,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S1_GRD')", "provider": "European Union/ESA/Copernicus", "state_date": "2014-10-03", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel", @@ -744,7 +744,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2')", "provider": "European Union/ESA/Copernicus", "state_date": "2015-06-27", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -56, 180, 83", "deprecated": true, "keywords": "copernicus, esa, eu, msi, radiance, sentinel", @@ -762,7 +762,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY')", "provider": "European Union/ESA/Copernicus/SentinelHub", "state_date": "2015-06-27", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub", @@ -780,7 +780,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_HARMONIZED')", "provider": "European Union/ESA/Copernicus", "state_date": "2015-06-27", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "copernicus, esa, eu, msi, radiance, sentinel", @@ -798,7 +798,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_SR')", "provider": "European Union/ESA/Copernicus", "state_date": "2017-03-28", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -56, 180, 83", "deprecated": true, "keywords": "copernicus, esa, eu, msi, reflectance, sentinel, sr", @@ -816,7 +816,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')", "provider": "European Union/ESA/Copernicus", "state_date": "2017-03-28", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "copernicus, esa, eu, msi, reflectance, sentinel, sr", @@ -834,7 +834,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S3/OLCI')", "provider": "European Union/ESA/Copernicus", "state_date": "2016-10-18", - "end_date": "2024-10-30", + "end_date": "2024-10-31", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "copernicus, esa, eu, olci, radiance, sentinel, toa", @@ -852,7 +852,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -870,7 +870,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -888,7 +888,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-05", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi", @@ -906,7 +906,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-11-22", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi", @@ -924,7 +924,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-10-02", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi", @@ -942,7 +942,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi", @@ -960,7 +960,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi", @@ -978,7 +978,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi", @@ -996,7 +996,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_AI')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-04", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -1014,7 +1014,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_LH')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-04", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -1032,7 +1032,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CH4')", "provider": "European Union/ESA/Copernicus", "state_date": "2019-02-08", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, copernicus, esa, eu, knmi, methane, s5p, sentinel, sron, tropomi", @@ -1050,7 +1050,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CLOUD')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-04", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi", @@ -1068,7 +1068,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-06-28", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi", @@ -1086,7 +1086,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-12-05", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi", @@ -1104,7 +1104,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-06-28", - "end_date": "2024-10-22", + "end_date": "2024-10-23", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi", @@ -1122,7 +1122,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-09-08", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi", @@ -1158,7 +1158,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-12-05", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi", @@ -1572,7 +1572,7 @@ "snippet": "ee.ImageCollection('ECMWF/CAMS/NRT')", "provider": "European Centre for Medium-Range Weather Forecasts (ECMWF)", "state_date": "2016-06-22", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter", @@ -1626,7 +1626,7 @@ "snippet": "ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR')", "provider": "Daily Aggregates: Google and Copernicus Climate Data Store", "state_date": "1950-01-02", - "end_date": "2024-10-24", + "end_date": "2024-10-25", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind", @@ -1644,7 +1644,7 @@ "snippet": "ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY')", "provider": "Copernicus Climate Data Store", "state_date": "1950-01-01", - "end_date": "2024-10-25", + "end_date": "2024-10-26", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind", @@ -2688,7 +2688,7 @@ "snippet": "ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED')", "provider": "Google Earth Engine", "state_date": "2015-06-27", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "google, cloud, sentinel2_derived", @@ -2706,7 +2706,7 @@ "snippet": "ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1')", "provider": "World Resources Institute", "state_date": "2015-06-27", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "global, google, landcover, landuse, nrt, sentinel2_derived", @@ -2994,7 +2994,7 @@ "snippet": "ee.ImageCollection('IDAHO_EPSCOR/GRIDMET')", "provider": "University of California Merced", "state_date": "1979-01-01", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-124.9, 24.9, -66.8, 49.6", "deprecated": false, "keywords": "climate, fireburning, gridmet, humidity, merced, metdata, nfdrs, precipitation, radiation, temperature, wind", @@ -3624,7 +3624,7 @@ "snippet": "ee.ImageCollection('JAXA/ALOS/PALSAR-2/Level2_2/ScanSAR')", "provider": "JAXA EORC", "state_date": "2014-08-04", - "end_date": "2024-08-31", + "end_date": "2024-09-05", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "alos2, eroc, jaxa, palsar2, radar, sar", @@ -3750,7 +3750,7 @@ "snippet": "ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V3')", "provider": "Global Change Observation Mission (GCOM)", "state_date": "2021-11-29", - "end_date": "2024-10-29", + "end_date": "2024-10-31", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index", @@ -3804,7 +3804,7 @@ "snippet": "ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V3')", "provider": "Global Change Observation Mission (GCOM)", "state_date": "2021-11-29", - "end_date": "2024-10-29", + "end_date": "2024-10-31", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst", @@ -3858,7 +3858,7 @@ "snippet": "ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V3')", "provider": "Global Change Observation Mission (GCOM)", "state_date": "2021-11-29", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color", @@ -3912,7 +3912,7 @@ "snippet": "ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V3')", "provider": "Global Change Observation Mission (GCOM)", "state_date": "2021-11-29", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst", @@ -3930,7 +3930,7 @@ "snippet": "ee.ImageCollection('JAXA/GPM_L3/GSMaP/v6/operational')", "provider": "JAXA Earth Observation Research Center", "state_date": "2014-03-01", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -60, 180, 60", "deprecated": false, "keywords": "climate, geophysical, gpm, hourly, jaxa, precipitation, weather", @@ -3966,7 +3966,7 @@ "snippet": "ee.ImageCollection('JAXA/GPM_L3/GSMaP/v7/operational')", "provider": "JAXA Earth Observation Research Center", "state_date": "2014-03-01", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -60, 180, 60", "deprecated": false, "keywords": "climate, geophysical, gpm, hourly, jaxa, precipitation, weather", @@ -3984,7 +3984,7 @@ "snippet": "ee.ImageCollection('JAXA/GPM_L3/GSMaP/v8/operational')", "provider": "JAXA Earth Observation Research Center", "state_date": "1998-01-01", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -60, 180, 60", "deprecated": false, "keywords": "climate, geophysical, gpm, hourly, jaxa, precipitation, weather", @@ -5496,7 +5496,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC08/C02/T1_RT')", "provider": "USGS", "state_date": "2013-03-18", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l8, landsat, lc8, nrt, oli_tirs, radiance, rt, t1, tier1, usgs", @@ -5514,7 +5514,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC08/C02/T1_RT_TOA')", "provider": "USGS/Google", "state_date": "2013-03-18", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l8, landsat, lc8, toa, usgs", @@ -5604,7 +5604,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T1')", "provider": "USGS", "state_date": "2021-10-31", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs", @@ -5622,7 +5622,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T1_L2')", "provider": "USGS", "state_date": "2021-10-31", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs", @@ -5640,7 +5640,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA')", "provider": "USGS/Google", "state_date": "2021-10-31", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, landsat, toa, usgs", @@ -7656,7 +7656,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MCD19A1_GRANULES')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-12-21", - "end_date": "2024-10-27", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, aod, aqua, daily, global, maiac, modis, nasa, terra, usgs", @@ -7674,7 +7674,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MCD19A2_GRANULES')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-27", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, aod, aqua, daily, global, maiac, mcd19a2, modis, nasa, terra, usgs", @@ -7692,7 +7692,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MCD43A1')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-21", + "end_date": "2024-10-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "albedo, brdf, daily, global, mcd43a1, modis, nasa, reflectance, usgs", @@ -7710,7 +7710,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MCD43A2')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-21", + "end_date": "2024-10-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "albedo, brdf, daily, global, modis, nasa, quality, reflectance, usgs", @@ -7728,7 +7728,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MCD43A3')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-21", + "end_date": "2024-10-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "albedo, black_sky, daily, global, modis, nasa, usgs, white_sky", @@ -7746,7 +7746,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MCD43A4')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-21", + "end_date": "2024-10-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "albedo, brdf, daily, global, modis, nasa, reflectance, usgs", @@ -7764,7 +7764,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MCD43C3')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-20", + "end_date": "2024-10-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "albedo, black_sky, brdf, daily, global, modis, nasa, usgs, white_sky", @@ -7854,7 +7854,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MOD09GA')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, global, mod09ga, modis, nasa, sr, surface_reflectance, terra, usgs", @@ -7872,7 +7872,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MOD09GQ')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, global, mod09gq, modis, nasa, sr, surface_reflectance, terra, usgs", @@ -7926,7 +7926,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MOD11A1')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, emissivity, global, lst, mod11a1, modis, nasa, surface_temperature, terra, usgs", @@ -8106,7 +8106,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MOD16A2')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2001-01-01", - "end_date": "2024-10-07", + "end_date": "2024-10-15", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "8_day, evapotranspiration, global, mod16a2, modis, nasa", @@ -8196,7 +8196,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MOD21A1D')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, emissivity, global, lst, nasa, surface_temperature, terra, usgs", @@ -8214,7 +8214,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MOD21A1N')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, emissivity, global, lst, nasa, surface_temperature, terra, usgs", @@ -8340,7 +8340,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MYD09GA')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2002-07-04", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aqua, daily, global, modis, myd09ga, nasa, sr, surface_reflectance, usgs", @@ -8358,7 +8358,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MYD09GQ')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2002-07-04", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aqua, daily, global, modis, myd09gq, nasa, sr, surface_reflectance, usgs", @@ -8412,7 +8412,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MYD11A1')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2002-07-04", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aqua, daily, emissivity, global, lst, modis, myd11a1, nasa, surface_temperature, usgs", @@ -8628,7 +8628,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MYD21A1D')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aqua, daily, emissivity, global, lst, nasa, surface_temperature, usgs", @@ -8646,7 +8646,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MYD21A1N')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-02-24", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aqua, daily, emissivity, global, lst, nasa, surface_temperature, usgs", @@ -9690,7 +9690,7 @@ "snippet": "ee.ImageCollection('NASA/EMIT/L1B/RAD')", "provider": "NASA Jet Propulsion Laboratory", "state_date": "2022-08-09", - "end_date": "2024-10-28", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, emit, nasa, radiance", @@ -9708,7 +9708,7 @@ "snippet": "ee.ImageCollection('NASA/EMIT/L2A/RFL')", "provider": "NASA Jet Propulsion Laboratory", "state_date": "2022-08-09", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, emit, nasa, reflectance", @@ -9798,7 +9798,7 @@ "snippet": "ee.ImageCollection('NASA/GEOS-CF/v1/fcst/htf')", "provider": "NASA / GMAO", "state_date": "2022-10-01", - "end_date": "2024-10-30", + "end_date": "2024-10-31", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "composition, forecast, geos, gmao, nasa", @@ -9816,7 +9816,7 @@ "snippet": "ee.ImageCollection('NASA/GEOS-CF/v1/fcst/tavg1hr')", "provider": "NASA / GMAO", "state_date": "2022-10-01", - "end_date": "2024-10-29", + "end_date": "2024-10-31", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "composition, forecast, geos, gmao, nasa", @@ -9834,7 +9834,7 @@ "snippet": "ee.ImageCollection('NASA/GEOS-CF/v1/rpl/htf')", "provider": "NASA / GMAO", "state_date": "2018-01-01", - "end_date": "2024-10-30", + "end_date": "2024-10-31", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "composition, forecast, geos, gmao, nasa", @@ -9852,7 +9852,7 @@ "snippet": "ee.ImageCollection('NASA/GEOS-CF/v1/rpl/tavg1hr')", "provider": "NASA / GMAO", "state_date": "2018-01-01", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "composition, forecast, geos, gmao, nasa", @@ -10284,7 +10284,7 @@ "snippet": "ee.ImageCollection('NASA/HLS/HLSL30/v002')", "provider": "NASA LP DAAC", "state_date": "2013-04-11", - "end_date": "2024-10-28", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "landsat, nasa, sentinel, usgs", @@ -10320,7 +10320,7 @@ "snippet": "ee.ImageCollection('NASA/LANCE/NOAA20_VIIRS/C2')", "provider": "NASA / LANCE / NOAA20_VIIRS", "state_date": "2023-10-08", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs", @@ -10338,7 +10338,7 @@ "snippet": "ee.ImageCollection('NASA/LANCE/SNPP_VIIRS/C2')", "provider": "NASA / LANCE / SNPP_VIIRS", "state_date": "2023-09-03", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs", @@ -10446,7 +10446,7 @@ "snippet": "ee.ImageCollection('NASA/NLDAS/FORA0125_H002')", "provider": "NASA GES DISC at NASA Goddard Space Flight Center", "state_date": "1979-01-01", - "end_date": "2024-10-26", + "end_date": "2024-10-29", "bbox": "-125.15, 24.85, -66.85, 53.28", "deprecated": false, "keywords": "climate, evaporation, forcing, geophysical, hourly, humidity, ldas, nasa, nldas, precipitation, pressure, radiation, temperature, wind", @@ -10626,7 +10626,7 @@ "snippet": "ee.ImageCollection('NASA/SMAP/SPL4SMGP/007')", "provider": "Google and NSIDC", "state_date": "2015-03-31", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -84, 180, 84", "deprecated": false, "keywords": "drought, nasa, smap, soil_moisture, surface, weather", @@ -10644,7 +10644,7 @@ "snippet": "ee.ImageCollection('NASA/VIIRS/002/VNP09GA')", "provider": "NASA Land SIPS", "state_date": "2012-01-19", - "end_date": "2024-10-20", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, nasa, noaa, npp, reflectance, sr, viirs, vnp09ga", @@ -10662,7 +10662,7 @@ "snippet": "ee.ImageCollection('NASA/VIIRS/002/VNP09H1')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2012-01-19", - "end_date": "2024-10-07", + "end_date": "2024-10-23", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, nasa, noaa, npp, reflectance, sr, viirs", @@ -10680,7 +10680,7 @@ "snippet": "ee.ImageCollection('NASA/VIIRS/002/VNP13A1')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2012-01-17", - "end_date": "2024-09-29", + "end_date": "2024-10-15", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "16_day, evi, nasa, ndvi, noaa, npp, vegetation, viirs, vnp13a1", @@ -10698,7 +10698,7 @@ "snippet": "ee.ImageCollection('NASA/VIIRS/002/VNP14A1')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2012-01-19", - "end_date": "2024-10-20", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "fire, land, nasa, noaa, surface, viirs", @@ -10716,7 +10716,7 @@ "snippet": "ee.ImageCollection('NASA/VIIRS/002/VNP15A2H')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2012-01-17", - "end_date": "2024-10-07", + "end_date": "2024-10-23", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "land, nasa, noaa, surface, viirs", @@ -10734,7 +10734,7 @@ "snippet": "ee.ImageCollection('NASA/VIIRS/002/VNP21A1D')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2012-01-19", - "end_date": "2024-10-20", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, day, land, nasa, noaa, surface, temperature, viirs", @@ -10752,7 +10752,7 @@ "snippet": "ee.ImageCollection('NASA/VIIRS/002/VNP21A1N')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2012-01-19", - "end_date": "2024-10-22", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, land, nasa, night, noaa, surface, temperature, viirs", @@ -10842,7 +10842,7 @@ "snippet": "ee.ImageCollection('NCEP_RE/surface_temp')", "provider": "NCEP", "state_date": "1948-01-01", - "end_date": "2024-10-27", + "end_date": "2024-10-28", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "atmosphere, climate, geophysical, ncep, noaa, reanalysis, temperature", @@ -11094,7 +11094,7 @@ "snippet": "ee.ImageCollection('NOAA/CDR/OISST/V2_1')", "provider": "NOAA", "state_date": "1981-09-01", - "end_date": "2024-10-28", + "end_date": "2024-10-29", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "avhrr, cdr, daily, ice, noaa, ocean, oisst, real_time, sst, temperature", @@ -11166,7 +11166,7 @@ "snippet": "ee.ImageCollection('NOAA/CFSR')", "provider": "NOAA NWS National Centers for Environmental Prediction (NCEP)", "state_date": "2018-12-13", - "end_date": "2024-10-30", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather", @@ -11184,7 +11184,7 @@ "snippet": "ee.ImageCollection('NOAA/CFSV2/FOR6H')", "provider": "NOAA NWS National Centers for Environmental Prediction (NCEP)", "state_date": "1979-01-01", - "end_date": "2024-10-30", + "end_date": "2024-10-31", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather", @@ -11238,7 +11238,7 @@ "snippet": "ee.ImageCollection('NOAA/GFS0P25')", "provider": "NOAA/NCEP/EMC", "state_date": "2015-07-01", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind", @@ -11256,7 +11256,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/FDCC')", "provider": "NOAA", "state_date": "2017-05-24", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-152.11, 14, -49.18, 56.77", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire", @@ -11274,7 +11274,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/FDCF')", "provider": "NOAA", "state_date": "2017-05-24", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire", @@ -11292,7 +11292,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPC')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-152.11, 14, -49.18, 56.77", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -11310,7 +11310,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPF')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -11328,7 +11328,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPM')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -11436,7 +11436,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/FDCC')", "provider": "NOAA", "state_date": "2022-10-13", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, 14.57, 180, 53.51", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire", @@ -11454,7 +11454,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/FDCF')", "provider": "NOAA", "state_date": "2022-10-13", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire", @@ -11472,7 +11472,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPC')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, 14.57, 180, 53.51", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -11490,7 +11490,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPF')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -11508,7 +11508,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPM')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2024-10-31", + "end_date": "2024-11-01", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -11616,7 +11616,7 @@ "snippet": "ee.ImageCollection('NOAA/NWS/RTMA')", "provider": "NOAA/NWS", "state_date": "2011-01-01", - "end_date": "2024-10-30", + "end_date": "2024-11-01", "bbox": "-130.17, 20.15, -60.81, 52.91", "deprecated": false, "keywords": "climate, cloud, geophysical, humidity, noaa, nws, precipitation, pressure, rtma, surface, temperature, visibility, weather, wind", @@ -11832,7 +11832,7 @@ "snippet": "ee.ImageCollection('NOAA/VIIRS/001/VNP46A1')", "provider": "NASA LAADS DAAC", "state_date": "2012-01-19", - "end_date": "2024-10-30", + "end_date": "2024-10-31", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, dnb, nasa, noaa, viirs", @@ -11850,7 +11850,7 @@ "snippet": "ee.ImageCollection('NOAA/VIIRS/001/VNP46A2')", "provider": "NASA LAADS DAAC", "state_date": "2012-01-19", - "end_date": "2024-10-21", + "end_date": "2024-10-24", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "brdf, daily, nasa, noaa, viirs", @@ -11994,7 +11994,7 @@ "snippet": "ee.ImageCollection('OREGONSTATE/PRISM/AN81d')", "provider": "PRISM / OREGONSTATE", "state_date": "1981-01-01", - "end_date": "2024-10-27", + "end_date": "2024-10-29", "bbox": "-125, 24, -66, 50", "deprecated": false, "keywords": "climate, daily, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather", @@ -13128,7 +13128,7 @@ "snippet": "ee.ImageCollection('TOMS/MERGED')", "provider": "NASA / GES DISC", "state_date": "1978-11-01", - "end_date": "2024-10-29", + "end_date": "2024-10-30", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms", @@ -16350,7 +16350,7 @@ "snippet": "ee.ImageCollection('projects/sat-io/open-datasets/us-drought-monitor')", "provider": "National Drought Mitigation Center", "state_date": "2000-01-04", - "end_date": "2024-10-15", + "end_date": "2024-10-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "drought, ndmc, noaa, usda", diff --git a/gee_catalog.tsv b/gee_catalog.tsv index 76b4362..ed2ec94 100644 --- a/gee_catalog.tsv +++ b/gee_catalog.tsv @@ -5,7 +5,7 @@ ACA/reef_habitat/v2_0 Allen Coral Atlas (ACA) - Geomorphic Zonation and Benthic AHN/AHN2_05M_INT AHN Netherlands 0.5m DEM, Interpolated image ee.Image('AHN/AHN2_05M_INT') AHN 2012-01-01 2012-01-01 3.35, 50.74, 7.24, 53.55 False ahn, dem, elevation, geophysical, lidar, netherlands https://storage.googleapis.com/earthengine-stac/catalog/AHN/AHN_AHN2_05M_INT.json https://developers.google.com/earth-engine/datasets/catalog/AHN_AHN2_05M_INT CC0-1.0 AHN/AHN2_05M_NON AHN Netherlands 0.5m DEM, Non-Interpolated image ee.Image('AHN/AHN2_05M_NON') AHN 2012-01-01 2012-01-01 3.35, 50.74, 7.24, 53.55 False ahn, dem, elevation, geophysical, lidar, netherlands https://storage.googleapis.com/earthengine-stac/catalog/AHN/AHN_AHN2_05M_NON.json https://developers.google.com/earth-engine/datasets/catalog/AHN_AHN2_05M_NON CC0-1.0 AHN/AHN2_05M_RUW AHN Netherlands 0.5m DEM, Raw Samples image ee.Image('AHN/AHN2_05M_RUW') AHN 2012-01-01 2012-01-01 3.35, 50.74, 7.24, 53.55 False ahn, dem, elevation, geophysical, lidar, netherlands https://storage.googleapis.com/earthengine-stac/catalog/AHN/AHN_AHN2_05M_RUW.json https://developers.google.com/earth-engine/datasets/catalog/AHN_AHN2_05M_RUW CC0-1.0 -ASTER/AST_L1T_003 ASTER L1T Radiance image_collection ee.ImageCollection('ASTER/AST_L1T_003') NASA LP DAAC at the USGS EROS Center 2000-03-04 2024-10-29 -180, -90, 180, 90 False aster, eos, imagery, nasa, nir, radiance, swir, terra, thermal, tir, toa, usgs, vnir https://storage.googleapis.com/earthengine-stac/catalog/ASTER/ASTER_AST_L1T_003.json https://developers.google.com/earth-engine/datasets/catalog/ASTER_AST_L1T_003 proprietary +ASTER/AST_L1T_003 ASTER L1T Radiance image_collection ee.ImageCollection('ASTER/AST_L1T_003') NASA LP DAAC at the USGS EROS Center 2000-03-04 2024-10-30 -180, -90, 180, 90 False aster, eos, imagery, nasa, nir, radiance, swir, terra, thermal, tir, toa, usgs, vnir https://storage.googleapis.com/earthengine-stac/catalog/ASTER/ASTER_AST_L1T_003.json https://developers.google.com/earth-engine/datasets/catalog/ASTER_AST_L1T_003 proprietary AU/GA/AUSTRALIA_5M_DEM Australian 5M DEM image_collection ee.ImageCollection('AU/GA/AUSTRALIA_5M_DEM') Geoscience Australia 2015-12-01 2015-12-01 114.09, -43.45, 153.64, -9.88 False australia, dem, elevation, ga, geophysical, geoscience_australia, lidar https://storage.googleapis.com/earthengine-stac/catalog/AU/AU_GA_AUSTRALIA_5M_DEM.json https://developers.google.com/earth-engine/datasets/catalog/AU_GA_AUSTRALIA_5M_DEM CC-BY-4.0 AU/GA/DEM_1SEC/v10/DEM-H DEM-H: Australian SRTM Hydrologically Enforced Digital Elevation Model image ee.Image('AU/GA/DEM_1SEC/v10/DEM-H') Geoscience Australia 2010-02-01 2010-02-01 112.99, -44.06, 154, -9.99 False australia, dem, elevation, ga, geophysical, geoscience_australia, smoothed, srtm https://storage.googleapis.com/earthengine-stac/catalog/AU/AU_GA_DEM_1SEC_v10_DEM-H.json https://developers.google.com/earth-engine/datasets/catalog/AU_GA_DEM_1SEC_v10_DEM-H CC-BY-4.0 AU/GA/DEM_1SEC/v10/DEM-S DEM-S: Australian Smoothed Digital Elevation Model image ee.Image('AU/GA/DEM_1SEC/v10/DEM-S') Geoscience Australia 2010-02-01 2010-02-01 112.99, -44.06, 154, -9.99 False australia, dem, elevation, ga, geophysical, geoscience_australia, smoothed, srtm https://storage.googleapis.com/earthengine-stac/catalog/AU/AU_GA_DEM_1SEC_v10_DEM-S.json https://developers.google.com/earth-engine/datasets/catalog/AU_GA_DEM_1SEC_v10_DEM-S CC-BY-4.0 @@ -39,31 +39,31 @@ COPERNICUS/CORINE/V20/100m Copernicus CORINE Land Cover image_collection ee.Imag COPERNICUS/DEM/GLO30 Copernicus DEM GLO-30: Global 30m Digital Elevation Model image_collection ee.ImageCollection('COPERNICUS/DEM/GLO30') Copernicus 2010-12-01 2015-01-31 -180, -90, 180, 90 False copernicus, dem, elevation, geophysical https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_DEM_GLO30.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_DEM_GLO30 proprietary COPERNICUS/Landcover/100m/Proba-V-C3/Global Copernicus Global Land Cover Layers: CGLS-LC100 Collection 3 image_collection ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V-C3/Global') Copernicus 2015-01-01 2019-12-31 -180, -90, 180, 90 False copernicus, eea, esa, eu, landcover, proba, probav, vito https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_Landcover_100m_Proba-V-C3_Global.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global proprietary COPERNICUS/Landcover/100m/Proba-V/Global Copernicus Global Land Cover Layers: CGLS-LC100 Collection 2 [deprecated] image_collection ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V/Global') Copernicus 2015-01-01 2015-01-01 -180, -90, 180, 90 True copernicus, eea, esa, eu, landcover, proba, probav, vito https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_Landcover_100m_Proba-V_Global.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V_Global proprietary -COPERNICUS/S1_GRD Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar Ground Range Detected, log scaling image_collection ee.ImageCollection('COPERNICUS/S1_GRD') European Union/ESA/Copernicus 2014-10-03 2024-10-31 -180, -90, 180, 90 False backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S1_GRD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S1_GRD proprietary -COPERNICUS/S2 Sentinel-2 MSI: MultiSpectral Instrument, Level-1C [deprecated] image_collection ee.ImageCollection('COPERNICUS/S2') European Union/ESA/Copernicus 2015-06-27 2024-10-31 -180, -56, 180, 83 True copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2 proprietary -COPERNICUS/S2_CLOUD_PROBABILITY Sentinel-2: Cloud Probability image_collection ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY') European Union/ESA/Copernicus/SentinelHub 2015-06-27 2024-10-31 -180, -56, 180, 83 False cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_CLOUD_PROBABILITY.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_CLOUD_PROBABILITY proprietary -COPERNICUS/S2_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-1C image_collection ee.ImageCollection('COPERNICUS/S2_HARMONIZED') European Union/ESA/Copernicus 2015-06-27 2024-10-31 -180, -56, 180, 83 False copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_HARMONIZED proprietary -COPERNICUS/S2_SR Sentinel-2 MSI: MultiSpectral Instrument, Level-2A [deprecated] image_collection ee.ImageCollection('COPERNICUS/S2_SR') European Union/ESA/Copernicus 2017-03-28 2024-10-31 -180, -56, 180, 83 True copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR proprietary -COPERNICUS/S2_SR_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-2A image_collection ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED') European Union/ESA/Copernicus 2017-03-28 2024-10-31 -180, -56, 180, 83 False copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED proprietary -COPERNICUS/S3/OLCI Sentinel-3 OLCI EFR: Ocean and Land Color Instrument Earth Observation Full Resolution image_collection ee.ImageCollection('COPERNICUS/S3/OLCI') European Union/ESA/Copernicus 2016-10-18 2024-10-30 -180, -90, 180, 90 False copernicus, esa, eu, olci, radiance, sentinel, toa https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S3_OLCI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S3_OLCI proprietary -COPERNICUS/S5P/NRTI/L3_AER_AI Sentinel-5P NRTI AER AI: Near Real-Time UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI') European Union/ESA/Copernicus 2018-07-10 2024-10-31 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_AI proprietary -COPERNICUS/S5P/NRTI/L3_AER_LH Sentinel-5P NRTI AER LH: Near Real-Time UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH') European Union/ESA/Copernicus 2018-07-10 2024-10-31 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_LH proprietary -COPERNICUS/S5P/NRTI/L3_CLOUD Sentinel-5P NRTI CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD') European Union/ESA/Copernicus 2018-07-05 2024-10-31 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CLOUD proprietary -COPERNICUS/S5P/NRTI/L3_CO Sentinel-5P NRTI CO: Near Real-Time Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO') European Union/ESA/Copernicus 2018-11-22 2024-10-31 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CO proprietary -COPERNICUS/S5P/NRTI/L3_HCHO Sentinel-5P NRTI HCHO: Near Real-Time Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO') European Union/ESA/Copernicus 2018-10-02 2024-10-31 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_HCHO proprietary -COPERNICUS/S5P/NRTI/L3_NO2 Sentinel-5P NRTI NO2: Near Real-Time Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2') European Union/ESA/Copernicus 2018-07-10 2024-10-31 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_NO2 proprietary -COPERNICUS/S5P/NRTI/L3_O3 Sentinel-5P NRTI O3: Near Real-Time Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3') European Union/ESA/Copernicus 2018-07-10 2024-10-31 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_O3 proprietary -COPERNICUS/S5P/NRTI/L3_SO2 Sentinel-5P NRTI SO2: Near Real-Time Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2') European Union/ESA/Copernicus 2018-07-10 2024-10-31 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_SO2 proprietary -COPERNICUS/S5P/OFFL/L3_AER_AI Sentinel-5P OFFL AER AI: Offline UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_AI') European Union/ESA/Copernicus 2018-07-04 2024-10-29 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_AI proprietary -COPERNICUS/S5P/OFFL/L3_AER_LH Sentinel-5P OFFL AER LH: Offline UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_LH') European Union/ESA/Copernicus 2018-07-04 2024-10-29 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_LH proprietary -COPERNICUS/S5P/OFFL/L3_CH4 Sentinel-5P OFFL CH4: Offline Methane image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CH4') European Union/ESA/Copernicus 2019-02-08 2024-10-29 -180, -90, 180, 90 False climate, copernicus, esa, eu, knmi, methane, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CH4.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CH4 proprietary -COPERNICUS/S5P/OFFL/L3_CLOUD Sentinel-5P OFFL CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CLOUD') European Union/ESA/Copernicus 2018-07-04 2024-10-29 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CLOUD proprietary -COPERNICUS/S5P/OFFL/L3_CO Sentinel-5P OFFL CO: Offline Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CO') European Union/ESA/Copernicus 2018-06-28 2024-10-29 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CO proprietary -COPERNICUS/S5P/OFFL/L3_HCHO Sentinel-5P OFFL HCHO: Offline Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO') European Union/ESA/Copernicus 2018-12-05 2024-10-29 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_HCHO proprietary -COPERNICUS/S5P/OFFL/L3_NO2 Sentinel-5P OFFL NO2: Offline Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2') European Union/ESA/Copernicus 2018-06-28 2024-10-22 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_NO2 proprietary -COPERNICUS/S5P/OFFL/L3_O3 Sentinel-5P OFFL O3: Offline Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3') European Union/ESA/Copernicus 2018-09-08 2024-10-29 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3 proprietary +COPERNICUS/S1_GRD Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar Ground Range Detected, log scaling image_collection ee.ImageCollection('COPERNICUS/S1_GRD') European Union/ESA/Copernicus 2014-10-03 2024-11-01 -180, -90, 180, 90 False backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S1_GRD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S1_GRD proprietary +COPERNICUS/S2 Sentinel-2 MSI: MultiSpectral Instrument, Level-1C [deprecated] image_collection ee.ImageCollection('COPERNICUS/S2') European Union/ESA/Copernicus 2015-06-27 2024-11-01 -180, -56, 180, 83 True copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2 proprietary +COPERNICUS/S2_CLOUD_PROBABILITY Sentinel-2: Cloud Probability image_collection ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY') European Union/ESA/Copernicus/SentinelHub 2015-06-27 2024-11-01 -180, -56, 180, 83 False cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_CLOUD_PROBABILITY.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_CLOUD_PROBABILITY proprietary +COPERNICUS/S2_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-1C image_collection ee.ImageCollection('COPERNICUS/S2_HARMONIZED') European Union/ESA/Copernicus 2015-06-27 2024-11-01 -180, -56, 180, 83 False copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_HARMONIZED proprietary +COPERNICUS/S2_SR Sentinel-2 MSI: MultiSpectral Instrument, Level-2A [deprecated] image_collection ee.ImageCollection('COPERNICUS/S2_SR') European Union/ESA/Copernicus 2017-03-28 2024-11-01 -180, -56, 180, 83 True copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR proprietary +COPERNICUS/S2_SR_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-2A image_collection ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED') European Union/ESA/Copernicus 2017-03-28 2024-11-01 -180, -56, 180, 83 False copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED proprietary +COPERNICUS/S3/OLCI Sentinel-3 OLCI EFR: Ocean and Land Color Instrument Earth Observation Full Resolution image_collection ee.ImageCollection('COPERNICUS/S3/OLCI') European Union/ESA/Copernicus 2016-10-18 2024-10-31 -180, -90, 180, 90 False copernicus, esa, eu, olci, radiance, sentinel, toa https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S3_OLCI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S3_OLCI proprietary +COPERNICUS/S5P/NRTI/L3_AER_AI Sentinel-5P NRTI AER AI: Near Real-Time UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI') European Union/ESA/Copernicus 2018-07-10 2024-11-01 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_AI proprietary +COPERNICUS/S5P/NRTI/L3_AER_LH Sentinel-5P NRTI AER LH: Near Real-Time UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH') European Union/ESA/Copernicus 2018-07-10 2024-11-01 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_LH proprietary +COPERNICUS/S5P/NRTI/L3_CLOUD Sentinel-5P NRTI CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD') European Union/ESA/Copernicus 2018-07-05 2024-11-01 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CLOUD proprietary +COPERNICUS/S5P/NRTI/L3_CO Sentinel-5P NRTI CO: Near Real-Time Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO') European Union/ESA/Copernicus 2018-11-22 2024-11-01 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CO proprietary +COPERNICUS/S5P/NRTI/L3_HCHO Sentinel-5P NRTI HCHO: Near Real-Time Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO') European Union/ESA/Copernicus 2018-10-02 2024-11-01 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_HCHO proprietary +COPERNICUS/S5P/NRTI/L3_NO2 Sentinel-5P NRTI NO2: Near Real-Time Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2') European Union/ESA/Copernicus 2018-07-10 2024-11-01 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_NO2 proprietary +COPERNICUS/S5P/NRTI/L3_O3 Sentinel-5P NRTI O3: Near Real-Time Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3') European Union/ESA/Copernicus 2018-07-10 2024-11-01 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_O3 proprietary +COPERNICUS/S5P/NRTI/L3_SO2 Sentinel-5P NRTI SO2: Near Real-Time Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2') European Union/ESA/Copernicus 2018-07-10 2024-11-01 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_SO2 proprietary +COPERNICUS/S5P/OFFL/L3_AER_AI Sentinel-5P OFFL AER AI: Offline UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_AI') European Union/ESA/Copernicus 2018-07-04 2024-10-30 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_AI proprietary +COPERNICUS/S5P/OFFL/L3_AER_LH Sentinel-5P OFFL AER LH: Offline UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_LH') European Union/ESA/Copernicus 2018-07-04 2024-10-30 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_LH proprietary +COPERNICUS/S5P/OFFL/L3_CH4 Sentinel-5P OFFL CH4: Offline Methane image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CH4') European Union/ESA/Copernicus 2019-02-08 2024-10-30 -180, -90, 180, 90 False climate, copernicus, esa, eu, knmi, methane, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CH4.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CH4 proprietary +COPERNICUS/S5P/OFFL/L3_CLOUD Sentinel-5P OFFL CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CLOUD') European Union/ESA/Copernicus 2018-07-04 2024-10-30 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CLOUD proprietary +COPERNICUS/S5P/OFFL/L3_CO Sentinel-5P OFFL CO: Offline Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CO') European Union/ESA/Copernicus 2018-06-28 2024-10-30 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CO proprietary +COPERNICUS/S5P/OFFL/L3_HCHO Sentinel-5P OFFL HCHO: Offline Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO') European Union/ESA/Copernicus 2018-12-05 2024-10-30 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_HCHO proprietary +COPERNICUS/S5P/OFFL/L3_NO2 Sentinel-5P OFFL NO2: Offline Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2') European Union/ESA/Copernicus 2018-06-28 2024-10-23 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_NO2 proprietary +COPERNICUS/S5P/OFFL/L3_O3 Sentinel-5P OFFL O3: Offline Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3') European Union/ESA/Copernicus 2018-09-08 2024-10-30 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3 proprietary COPERNICUS/S5P/OFFL/L3_O3_TCL Sentinel-5P OFFL O3 TCL: Offline Tropospheric Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3_TCL') European Union/ESA/Copernicus 2018-04-30 2024-10-16 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3_TCL.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3_TCL proprietary -COPERNICUS/S5P/OFFL/L3_SO2 Sentinel-5P OFFL SO2: Offline Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2') European Union/ESA/Copernicus 2018-12-05 2024-10-29 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_SO2 proprietary +COPERNICUS/S5P/OFFL/L3_SO2 Sentinel-5P OFFL SO2: Offline Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2') European Union/ESA/Copernicus 2018-12-05 2024-10-30 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_SO2 proprietary CPOM/CryoSat2/ANTARCTICA_DEM CryoSat-2 Antarctica 1km DEM image ee.Image('CPOM/CryoSat2/ANTARCTICA_DEM') CPOM 2010-07-01 2016-07-01 -180, -88, 180, -60 False antarctica, cpom, cryosat_2, dem, elevation, polar https://storage.googleapis.com/earthengine-stac/catalog/CPOM/CPOM_CryoSat2_ANTARCTICA_DEM.json https://developers.google.com/earth-engine/datasets/catalog/CPOM_CryoSat2_ANTARCTICA_DEM proprietary CSIC/SPEI/2_8 SPEIbase: Standardised Precipitation-Evapotranspiration Index database, Version 2.8 [deprecated] image_collection ee.ImageCollection('CSIC/SPEI/2_8') Spanish National Research Council (CSIC) 1901-01-01 2021-01-01 -180, -90, 180, 90 True climate, climate_change, drought, evapotranspiration, global, monthly, palmer, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/CSIC/CSIC_SPEI_2_8.json https://developers.google.com/earth-engine/datasets/catalog/CSIC_SPEI_2_8 CC-BY-4.0 CSIC/SPEI/2_9 SPEIbase: Standardised Precipitation-Evapotranspiration Index database, Version 2.9 image_collection ee.ImageCollection('CSIC/SPEI/2_9') Spanish National Research Council (CSIC) 1901-01-01 2023-01-01 -180, -90, 180, 90 False climate, climate_change, drought, evapotranspiration, global, monthly, palmer, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/CSIC/CSIC_SPEI_2_9.json https://developers.google.com/earth-engine/datasets/catalog/CSIC_SPEI_2_9 CC-BY-4.0 @@ -86,11 +86,11 @@ CSP/ERGo/1_0/US/topoDiversity US NED Topographic Diversity image ee.Image('CSP/E CSP/HM/GlobalHumanModification CSP gHM: Global Human Modification image_collection ee.ImageCollection('CSP/HM/GlobalHumanModification') Conservation Science Partners 2016-01-01 2016-12-31 -180, -90, 180, 90 False csp, fragmentation, human_modification, landcover, landscape_gradient, stressors, tnc https://storage.googleapis.com/earthengine-stac/catalog/CSP/CSP_HM_GlobalHumanModification.json https://developers.google.com/earth-engine/datasets/catalog/CSP_HM_GlobalHumanModification CC-BY-NC-SA-4.0 DLR/WSF/WSF2015/v1 World Settlement Footprint 2015 image ee.Image('DLR/WSF/WSF2015/v1') Deutsches Zentrum für Luft- und Raumfahrt (DLR) 2015-01-01 2016-01-01 -180, -90, 180, 90 False landcover, landsat_derived, sentinel1_derived, settlement, urban https://storage.googleapis.com/earthengine-stac/catalog/DLR/DLR_WSF_WSF2015_v1.json https://developers.google.com/earth-engine/datasets/catalog/DLR_WSF_WSF2015_v1 CC0-1.0 DOE/ORNL/LandScan_HD/Ukraine_202201 LandScan High Definition Data for Ukraine, January 2022 image ee.Image('DOE/ORNL/LandScan_HD/Ukraine_202201') Oak Ridge National Laboratory 2022-01-01 2022-02-01 22.125, 44.175, 40.225, 52.4 False landscan, population, ukraine https://storage.googleapis.com/earthengine-stac/catalog/DOE/DOE_ORNL_LandScan_HD_Ukraine_202201.json https://developers.google.com/earth-engine/datasets/catalog/DOE_ORNL_LandScan_HD_Ukraine_202201 CC-BY-4.0 -ECMWF/CAMS/NRT Copernicus Atmosphere Monitoring Service (CAMS) Global Near-Real-Time image_collection ee.ImageCollection('ECMWF/CAMS/NRT') European Centre for Medium-Range Weather Forecasts (ECMWF) 2016-06-22 2024-10-31 -180, -90, 180, 90 False aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_CAMS_NRT.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_CAMS_NRT proprietary +ECMWF/CAMS/NRT Copernicus Atmosphere Monitoring Service (CAMS) Global Near-Real-Time image_collection ee.ImageCollection('ECMWF/CAMS/NRT') European Centre for Medium-Range Weather Forecasts (ECMWF) 2016-06-22 2024-11-01 -180, -90, 180, 90 False aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_CAMS_NRT.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_CAMS_NRT proprietary ECMWF/ERA5/DAILY ERA5 Daily Aggregates - Latest Climate Reanalysis Produced by ECMWF / Copernicus Climate Change Service image_collection ee.ImageCollection('ECMWF/ERA5/DAILY') ECMWF / Copernicus Climate Change Service 1979-01-02 2020-07-09 -180, -90, 180, 90 False climate, copernicus, dewpoint, ecmwf, era5, precipitation, pressure, reanalysis, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_DAILY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_DAILY proprietary ECMWF/ERA5/MONTHLY ERA5 Monthly Aggregates - Latest Climate Reanalysis Produced by ECMWF / Copernicus Climate Change Service image_collection ee.ImageCollection('ECMWF/ERA5/MONTHLY') ECMWF / Copernicus Climate Change Service 1979-01-01 2020-06-01 -180, -90, 180, 90 False climate, copernicus, dewpoint, ecmwf, era5, precipitation, pressure, reanalysis, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_MONTHLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_MONTHLY proprietary -ECMWF/ERA5_LAND/DAILY_AGGR ERA5-Land Daily Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR') Daily Aggregates: Google and Copernicus Climate Data Store 1950-01-02 2024-10-24 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_DAILY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_DAILY_AGGR proprietary -ECMWF/ERA5_LAND/HOURLY ERA5-Land Hourly - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY') Copernicus Climate Data Store 1950-01-01 2024-10-25 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_HOURLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_HOURLY proprietary +ECMWF/ERA5_LAND/DAILY_AGGR ERA5-Land Daily Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR') Daily Aggregates: Google and Copernicus Climate Data Store 1950-01-02 2024-10-25 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_DAILY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_DAILY_AGGR proprietary +ECMWF/ERA5_LAND/HOURLY ERA5-Land Hourly - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY') Copernicus Climate Data Store 1950-01-01 2024-10-26 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_HOURLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_HOURLY proprietary ECMWF/ERA5_LAND/MONTHLY ERA5-Land Monthly Averaged - ECMWF Climate Reanalysis [deprecated] image_collection ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY') Copernicus Climate Data Store 1950-02-01 2023-04-01 -180, -90, 180, 90 True cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_MONTHLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_MONTHLY proprietary ECMWF/ERA5_LAND/MONTHLY_AGGR ERA5-Land Monthly Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_AGGR') Monthly Aggregates: Google and Copernicus Climate Data Store 1950-02-01 2024-09-01 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_MONTHLY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_MONTHLY_AGGR proprietary ECMWF/ERA5_LAND/MONTHLY_BY_HOUR ERA5-Land Monthly Averaged by Hour of Day - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_BY_HOUR') Climate Data Store 1950-01-01 2024-09-01 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_MONTHLY_BY_HOUR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_MONTHLY_BY_HOUR proprietary @@ -148,8 +148,8 @@ GLIMS/20230607 GLIMS 2023: Global Land Ice Measurements From Space table ee.Feat GLIMS/current GLIMS Current: Global Land Ice Measurements From Space table ee.FeatureCollection('GLIMS/current') National Snow and Ice Data Center (NSDIC) 1750-01-01 2023-06-07 -180, -90, 180, 90 False glacier, glims, ice, landcover, nasa, nsidc, snow https://storage.googleapis.com/earthengine-stac/catalog/GLIMS/GLIMS_current.json https://developers.google.com/earth-engine/datasets/catalog/GLIMS_current proprietary GLOBAL_FLOOD_DB/MODIS_EVENTS/V1 Global Flood Database v1 (2000-2018) image_collection ee.ImageCollection('GLOBAL_FLOOD_DB/MODIS_EVENTS/V1') Cloud to Street (C2S) / Dartmouth Flood Observatory (DFO) 2000-02-17 2018-12-10 -180, -90, 180, 90 False c2s, cloudtostreet, dartmouth, dfo, flood, gfd, inundation, surface, water https://storage.googleapis.com/earthengine-stac/catalog/GLOBAL_FLOOD_DB/GLOBAL_FLOOD_DB_MODIS_EVENTS_V1.json https://developers.google.com/earth-engine/datasets/catalog/GLOBAL_FLOOD_DB_MODIS_EVENTS_V1 CC-BY-NC-4.0 GOOGLE/AirView/California_Unified_2015_2019 Google Street View Air Quality: High Resolution Air Pollution Mapping in California table ee.FeatureCollection('GOOGLE/AirView/California_Unified_2015_2019') Google / Aclima 2015-05-28 2019-06-07 -180, -90, 180, 90 False air_quality, nitrogen_dioxide, pollution https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_AirView_California_Unified_2015_2019.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_AirView_California_Unified_2015_2019 CC-BY-NC-4.0 -GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED Cloud Score+ S2_HARMONIZED V1 image_collection ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED') Google Earth Engine 2015-06-27 2024-10-31 -180, -90, 180, 90 False google, cloud, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED CC-BY-4.0 -GOOGLE/DYNAMICWORLD/V1 Dynamic World V1 image_collection ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1') World Resources Institute 2015-06-27 2024-10-31 -180, -90, 180, 90 False global, google, landcover, landuse, nrt, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_DYNAMICWORLD_V1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1 CC-BY-4.0 +GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED Cloud Score+ S2_HARMONIZED V1 image_collection ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED') Google Earth Engine 2015-06-27 2024-11-01 -180, -90, 180, 90 False google, cloud, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED CC-BY-4.0 +GOOGLE/DYNAMICWORLD/V1 Dynamic World V1 image_collection ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1') World Resources Institute 2015-06-27 2024-11-01 -180, -90, 180, 90 False global, google, landcover, landuse, nrt, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_DYNAMICWORLD_V1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1 CC-BY-4.0 GOOGLE/GLOBAL_CCDC/V1 Google Global Landsat-based CCDC Segments (1999-2019) image_collection ee.ImageCollection('GOOGLE/GLOBAL_CCDC/V1') Google 1999-01-01 2020-01-01 -180, -60, 180, 72 False change_detection, google, landcover, landsat_derived, landuse https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_GLOBAL_CCDC_V1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_GLOBAL_CCDC_V1 CC-BY-4.0 GOOGLE/Research/open-buildings-temporal/v1 Open Buildings Temporal V1 image_collection ee.ImageCollection('GOOGLE/Research/open-buildings-temporal/v1') Google Research - Open Buildings 2016-06-30 2023-06-30 -180, -90, 180, 90 False building_height, height, annual, built_up, open_buildings, africa, asia, south_asia, southeast_asia, high_resolution https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_Research_open-buildings-temporal_v1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings-temporal_v1 CC-BY-4.0 GOOGLE/Research/open-buildings/v1/polygons Open Buildings V1 Polygons [deprecated] table ee.FeatureCollection('GOOGLE/Research/open-buildings/v1/polygons') Google Research - Open Buildings 2021-04-30 2021-04-30 -180, -90, 180, 90 True africa, building, built_up, open_buildings, structure https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_Research_open-buildings_v1_polygons.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v1_polygons CC-BY-4.0 @@ -165,7 +165,7 @@ HYCOM/GLBu0_08/sea_water_velocity HYCOM: Hybrid Coordinate Ocean Model, Water Ve HYCOM/sea_surface_elevation HYCOM: Hybrid Coordinate Ocean Model, Sea Surface Elevation image_collection ee.ImageCollection('HYCOM/sea_surface_elevation') NOPP 1992-10-02 2024-09-05 -180, -80.48, 180, 80.48 False elevation, hycom, nopp, ocean, ssh, water https://storage.googleapis.com/earthengine-stac/catalog/HYCOM/HYCOM_sea_surface_elevation.json https://developers.google.com/earth-engine/datasets/catalog/HYCOM_sea_surface_elevation proprietary HYCOM/sea_temp_salinity HYCOM: Hybrid Coordinate Ocean Model, Water Temperature and Salinity image_collection ee.ImageCollection('HYCOM/sea_temp_salinity') NOPP 1992-10-02 2024-09-05 -180, -80.48, 180, 80.48 False hycom, nopp, ocean, salinity, sst, water, water_temp https://storage.googleapis.com/earthengine-stac/catalog/HYCOM/HYCOM_sea_temp_salinity.json https://developers.google.com/earth-engine/datasets/catalog/HYCOM_sea_temp_salinity proprietary HYCOM/sea_water_velocity HYCOM: Hybrid Coordinate Ocean Model, Water Velocity image_collection ee.ImageCollection('HYCOM/sea_water_velocity') NOPP 1992-10-02 2024-09-05 -180, -80.48, 180, 80.48 False hycom, nopp, ocean, velocity, water https://storage.googleapis.com/earthengine-stac/catalog/HYCOM/HYCOM_sea_water_velocity.json https://developers.google.com/earth-engine/datasets/catalog/HYCOM_sea_water_velocity proprietary -IDAHO_EPSCOR/GRIDMET GRIDMET: University of Idaho Gridded Surface Meteorological Dataset image_collection ee.ImageCollection('IDAHO_EPSCOR/GRIDMET') University of California Merced 1979-01-01 2024-10-28 -124.9, 24.9, -66.8, 49.6 False climate, fireburning, gridmet, humidity, merced, metdata, nfdrs, precipitation, radiation, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_GRIDMET.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_GRIDMET proprietary +IDAHO_EPSCOR/GRIDMET GRIDMET: University of Idaho Gridded Surface Meteorological Dataset image_collection ee.ImageCollection('IDAHO_EPSCOR/GRIDMET') University of California Merced 1979-01-01 2024-10-29 -124.9, 24.9, -66.8, 49.6 False climate, fireburning, gridmet, humidity, merced, metdata, nfdrs, precipitation, radiation, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_GRIDMET.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_GRIDMET proprietary IDAHO_EPSCOR/MACAv2_METDATA MACAv2-METDATA: University of Idaho, Multivariate Adaptive Constructed Analogs Applied to Global Climate Models image_collection ee.ImageCollection('IDAHO_EPSCOR/MACAv2_METDATA') University of California Merced 1900-01-01 2100-12-31 -124.9, 24.9, -67, 49.6 False climate, conus, geophysical, idaho, maca, monthly https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_MACAv2_METDATA.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_MACAv2_METDATA CC0-1.0 IDAHO_EPSCOR/MACAv2_METDATA_MONTHLY MACAv2-METDATA Monthly Summaries: University of Idaho, Multivariate Adaptive Constructed Analogs Applied to Global Climate Models image_collection ee.ImageCollection('IDAHO_EPSCOR/MACAv2_METDATA_MONTHLY') University of California Merced 1900-01-01 2099-12-31 -124.9, 24.9, -67, 49.6 False climate, conus, geophysical, idaho, maca, monthly https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_MACAv2_METDATA_MONTHLY.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_MACAv2_METDATA_MONTHLY CC0-1.0 IDAHO_EPSCOR/PDSI PDSI: University of Idaho Palmer Drought Severity Index [deprecated] image_collection ee.ImageCollection('IDAHO_EPSCOR/PDSI') University of California Merced 1979-03-01 2020-06-20 -124.9, 24.9, -66.8, 49.6 True climate, conus, crop, drought, geophysical, merced, palmer, pdsi https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_PDSI.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_PDSI proprietary @@ -200,27 +200,27 @@ JAXA/ALOS/AW3D30/V2_1 ALOS DSM: Global 30m v2.1 [deprecated] image ee.Image('JAX JAXA/ALOS/AW3D30/V2_2 ALOS DSM: Global 30m v2.2 [deprecated] image ee.Image('JAXA/ALOS/AW3D30/V2_2') JAXA Earth Observation Research Center 2006-01-24 2011-05-12 -180, -90, 180, 90 True alos, dem, elevation, geophysical, jaxa, topography https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_AW3D30_V2_2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_AW3D30_V2_2 proprietary JAXA/ALOS/AW3D30/V3_2 ALOS DSM: Global 30m v3.2 image_collection ee.ImageCollection('JAXA/ALOS/AW3D30/V3_2') JAXA Earth Observation Research Center 2006-01-24 2011-05-12 -180, -90, 180, 90 False alos, dem, elevation, geophysical, jaxa, topography https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_AW3D30_V3_2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_AW3D30_V3_2 proprietary JAXA/ALOS/PALSAR-2/Level2_1/StripMap_202401 ALOS-2 PALSAR-2 StripMap Level 2.1 image_collection ee.ImageCollection('JAXA/ALOS/PALSAR-2/Level2_1/StripMap_202401') JAXA EORC 2022-09-26 2024-01-08 -180, -90, 180, 90 False alos2, eroc, jaxa, palsar2, radar, sar https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_PALSAR-2_Level2_1_StripMap_202401.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR-2_Level2_1_StripMap_202401 CC-BY-NC-SA-4.0 -JAXA/ALOS/PALSAR-2/Level2_2/ScanSAR PALSAR-2 ScanSAR Level 2.2 image_collection ee.ImageCollection('JAXA/ALOS/PALSAR-2/Level2_2/ScanSAR') JAXA EORC 2014-08-04 2024-08-31 -180, -90, 180, 90 False alos2, eroc, jaxa, palsar2, radar, sar https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_PALSAR-2_Level2_2_ScanSAR.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR-2_Level2_2_ScanSAR proprietary +JAXA/ALOS/PALSAR-2/Level2_2/ScanSAR PALSAR-2 ScanSAR Level 2.2 image_collection ee.ImageCollection('JAXA/ALOS/PALSAR-2/Level2_2/ScanSAR') JAXA EORC 2014-08-04 2024-09-05 -180, -90, 180, 90 False alos2, eroc, jaxa, palsar2, radar, sar https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_PALSAR-2_Level2_2_ScanSAR.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR-2_Level2_2_ScanSAR proprietary JAXA/ALOS/PALSAR/YEARLY/FNF Global 3-class PALSAR-2/PALSAR Forest/Non-Forest Map image_collection ee.ImageCollection('JAXA/ALOS/PALSAR/YEARLY/FNF') JAXA EORC 2007-01-01 2018-01-01 -180, -90, 180, 90 False alos, alos2, classification, eroc, forest, jaxa, landcover, palsar, palsar2, sar https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_PALSAR_YEARLY_FNF.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_FNF proprietary JAXA/ALOS/PALSAR/YEARLY/FNF4 Global 4-class PALSAR-2/PALSAR Forest/Non-Forest Map image_collection ee.ImageCollection('JAXA/ALOS/PALSAR/YEARLY/FNF4') JAXA EORC 2017-01-01 2021-01-01 -180, -90, 180, 90 False alos, alos2, classification, eroc, forest, jaxa, landcover, palsar, palsar2, sar https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_PALSAR_YEARLY_FNF4.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_FNF4 proprietary JAXA/ALOS/PALSAR/YEARLY/SAR Global PALSAR-2/PALSAR Yearly Mosaic, version 1 image_collection ee.ImageCollection('JAXA/ALOS/PALSAR/YEARLY/SAR') JAXA EORC 2007-01-01 2020-01-01 -180, -90, 180, 90 False alos, alos2, eroc, jaxa, palsar, palsar2, sar https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_PALSAR_YEARLY_SAR.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_SAR proprietary JAXA/ALOS/PALSAR/YEARLY/SAR_EPOCH Global PALSAR-2/PALSAR Yearly Mosaic, version 2 image_collection ee.ImageCollection('JAXA/ALOS/PALSAR/YEARLY/SAR_EPOCH') JAXA EORC 2015-01-01 2023-01-01 -180, -90, 180, 90 False alos, alos2, eroc, jaxa, palsar, palsar2, sar https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_PALSAR_YEARLY_SAR_EPOCH.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_SAR_EPOCH proprietary JAXA/GCOM-C/L3/LAND/LAI/V1 GCOM-C/SGLI L3 Leaf Area Index (V1) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V1') Global Change Observation Mission (GCOM) 2018-01-01 2020-06-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LAI_V1.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LAI_V1 proprietary JAXA/GCOM-C/L3/LAND/LAI/V2 GCOM-C/SGLI L3 Leaf Area Index (V2) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V2') Global Change Observation Mission (GCOM) 2018-01-01 2021-11-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LAI_V2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LAI_V2 proprietary -JAXA/GCOM-C/L3/LAND/LAI/V3 GCOM-C/SGLI L3 Leaf Area Index (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-10-29 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LAI_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LAI_V3 proprietary +JAXA/GCOM-C/L3/LAND/LAI/V3 GCOM-C/SGLI L3 Leaf Area Index (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-10-31 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LAI_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LAI_V3 proprietary JAXA/GCOM-C/L3/LAND/LST/V1 GCOM-C/SGLI L3 Land Surface Temperature (V1) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V1') Global Change Observation Mission (GCOM) 2018-01-01 2020-06-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LST_V1.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LST_V1 proprietary JAXA/GCOM-C/L3/LAND/LST/V2 GCOM-C/SGLI L3 Land Surface Temperature (V2) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V2') Global Change Observation Mission (GCOM) 2018-01-01 2021-11-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LST_V2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LST_V2 proprietary -JAXA/GCOM-C/L3/LAND/LST/V3 GCOM-C/SGLI L3 Land Surface Temperature (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-10-29 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LST_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LST_V3 proprietary +JAXA/GCOM-C/L3/LAND/LST/V3 GCOM-C/SGLI L3 Land Surface Temperature (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-10-31 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LST_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LST_V3 proprietary JAXA/GCOM-C/L3/OCEAN/CHLA/V1 GCOM-C/SGLI L3 Chlorophyll-a Concentration (V1) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V1') Global Change Observation Mission (GCOM) 2018-01-01 2020-06-28 -180, -90, 180, 90 False chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_CHLA_V1.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_CHLA_V1 proprietary JAXA/GCOM-C/L3/OCEAN/CHLA/V2 GCOM-C/SGLI L3 Chlorophyll-a Concentration (V2) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V2') Global Change Observation Mission (GCOM) 2018-01-01 2021-11-28 -180, -90, 180, 90 False chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_CHLA_V2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_CHLA_V2 proprietary -JAXA/GCOM-C/L3/OCEAN/CHLA/V3 GCOM-C/SGLI L3 Chlorophyll-a Concentration (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-10-29 -180, -90, 180, 90 False chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_CHLA_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_CHLA_V3 proprietary +JAXA/GCOM-C/L3/OCEAN/CHLA/V3 GCOM-C/SGLI L3 Chlorophyll-a Concentration (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-10-30 -180, -90, 180, 90 False chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_CHLA_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_CHLA_V3 proprietary JAXA/GCOM-C/L3/OCEAN/SST/V1 GCOM-C/SGLI L3 Sea Surface Temperature (V1) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V1') Global Change Observation Mission (GCOM) 2018-01-01 2020-06-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_SST_V1.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_SST_V1 proprietary JAXA/GCOM-C/L3/OCEAN/SST/V2 GCOM-C/SGLI L3 Sea Surface Temperature (V2) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V2') Global Change Observation Mission (GCOM) 2018-01-01 2021-11-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_SST_V2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_SST_V2 proprietary -JAXA/GCOM-C/L3/OCEAN/SST/V3 GCOM-C/SGLI L3 Sea Surface Temperature (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-10-29 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_SST_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_SST_V3 proprietary -JAXA/GPM_L3/GSMaP/v6/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V6 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v6/operational') JAXA Earth Observation Research Center 2014-03-01 2024-10-31 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v6_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v6_operational proprietary +JAXA/GCOM-C/L3/OCEAN/SST/V3 GCOM-C/SGLI L3 Sea Surface Temperature (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-10-30 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_SST_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_SST_V3 proprietary +JAXA/GPM_L3/GSMaP/v6/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V6 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v6/operational') JAXA Earth Observation Research Center 2014-03-01 2024-11-01 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v6_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v6_operational proprietary JAXA/GPM_L3/GSMaP/v6/reanalysis GSMaP Reanalysis: Global Satellite Mapping of Precipitation image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v6/reanalysis') JAXA Earth Observation Research Center 2000-03-01 2014-03-12 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v6_reanalysis.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v6_reanalysis proprietary -JAXA/GPM_L3/GSMaP/v7/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V7 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v7/operational') JAXA Earth Observation Research Center 2014-03-01 2024-10-31 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v7_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v7_operational proprietary -JAXA/GPM_L3/GSMaP/v8/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V8 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v8/operational') JAXA Earth Observation Research Center 1998-01-01 2024-10-31 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v8_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v8_operational proprietary +JAXA/GPM_L3/GSMaP/v7/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V7 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v7/operational') JAXA Earth Observation Research Center 2014-03-01 2024-11-01 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v7_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v7_operational proprietary +JAXA/GPM_L3/GSMaP/v8/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V8 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v8/operational') JAXA Earth Observation Research Center 1998-01-01 2024-11-01 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v8_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v8_operational proprietary JCU/Murray/GIC/global_tidal_wetland_change/2019 Murray Global Tidal Wetland Change v1.0 (1999-2019) image ee.Image('JCU/Murray/GIC/global_tidal_wetland_change/2019') Murray/JCU 1999-01-01 2019-12-31 -180, -90, 180, 90 False coastal, ecosystem, intertidal, landsat_derived, mangrove, murray, saltmarsh, tidal_flat, tidal_marsh https://storage.googleapis.com/earthengine-stac/catalog/JCU/JCU_Murray_GIC_global_tidal_wetland_change_2019.json https://developers.google.com/earth-engine/datasets/catalog/JCU_Murray_GIC_global_tidal_wetland_change_2019 CC-BY-4.0 JRC/CEMS_GLOFAS/FloodHazard/v1 JRC Global River Flood Hazard Maps Version 1 image_collection ee.ImageCollection('JRC/CEMS_GLOFAS/FloodHazard/v1') Joint Research Centre 2024-03-16 2024-03-16 -180, -90, 180, 90 False flood, monitoring, wri https://storage.googleapis.com/earthengine-stac/catalog/JRC/JRC_CEMS_GLOFAS_FloodHazard_v1.json https://developers.google.com/earth-engine/datasets/catalog/JRC_CEMS_GLOFAS_FloodHazard_v1 CC-BY-4.0 JRC/D5/EUCROPMAP/V1 EUCROPMAP image_collection ee.ImageCollection('JRC/D5/EUCROPMAP/V1') Joint Research Center (JRC) 2018-01-01 2022-01-01 -16.171875, 34.313433, 36.386719, 72.182526 False crop, eu, jrc, lucas, sentinel1_derived https://storage.googleapis.com/earthengine-stac/catalog/JRC/JRC_D5_EUCROPMAP_V1.json https://developers.google.com/earth-engine/datasets/catalog/JRC_D5_EUCROPMAP_V1 CC-BY-4.0 @@ -304,15 +304,15 @@ LANDSAT/GLS2005_L5 Landsat Global Land Survey 2005, Landsat 5 scenes image_colle LANDSAT/GLS2005_L7 Landsat Global Land Survey 2005, Landsat 7 scenes image_collection ee.ImageCollection('LANDSAT/GLS2005_L7') USGS 2003-07-29 2008-07-29 -180, -90, 180, 90 False etm, gls, l7, landsat, radiance, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_GLS2005_L7.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_GLS2005_L7 PDDL-1.0 LANDSAT/LC08/C02/T1 USGS Landsat 8 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1') USGS 2013-03-18 2024-10-26 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, oli_tirs, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1 PDDL-1.0 LANDSAT/LC08/C02/T1_L2 USGS Landsat 8 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_L2') USGS 2013-03-18 2024-10-26 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l8sr, landsat, lasrc, lc08, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2 proprietary -LANDSAT/LC08/C02/T1_RT USGS Landsat 8 Collection 2 Tier 1 and Real-Time data Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_RT') USGS 2013-03-18 2024-10-31 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, nrt, oli_tirs, radiance, rt, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_RT.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_RT PDDL-1.0 -LANDSAT/LC08/C02/T1_RT_TOA USGS Landsat 8 Collection 2 Tier 1 and Real-Time data TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_RT_TOA') USGS/Google 2013-03-18 2024-10-31 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_RT_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_RT_TOA PDDL-1.0 +LANDSAT/LC08/C02/T1_RT USGS Landsat 8 Collection 2 Tier 1 and Real-Time data Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_RT') USGS 2013-03-18 2024-11-01 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, nrt, oli_tirs, radiance, rt, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_RT.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_RT PDDL-1.0 +LANDSAT/LC08/C02/T1_RT_TOA USGS Landsat 8 Collection 2 Tier 1 and Real-Time data TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_RT_TOA') USGS/Google 2013-03-18 2024-11-01 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_RT_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_RT_TOA PDDL-1.0 LANDSAT/LC08/C02/T1_TOA USGS Landsat 8 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA') USGS/Google 2013-03-18 2024-10-26 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_TOA PDDL-1.0 LANDSAT/LC08/C02/T2 USGS Landsat 8 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2') USGS 2021-10-28 2024-10-26 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, oli_tirs, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2 PDDL-1.0 LANDSAT/LC08/C02/T2_L2 USGS Landsat 8 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2_L2') USGS 2013-03-18 2024-10-26 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l8sr, landsat, lasrc, lc08, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2_L2 proprietary LANDSAT/LC08/C02/T2_TOA USGS Landsat 8 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2_TOA') USGS/Google 2021-10-28 2024-10-26 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2_TOA PDDL-1.0 -LANDSAT/LC09/C02/T1 USGS Landsat 9 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1') USGS 2021-10-31 2024-10-31 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1 PDDL-1.0 -LANDSAT/LC09/C02/T1_L2 USGS Landsat 9 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_L2') USGS 2021-10-31 2024-10-29 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_L2 proprietary -LANDSAT/LC09/C02/T1_TOA USGS Landsat 9 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA') USGS/Google 2021-10-31 2024-10-31 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_TOA PDDL-1.0 +LANDSAT/LC09/C02/T1 USGS Landsat 9 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1') USGS 2021-10-31 2024-11-01 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1 PDDL-1.0 +LANDSAT/LC09/C02/T1_L2 USGS Landsat 9 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_L2') USGS 2021-10-31 2024-10-30 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_L2 proprietary +LANDSAT/LC09/C02/T1_TOA USGS Landsat 9 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA') USGS/Google 2021-10-31 2024-11-01 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_TOA PDDL-1.0 LANDSAT/LC09/C02/T2 USGS Landsat 9 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2') USGS 2021-11-02 2024-10-31 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2 PDDL-1.0 LANDSAT/LC09/C02/T2_L2 USGS Landsat 9 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2_L2') USGS 2021-10-31 2024-10-29 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_L2 proprietary LANDSAT/LC09/C02/T2_TOA USGS Landsat 9 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2_TOA') USGS/Google 2021-11-02 2024-10-31 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_TOA PDDL-1.0 @@ -424,22 +424,22 @@ MODIS/061/MCD12Q2 MCD12Q2.006 Land Cover Dynamics Yearly Global 500m image_colle MODIS/061/MCD15A3H MCD15A3H.061 MODIS Leaf Area Index/FPAR 4-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MCD15A3H') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-23 -180, -90, 180, 90 False 4_day, fpar, global, lai, mcd15a3h, modis, nasa, usgs, vegetation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD15A3H.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD15A3H proprietary MODIS/061/MCD18A1 MCD18A1.061 Surface Radiation Daily/3-Hour image_collection ee.ImageCollection('MODIS/061/MCD18A1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-06-01 -180, -90, 180, 90 False par, radiation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD18A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD18A1 proprietary MODIS/061/MCD18C2 MCD18C2.061 Photosynthetically Active Radiation Daily 3-Hour image_collection ee.ImageCollection('MODIS/061/MCD18C2') NASA LP DAAC at the USGS EROS Center 2002-02-24 2024-06-01 -180, -90, 180, 90 False par, radiation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD18C2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD18C2 proprietary -MODIS/061/MCD19A1_GRANULES MCD19A1.061: Land Surface BRF Daily L2G Global 500m and 1km image_collection ee.ImageCollection('MODIS/061/MCD19A1_GRANULES') NASA LP DAAC at the USGS EROS Center 2000-12-21 2024-10-27 -180, -90, 180, 90 False aerosol, aod, aqua, daily, global, maiac, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD19A1_GRANULES.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD19A1_GRANULES proprietary -MODIS/061/MCD19A2_GRANULES MCD19A2.061: Terra & Aqua MAIAC Land Aerosol Optical Depth Daily 1km image_collection ee.ImageCollection('MODIS/061/MCD19A2_GRANULES') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-27 -180, -90, 180, 90 False aerosol, aod, aqua, daily, global, maiac, mcd19a2, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD19A2_GRANULES.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD19A2_GRANULES proprietary -MODIS/061/MCD43A1 MCD43A1.061 MODIS BRDF-Albedo Model Parameters Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-21 -180, -90, 180, 90 False albedo, brdf, daily, global, mcd43a1, modis, nasa, reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A1 proprietary -MODIS/061/MCD43A2 MCD43A2.061 MODIS BRDF-Albedo Quality Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A2') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-21 -180, -90, 180, 90 False albedo, brdf, daily, global, modis, nasa, quality, reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A2 proprietary -MODIS/061/MCD43A3 MCD43A3.061 MODIS Albedo Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A3') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-21 -180, -90, 180, 90 False albedo, black_sky, daily, global, modis, nasa, usgs, white_sky https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A3.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A3 proprietary -MODIS/061/MCD43A4 MCD43A4.061 MODIS Nadir BRDF-Adjusted Reflectance Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A4') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-21 -180, -90, 180, 90 False albedo, brdf, daily, global, modis, nasa, reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A4.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A4 proprietary -MODIS/061/MCD43C3 MCD43C3.061 BRDF/Albedo Daily L3 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MCD43C3') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-20 -180, -90, 180, 90 False albedo, black_sky, brdf, daily, global, modis, nasa, usgs, white_sky https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43C3.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43C3 proprietary +MODIS/061/MCD19A1_GRANULES MCD19A1.061: Land Surface BRF Daily L2G Global 500m and 1km image_collection ee.ImageCollection('MODIS/061/MCD19A1_GRANULES') NASA LP DAAC at the USGS EROS Center 2000-12-21 2024-10-29 -180, -90, 180, 90 False aerosol, aod, aqua, daily, global, maiac, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD19A1_GRANULES.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD19A1_GRANULES proprietary +MODIS/061/MCD19A2_GRANULES MCD19A2.061: Terra & Aqua MAIAC Land Aerosol Optical Depth Daily 1km image_collection ee.ImageCollection('MODIS/061/MCD19A2_GRANULES') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False aerosol, aod, aqua, daily, global, maiac, mcd19a2, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD19A2_GRANULES.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD19A2_GRANULES proprietary +MODIS/061/MCD43A1 MCD43A1.061 MODIS BRDF-Albedo Model Parameters Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-22 -180, -90, 180, 90 False albedo, brdf, daily, global, mcd43a1, modis, nasa, reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A1 proprietary +MODIS/061/MCD43A2 MCD43A2.061 MODIS BRDF-Albedo Quality Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A2') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-22 -180, -90, 180, 90 False albedo, brdf, daily, global, modis, nasa, quality, reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A2 proprietary +MODIS/061/MCD43A3 MCD43A3.061 MODIS Albedo Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A3') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-22 -180, -90, 180, 90 False albedo, black_sky, daily, global, modis, nasa, usgs, white_sky https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A3.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A3 proprietary +MODIS/061/MCD43A4 MCD43A4.061 MODIS Nadir BRDF-Adjusted Reflectance Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A4') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-22 -180, -90, 180, 90 False albedo, brdf, daily, global, modis, nasa, reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A4.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A4 proprietary +MODIS/061/MCD43C3 MCD43C3.061 BRDF/Albedo Daily L3 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MCD43C3') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-22 -180, -90, 180, 90 False albedo, black_sky, brdf, daily, global, modis, nasa, usgs, white_sky https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43C3.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43C3 proprietary MODIS/061/MCD64A1 MCD64A1.061 MODIS Burned Area Monthly Global 500m image_collection ee.ImageCollection('MODIS/061/MCD64A1') NASA LP DAAC at the USGS EROS Center 2000-11-01 2024-08-01 -180, -90, 180, 90 False burn, change_detection, fire, geophysical, global, mcd64a1, modis, monthly, nasa, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD64A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD64A1 proprietary MODIS/061/MOD08_M3 MOD08_M3.061 Terra Atmosphere Monthly Global Product image_collection ee.ImageCollection('MODIS/061/MOD08_M3') NASA LAADS DAAC at NASA Goddard Space Flight Center 2000-02-01 2024-09-01 -180, -90, 180, 90 False atmosphere, geophysical, global, mod08, mod08_m3, modis, monthly, nasa, temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD08_M3.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD08_M3 proprietary MODIS/061/MOD09A1 MOD09A1.061 Terra Surface Reflectance 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MOD09A1') NASA LP DAAC at the USGS EROS Center 2000-02-18 2024-10-15 -180, -90, 180, 90 False 8_day, global, mod09a1, modis, nasa, sr, surface_reflectance, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD09A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD09A1 proprietary MODIS/061/MOD09CMG MOD09CMG.061 Terra Surface Reflectance Daily L3 Global 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MOD09CMG') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False brightness_temperature, ozone, surface_reflectance, terra https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD09CMG.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD09CMG proprietary -MODIS/061/MOD09GA MOD09GA.061 Terra Surface Reflectance Daily Global 1km and 500m image_collection ee.ImageCollection('MODIS/061/MOD09GA') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-28 -180, -90, 180, 90 False daily, global, mod09ga, modis, nasa, sr, surface_reflectance, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD09GA.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD09GA proprietary -MODIS/061/MOD09GQ MOD09GQ.061 Terra Surface Reflectance Daily Global 250m image_collection ee.ImageCollection('MODIS/061/MOD09GQ') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-28 -180, -90, 180, 90 False daily, global, mod09gq, modis, nasa, sr, surface_reflectance, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD09GQ.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD09GQ proprietary +MODIS/061/MOD09GA MOD09GA.061 Terra Surface Reflectance Daily Global 1km and 500m image_collection ee.ImageCollection('MODIS/061/MOD09GA') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False daily, global, mod09ga, modis, nasa, sr, surface_reflectance, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD09GA.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD09GA proprietary +MODIS/061/MOD09GQ MOD09GQ.061 Terra Surface Reflectance Daily Global 250m image_collection ee.ImageCollection('MODIS/061/MOD09GQ') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False daily, global, mod09gq, modis, nasa, sr, surface_reflectance, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD09GQ.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD09GQ proprietary MODIS/061/MOD09Q1 MOD09Q1.061 Terra Surface Reflectance 8-Day Global 250m image_collection ee.ImageCollection('MODIS/061/MOD09Q1') NASA LP DAAC at the USGS EROS Center 2000-02-18 2024-10-15 -180, -90, 180, 90 False 8_day, global, mod09q1, modis, nasa, sr, surface_reflectance, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD09Q1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD09Q1 proprietary MODIS/061/MOD10A1 MOD10A1.061 Terra Snow Cover Daily Global 500m image_collection ee.ImageCollection('MODIS/061/MOD10A1') NASA NSIDC DAAC at CIRES 2000-02-24 2024-10-29 -180, -90, 180, 90 False albedo, daily, geophysical, global, mod10a1, modis, nasa, nsidc, snow, terra https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD10A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD10A1 proprietary -MODIS/061/MOD11A1 MOD11A1.061 Terra Land Surface Temperature and Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MOD11A1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-28 -180, -90, 180, 90 False daily, emissivity, global, lst, mod11a1, modis, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD11A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD11A1 proprietary +MODIS/061/MOD11A1 MOD11A1.061 Terra Land Surface Temperature and Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MOD11A1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False daily, emissivity, global, lst, mod11a1, modis, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD11A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD11A1 proprietary MODIS/061/MOD11A2 MOD11A2.061 Terra Land Surface Temperature and Emissivity 8-Day Global 1km image_collection ee.ImageCollection('MODIS/061/MOD11A2') NASA LP DAAC at the USGS EROS Center 2000-02-18 2024-10-15 -180, -90, 180, 90 False 8_day, emissivity, global, lst, mod11a2, modis, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD11A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD11A2 proprietary MODIS/061/MOD13A1 MOD13A1.061 Terra Vegetation Indices 16-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MOD13A1') NASA LP DAAC at the USGS EROS Center 2000-02-18 2024-09-29 -180, -90, 180, 90 False 16_day, evi, global, mod13a1, modis, nasa, ndvi, terra, usgs, vegetation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD13A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD13A1 proprietary MODIS/061/MOD13A2 MOD13A2.061 Terra Vegetation Indices 16-Day Global 1km image_collection ee.ImageCollection('MODIS/061/MOD13A2') NASA LP DAAC at the USGS EROS Center 2000-02-18 2024-09-29 -180, -90, 180, 90 False 16_day, evi, global, mod13a2, modis, nasa, ndvi, terra, usgs, vegetation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD13A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD13A2 proprietary @@ -449,24 +449,24 @@ MODIS/061/MOD13Q1 MOD13Q1.061 Terra Vegetation Indices 16-Day Global 250m image_ MODIS/061/MOD14A1 MOD14A1.061: Terra Thermal Anomalies & Fire Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MOD14A1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-22 -180, -90, 180, 90 False daily, fire, global, mod14a1, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD14A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD14A1 proprietary MODIS/061/MOD14A2 MOD14A2.061: Terra Thermal Anomalies & Fire 8-Day Global 1km image_collection ee.ImageCollection('MODIS/061/MOD14A2') NASA LP DAAC at the USGS EROS Center 2000-02-18 2024-10-15 -180, -90, 180, 90 False 8_day, fire, global, mod14a2, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD14A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD14A2 proprietary MODIS/061/MOD15A2H MOD15A2H.061: Terra Leaf Area Index/FPAR 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MOD15A2H') NASA LP DAAC at the USGS EROS Center 2000-02-18 2024-10-15 -180, -90, 180, 90 False 8_day, fpar, global, lai, mod15a2h, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD15A2H.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD15A2H proprietary -MODIS/061/MOD16A2 MOD16A2.061: Terra Net Evapotranspiration 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MOD16A2') NASA LP DAAC at the USGS EROS Center 2001-01-01 2024-10-07 -180, -90, 180, 90 False 8_day, evapotranspiration, global, mod16a2, modis, nasa https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD16A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD16A2 proprietary +MODIS/061/MOD16A2 MOD16A2.061: Terra Net Evapotranspiration 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MOD16A2') NASA LP DAAC at the USGS EROS Center 2001-01-01 2024-10-15 -180, -90, 180, 90 False 8_day, evapotranspiration, global, mod16a2, modis, nasa https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD16A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD16A2 proprietary MODIS/061/MOD16A2GF MOD16A2GF.061: Terra Net Evapotranspiration Gap-Filled 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MOD16A2GF') NASA LP DAAC at the USGS EROS Center 2000-01-01 2023-12-27 -180, -90, 180, 90 False 8_day, evapotranspiration, global, modis, nasa https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD16A2GF.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD16A2GF proprietary MODIS/061/MOD17A2H MOD17A2H.061: Terra Gross Primary Productivity 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MOD17A2H') NASA LP DAAC at the USGS EROS Center 2021-01-01 2024-10-15 -180, -90, 180, 90 False 8_day, global, gpp, mod17a2, modis, nasa, photosynthesis, productivity, psn, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD17A2H.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD17A2H proprietary MODIS/061/MOD17A2HGF MOD17A2HGF.061: Terra Gross Primary Productivity 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MOD17A2HGF') NASA LP DAAC at the USGS EROS Center 2021-01-01 2023-12-27 -180, -90, 180, 90 False 8_day, global, gpp, modis, nasa, photosynthesis, productivity, psn, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD17A2HGF.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD17A2HGF proprietary MODIS/061/MOD17A3HGF MOD17A3HGF.061: Terra Net Primary Production Gap-Filled Yearly Global 500m image_collection ee.ImageCollection('MODIS/061/MOD17A3HGF') NASA LP DAAC at the USGS EROS Center 2001-01-01 2023-01-01 -180, -90, 180, 90 False global, gpp, nasa, npp, photosynthesis, productivity, psn, terra, usgs, yearly https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD17A3HGF.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD17A3HGF proprietary -MODIS/061/MOD21A1D MOD21A1D.061 Terra Land Surface Temperature and 3-Band Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MOD21A1D') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-28 -180, -90, 180, 90 False daily, emissivity, global, lst, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD21A1D.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD21A1D proprietary -MODIS/061/MOD21A1N MOD21A1N.061 Terra Land Surface Temperature and 3-Band Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MOD21A1N') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-28 -180, -90, 180, 90 False daily, emissivity, global, lst, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD21A1N.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD21A1N proprietary +MODIS/061/MOD21A1D MOD21A1D.061 Terra Land Surface Temperature and 3-Band Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MOD21A1D') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False daily, emissivity, global, lst, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD21A1D.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD21A1D proprietary +MODIS/061/MOD21A1N MOD21A1N.061 Terra Land Surface Temperature and 3-Band Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MOD21A1N') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False daily, emissivity, global, lst, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD21A1N.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD21A1N proprietary MODIS/061/MOD21C1 MOD21C1.061 Terra Land Surface Temperature and 3-Band Emissivity Daily L3 Global 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MOD21C1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False daily, emissivity, global, lst, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD21C1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD21C1 proprietary MODIS/061/MOD21C2 MOD21C2.061 Terra Land Surface Temperature and 3-Band Emissivity 8-Day L3 Global 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MOD21C2') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-15 -180, -90, 180, 90 False emissivity, global, lst, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD21C2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD21C2 proprietary MODIS/061/MOD21C3 MOD21C3.061 Terra Land Surface Temperature and 3-Band Emissivity Monthly L3 Global 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MOD21C3') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-09-01 -180, -90, 180, 90 False emissivity, global, lst, monthly, nasa, surface_temperature, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MOD21C3.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD21C3 proprietary MODIS/061/MYD08_M3 MYD08_M3.061 Aqua Atmosphere Monthly Global Product image_collection ee.ImageCollection('MODIS/061/MYD08_M3') NASA LAADS DAAC at NASA Goddard Space Flight Center 2002-07-01 2024-09-01 -180, -90, 180, 90 False aqua, atmosphere, geophysical, global, modis, monthly, myd08, myd08_m3, nasa, temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD08_M3.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD08_M3 proprietary MODIS/061/MYD09A1 MYD09A1.061 Aqua Surface Reflectance 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MYD09A1') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-15 -180, -90, 180, 90 False 8_day, aqua, global, modis, myd09a1, nasa, sr, surface_reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD09A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD09A1 proprietary MODIS/061/MYD09CMG MYD09CMG.061 Aqua Surface Reflectance Daily L3 Global 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MYD09CMG') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-29 -180, -90, 180, 90 False brightness_temperature, ozone, surface_reflectance, aqua https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD09CMG.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD09CMG proprietary -MODIS/061/MYD09GA MYD09GA.061 Aqua Surface Reflectance Daily Global 1km and 500m image_collection ee.ImageCollection('MODIS/061/MYD09GA') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-28 -180, -90, 180, 90 False aqua, daily, global, modis, myd09ga, nasa, sr, surface_reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD09GA.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD09GA proprietary -MODIS/061/MYD09GQ MYD09GQ.061 Aqua Surface Reflectance Daily Global 250m image_collection ee.ImageCollection('MODIS/061/MYD09GQ') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-28 -180, -90, 180, 90 False aqua, daily, global, modis, myd09gq, nasa, sr, surface_reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD09GQ.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD09GQ proprietary +MODIS/061/MYD09GA MYD09GA.061 Aqua Surface Reflectance Daily Global 1km and 500m image_collection ee.ImageCollection('MODIS/061/MYD09GA') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-29 -180, -90, 180, 90 False aqua, daily, global, modis, myd09ga, nasa, sr, surface_reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD09GA.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD09GA proprietary +MODIS/061/MYD09GQ MYD09GQ.061 Aqua Surface Reflectance Daily Global 250m image_collection ee.ImageCollection('MODIS/061/MYD09GQ') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-29 -180, -90, 180, 90 False aqua, daily, global, modis, myd09gq, nasa, sr, surface_reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD09GQ.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD09GQ proprietary MODIS/061/MYD09Q1 MYD09Q1.061 Aqua Surface Reflectance 8-Day Global 250m image_collection ee.ImageCollection('MODIS/061/MYD09Q1') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-15 -180, -90, 180, 90 False 8_day, aqua, global, modis, myd09q1, nasa, sr, surface_reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD09Q1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD09Q1 proprietary MODIS/061/MYD10A1 MYD10A1.061 Aqua Snow Cover Daily Global 500m image_collection ee.ImageCollection('MODIS/061/MYD10A1') NASA NSIDC DAAC at CIRES 2002-07-04 2024-10-29 -180, -90, 180, 90 False albedo, aqua, daily, geophysical, global, modis, myd10a1, nasa, nsidc, snow https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD10A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD10A1 proprietary -MODIS/061/MYD11A1 MYD11A1.061 Aqua Land Surface Temperature and Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MYD11A1') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-28 -180, -90, 180, 90 False aqua, daily, emissivity, global, lst, modis, myd11a1, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD11A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD11A1 proprietary +MODIS/061/MYD11A1 MYD11A1.061 Aqua Land Surface Temperature and Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MYD11A1') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-29 -180, -90, 180, 90 False aqua, daily, emissivity, global, lst, modis, myd11a1, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD11A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD11A1 proprietary MODIS/061/MYD11A2 MYD11A2.061 Aqua Land Surface Temperature and Emissivity 8-Day Global 1km image_collection ee.ImageCollection('MODIS/061/MYD11A2') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-15 -180, -90, 180, 90 False 8_day, aqua, emissivity, global, lst, modis, myd11a2, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD11A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD11A2 proprietary MODIS/061/MYD13A1 MYD13A1.061 Aqua Vegetation Indices 16-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MYD13A1') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-07 -180, -90, 180, 90 False 16_day, aqua, evi, global, modis, myd13a1, nasa, ndvi, usgs, vegetation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD13A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD13A1 proprietary MODIS/061/MYD13A2 MYD13A2.061 Aqua Vegetation Indices 16-Day Global 1km image_collection ee.ImageCollection('MODIS/061/MYD13A2') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-07 -180, -90, 180, 90 False 16_day, aqua, evi, global, modis, myd13a2, nasa, ndvi, usgs, vegetation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD13A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD13A2 proprietary @@ -478,8 +478,8 @@ MODIS/061/MYD14A2 MYD14A2.061: Aqua Thermal Anomalies & Fire 8-Day Global 1km im MODIS/061/MYD15A2H MYD15A2H.061: Aqua Leaf Area Index/FPAR 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MYD15A2H') NASA LP DAAC at the USGS EROS Center 2002-07-04 2024-10-15 -180, -90, 180, 90 False 8_day, aqua, fpar, global, lai, modis, myd15a2h, nasa, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD15A2H.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD15A2H proprietary MODIS/061/MYD17A2H MYD17A2H.061: Aqua Gross Primary Productivity 8-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MYD17A2H') NASA LP DAAC at the USGS EROS Center 2021-01-01 2024-10-15 -180, -90, 180, 90 False 8_day, aqua, global, gpp, modis, myd17a2, nasa, photosynthesis, productivity, psn, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD17A2H.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD17A2H proprietary MODIS/061/MYD17A3HGF MYD17A3HGF.061: Aqua Net Primary Production Gap-Filled Yearly Global 500m image_collection ee.ImageCollection('MODIS/061/MYD17A3HGF') NASA LP DAAC at the USGS EROS Center 2001-01-01 2023-01-01 -180, -90, 180, 90 False aqua, global, gpp, nasa, npp, photosynthesis, productivity, psn, usgs, yearly https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD17A3HGF.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD17A3HGF proprietary -MODIS/061/MYD21A1D MYD21A1D.061 Aqua Land Surface Temperature and 3-Band Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MYD21A1D') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-28 -180, -90, 180, 90 False aqua, daily, emissivity, global, lst, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD21A1D.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD21A1D proprietary -MODIS/061/MYD21A1N MYD21A1N.061 Aqua Land Surface Temperature and 3-Band Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MYD21A1N') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-28 -180, -90, 180, 90 False aqua, daily, emissivity, global, lst, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD21A1N.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD21A1N proprietary +MODIS/061/MYD21A1D MYD21A1D.061 Aqua Land Surface Temperature and 3-Band Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MYD21A1D') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False aqua, daily, emissivity, global, lst, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD21A1D.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD21A1D proprietary +MODIS/061/MYD21A1N MYD21A1N.061 Aqua Land Surface Temperature and 3-Band Emissivity Daily Global 1km image_collection ee.ImageCollection('MODIS/061/MYD21A1N') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False aqua, daily, emissivity, global, lst, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD21A1N.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD21A1N proprietary MODIS/061/MYD21C1 MYD21C1.061 Aqua Land Surface Temperature and 3-Band Emissivity Daily L3 Global 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MYD21C1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-29 -180, -90, 180, 90 False aqua, daily, emissivity, global, lst, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD21C1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD21C1 proprietary MODIS/061/MYD21C2 MYD21C2.061 Aqua Land Surface Temperature and 3-Band Emissivity 8-Day L3 Global 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MYD21C2') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-10-15 -180, -90, 180, 90 False aqua, emissivity, global, lst, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD21C2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD21C2 proprietary MODIS/061/MYD21C3 MYD21C3.061 Aqua Land Surface Temperature and 3-Band Emissivity Monthly L3 Global 0.05 Deg CMG image_collection ee.ImageCollection('MODIS/061/MYD21C3') NASA LP DAAC at the USGS EROS Center 2000-02-24 2024-09-01 -180, -90, 180, 90 False aqua, emissivity, global, lst, monthly, nasa, surface_temperature, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MYD21C3.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MYD21C3 proprietary @@ -537,16 +537,16 @@ MODIS/MYD13A1 MYD13A1.005 Vegetation Indices 16-Day L3 Global 500m [deprecated] MODIS/MYD13Q1 MYD13Q1.005 Vegetation Indices 16-Day Global 250m [deprecated] image_collection ee.ImageCollection('MODIS/MYD13Q1') NASA LP DAAC at the USGS EROS Center 2002-07-04 2017-03-14 -180, -90, 180, 90 True 16_day, aqua, evi, global, modis, myd13q1, ndvi, vegetation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_MYD13Q1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_MYD13Q1 proprietary MODIS/NTSG/MOD16A2/105 MOD16A2: MODIS Global Terrestrial Evapotranspiration 8-Day Global 1km image_collection ee.ImageCollection('MODIS/NTSG/MOD16A2/105') Numerical Terradynamic Simulation Group, The University of Montana 2000-01-01 2014-12-27 -180, -90, 180, 90 False 8_day, evapotranspiration, global, mod16a2, modis https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_NTSG_MOD16A2_105.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_NTSG_MOD16A2_105 proprietary NASA/ASTER_GED/AG100_003 AG100: ASTER Global Emissivity Dataset 100-meter V003 image ee.Image('NASA/ASTER_GED/AG100_003') NASA LP DAAC at the USGS EROS Center 2000-01-01 2008-12-31 -180, -59, 180, 80 False aster, caltech, elevation, emissivity, ged, geophysical, infrared, jpl, lst, nasa, ndvi, temperature, thermal https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_ASTER_GED_AG100_003.json https://developers.google.com/earth-engine/datasets/catalog/NASA_ASTER_GED_AG100_003 proprietary -NASA/EMIT/L1B/RAD EMIT L1B At-Sensor Calibrated Radiance and Geolocation Data 60 m image_collection ee.ImageCollection('NASA/EMIT/L1B/RAD') NASA Jet Propulsion Laboratory 2022-08-09 2024-10-28 -180, -90, 180, 90 False daily, emit, nasa, radiance https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L1B_RAD.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L1B_RAD proprietary -NASA/EMIT/L2A/RFL EMIT L2A Estimated Surface Reflectance and Uncertainty and Masks 60 m image_collection ee.ImageCollection('NASA/EMIT/L2A/RFL') NASA Jet Propulsion Laboratory 2022-08-09 2024-10-28 -180, -90, 180, 90 False daily, emit, nasa, reflectance https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L2A_RFL.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L2A_RFL proprietary +NASA/EMIT/L1B/RAD EMIT L1B At-Sensor Calibrated Radiance and Geolocation Data 60 m image_collection ee.ImageCollection('NASA/EMIT/L1B/RAD') NASA Jet Propulsion Laboratory 2022-08-09 2024-10-30 -180, -90, 180, 90 False daily, emit, nasa, radiance https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L1B_RAD.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L1B_RAD proprietary +NASA/EMIT/L2A/RFL EMIT L2A Estimated Surface Reflectance and Uncertainty and Masks 60 m image_collection ee.ImageCollection('NASA/EMIT/L2A/RFL') NASA Jet Propulsion Laboratory 2022-08-09 2024-10-29 -180, -90, 180, 90 False daily, emit, nasa, reflectance https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L2A_RFL.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L2A_RFL proprietary NASA/EMIT/L2B/CH4ENH Earth Surface Mineral Dust Source Investigation- Methane Enhancement image_collection ee.ImageCollection('NASA/EMIT/L2B/CH4ENH') NASA Jet Propulsion Laboratory 2022-08-10 2024-10-05 -180, -90, 180, 90 False daily, emit, nasa, methane https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L2B_CH4ENH.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L2B_CH4ENH proprietary NASA/EMIT/L2B/CH4PLM Earth Surface Mineral Dust Source Investigation- Methane Plume Complexes image_collection ee.ImageCollection('NASA/EMIT/L2B/CH4PLM') NASA Jet Propulsion Laboratory 2022-08-10 2024-09-30 -180, -90, 180, 90 False daily, emit, nasa, methane https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L2B_CH4PLM.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L2B_CH4PLM proprietary NASA/FLDAS/NOAH01/C/GL/M/V001 FLDAS: Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System image_collection ee.ImageCollection('NASA/FLDAS/NOAH01/C/GL/M/V001') NASA GES DISC at NASA Goddard Space Flight Center 1982-01-01 2024-09-01 -180, -60, 180, 90 False climate, evapotranspiration, famine, fldas, humidity, ldas, monthly, nasa, runoff, snow, soil_moisture, soil_temperature, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_FLDAS_NOAH01_C_GL_M_V001.json https://developers.google.com/earth-engine/datasets/catalog/NASA_FLDAS_NOAH01_C_GL_M_V001 proprietary NASA/GDDP-CMIP6 NEX-GDDP-CMIP6: NASA Earth Exchange Global Daily Downscaled Climate Projections image_collection ee.ImageCollection('NASA/GDDP-CMIP6') NASA / Climate Analytics Group 1950-01-01 2100-12-31 -180, -90, 180, 90 False cag, climate, gddp, geophysical, ipcc, nasa, nex, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GDDP-CMIP6.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GDDP-CMIP6 various -NASA/GEOS-CF/v1/fcst/htf GEOS-CF fcst htf v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/fcst/htf') NASA / GMAO 2022-10-01 2024-10-30 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_fcst_htf.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_htf proprietary -NASA/GEOS-CF/v1/fcst/tavg1hr GEOS-CF fcst tavg1hr v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/fcst/tavg1hr') NASA / GMAO 2022-10-01 2024-10-29 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_fcst_tavg1hr.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_tavg1hr proprietary -NASA/GEOS-CF/v1/rpl/htf GEOS-CF rpl htf v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/rpl/htf') NASA / GMAO 2018-01-01 2024-10-30 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_rpl_htf.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_htf proprietary -NASA/GEOS-CF/v1/rpl/tavg1hr GEOS-CF rpl tavg1hr v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/rpl/tavg1hr') NASA / GMAO 2018-01-01 2024-10-29 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_rpl_tavg1hr.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_tavg1hr proprietary +NASA/GEOS-CF/v1/fcst/htf GEOS-CF fcst htf v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/fcst/htf') NASA / GMAO 2022-10-01 2024-10-31 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_fcst_htf.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_htf proprietary +NASA/GEOS-CF/v1/fcst/tavg1hr GEOS-CF fcst tavg1hr v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/fcst/tavg1hr') NASA / GMAO 2022-10-01 2024-10-31 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_fcst_tavg1hr.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_tavg1hr proprietary +NASA/GEOS-CF/v1/rpl/htf GEOS-CF rpl htf v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/rpl/htf') NASA / GMAO 2018-01-01 2024-10-31 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_rpl_htf.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_htf proprietary +NASA/GEOS-CF/v1/rpl/tavg1hr GEOS-CF rpl tavg1hr v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/rpl/tavg1hr') NASA / GMAO 2018-01-01 2024-10-30 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_rpl_tavg1hr.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_tavg1hr proprietary NASA/GIMMS/3GV0 GIMMS NDVI From AVHRR Sensors (3rd Generation) image_collection ee.ImageCollection('NASA/GIMMS/3GV0') NASA/NOAA 1981-07-01 2013-12-16 -180, -90, 180, 90 False avhrr, gimms, nasa, ndvi, noaa, vegetation https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GIMMS_3GV0.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GIMMS_3GV0 proprietary NASA/GLDAS/V021/NOAH/G025/T3H GLDAS-2.1: Global Land Data Assimilation System image_collection ee.ImageCollection('NASA/GLDAS/V021/NOAH/G025/T3H') NASA GES DISC at NASA Goddard Space Flight Center 2000-01-01 2024-10-20 -180, -90, 180, 90 False 3_hourly, climate, evaporation, forcing, geophysical, gldas, humidity, ldas, nasa, precipitation, pressure, radiation, soil, soil_moisture, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GLDAS_V021_NOAH_G025_T3H.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GLDAS_V021_NOAH_G025_T3H proprietary NASA/GLDAS/V022/CLSM/G025/DA1D GLDAS-2.2: Global Land Data Assimilation System image_collection ee.ImageCollection('NASA/GLDAS/V022/CLSM/G025/DA1D') NASA GES DISC at NASA Goddard Earth Sciences Data and Information Services Center 2003-01-01 2024-05-31 -180, -90, 180, 90 False 3_hourly, climate, evaporation, forcing, geophysical, gldas, humidity, ldas, nasa, precipitation, pressure, radiation, soil, soil_moisture, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GLDAS_V022_CLSM_G025_DA1D.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GLDAS_V022_CLSM_G025_DA1D proprietary @@ -570,16 +570,16 @@ NASA/GSFC/MERRA/flx/2 MERRA-2 M2T1NXFLX: Surface Flux Diagnostics V5.12.4 image_ NASA/GSFC/MERRA/lnd/2 MERRA-2 M2T1NXLND: Land Surface Diagnostics V5.12.4 image_collection ee.ImageCollection('NASA/GSFC/MERRA/lnd/2') NASA/MERRA 1980-01-01 2024-10-01 -180, -90, 180, 90 False evaporation, ice, merra, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GSFC_MERRA_lnd_2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GSFC_MERRA_lnd_2 proprietary NASA/GSFC/MERRA/rad/2 MERRA-2 M2T1NXRAD: Radiation Diagnostics V5.12.4 image_collection ee.ImageCollection('NASA/GSFC/MERRA/rad/2') NASA/MERRA 1980-01-01 2024-10-01 -180, -90, 180, 90 False albedo, emissivity, merra, shortwave, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GSFC_MERRA_rad_2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GSFC_MERRA_rad_2 proprietary NASA/GSFC/MERRA/slv/2 MERRA-2 M2T1NXSLV: Single-Level Diagnostics V5.12.4 image_collection ee.ImageCollection('NASA/GSFC/MERRA/slv/2') NASA/MERRA 1980-01-01 2024-10-01 -180, -90, 180, 90 False condensation, humidity, merra, nasa, omega, pressure, slv, temperature, vapor, water, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GSFC_MERRA_slv_2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GSFC_MERRA_slv_2 proprietary -NASA/HLS/HLSL30/v002 HLSL30: HLS-2 Landsat Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m image_collection ee.ImageCollection('NASA/HLS/HLSL30/v002') NASA LP DAAC 2013-04-11 2024-10-28 -180, -90, 180, 90 False landsat, nasa, sentinel, usgs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_HLS_HLSL30_v002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_HLS_HLSL30_v002 proprietary +NASA/HLS/HLSL30/v002 HLSL30: HLS-2 Landsat Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m image_collection ee.ImageCollection('NASA/HLS/HLSL30/v002') NASA LP DAAC 2013-04-11 2024-10-30 -180, -90, 180, 90 False landsat, nasa, sentinel, usgs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_HLS_HLSL30_v002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_HLS_HLSL30_v002 proprietary NASA/JPL/global_forest_canopy_height_2005 Global Forest Canopy Height, 2005 image ee.Image('NASA/JPL/global_forest_canopy_height_2005') NASA/JPL 2005-05-20 2005-06-23 -180, -90, 180, 90 False canopy, forest, geophysical, glas, jpl, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_JPL_global_forest_canopy_height_2005.json https://developers.google.com/earth-engine/datasets/catalog/NASA_JPL_global_forest_canopy_height_2005 proprietary -NASA/LANCE/NOAA20_VIIRS/C2 VJ114IMGTDL_NRT Daily Raster: VIIRS (NOAA-20) Band 375m Active Fire image_collection ee.ImageCollection('NASA/LANCE/NOAA20_VIIRS/C2') NASA / LANCE / NOAA20_VIIRS 2023-10-08 2024-10-29 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_LANCE_NOAA20_VIIRS_C2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_LANCE_NOAA20_VIIRS_C2 proprietary -NASA/LANCE/SNPP_VIIRS/C2 VNP14IMGTDL_NRT Daily Raster: VIIRS (S-NPP) Band 375m Active Fire image_collection ee.ImageCollection('NASA/LANCE/SNPP_VIIRS/C2') NASA / LANCE / SNPP_VIIRS 2023-09-03 2024-10-29 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_LANCE_SNPP_VIIRS_C2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_LANCE_SNPP_VIIRS_C2 proprietary +NASA/LANCE/NOAA20_VIIRS/C2 VJ114IMGTDL_NRT Daily Raster: VIIRS (NOAA-20) Band 375m Active Fire image_collection ee.ImageCollection('NASA/LANCE/NOAA20_VIIRS/C2') NASA / LANCE / NOAA20_VIIRS 2023-10-08 2024-10-30 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_LANCE_NOAA20_VIIRS_C2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_LANCE_NOAA20_VIIRS_C2 proprietary +NASA/LANCE/SNPP_VIIRS/C2 VNP14IMGTDL_NRT Daily Raster: VIIRS (S-NPP) Band 375m Active Fire image_collection ee.ImageCollection('NASA/LANCE/SNPP_VIIRS/C2') NASA / LANCE / SNPP_VIIRS 2023-09-03 2024-10-30 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_LANCE_SNPP_VIIRS_C2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_LANCE_SNPP_VIIRS_C2 proprietary NASA/MEASURES/GFCC/TC/v3 Global Forest Cover Change (GFCC) Tree Cover Multi-Year Global 30m image_collection ee.ImageCollection('NASA/MEASURES/GFCC/TC/v3') NASA LP DAAC at the USGS EROS Center 2000-01-01 2015-01-01 -180, -90, 180, 90 False forest, glcf, landsat_derived, nasa, umd https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_MEASURES_GFCC_TC_v3.json https://developers.google.com/earth-engine/datasets/catalog/NASA_MEASURES_GFCC_TC_v3 proprietary NASA/NASADEM_HGT/001 NASADEM: NASA NASADEM Digital Elevation 30m image ee.Image('NASA/NASADEM_HGT/001') NASA / USGS / JPL-Caltech 2000-02-11 2000-02-22 -180, -56, 180, 60 False dem, elevation, geophysical, nasa, nasadem, srtm, topography, usgs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NASADEM_HGT_001.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NASADEM_HGT_001 proprietary NASA/NEX-DCP30 NEX-DCP30: NASA Earth Exchange Downscaled Climate Projections image_collection ee.ImageCollection('NASA/NEX-DCP30') NASA / Climate Analytics Group 1950-01-01 2099-12-01 -125.03, 24.07, -66.47, 53.74 False cag, climate, cmip5, geophysical, ipcc, nasa, nex, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NEX-DCP30.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-DCP30 proprietary NASA/NEX-DCP30_ENSEMBLE_STATS NEX-DCP30: Ensemble Stats for NASA Earth Exchange Downscaled Climate Projections image_collection ee.ImageCollection('NASA/NEX-DCP30_ENSEMBLE_STATS') NASA / Climate Analytics Group 1950-01-01 2099-12-01 -125.03, 24.07, -66.47, 49.93 False cag, climate, cmip5, geophysical, ipcc, nasa, nex, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NEX-DCP30_ENSEMBLE_STATS.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-DCP30_ENSEMBLE_STATS proprietary NASA/NEX-GDDP NEX-GDDP: NASA Earth Exchange Global Daily Downscaled Climate Projections image_collection ee.ImageCollection('NASA/NEX-GDDP') NASA / Climate Analytics Group 1950-01-01 2100-12-31 -180, -90, 180, 90 False cag, climate, cmip5, gddp, geophysical, ipcc, nasa, nex, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NEX-GDDP.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-GDDP proprietary -NASA/NLDAS/FORA0125_H002 NLDAS-2: North American Land Data Assimilation System Forcing Fields image_collection ee.ImageCollection('NASA/NLDAS/FORA0125_H002') NASA GES DISC at NASA Goddard Space Flight Center 1979-01-01 2024-10-26 -125.15, 24.85, -66.85, 53.28 False climate, evaporation, forcing, geophysical, hourly, humidity, ldas, nasa, nldas, precipitation, pressure, radiation, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NLDAS_FORA0125_H002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NLDAS_FORA0125_H002 proprietary +NASA/NLDAS/FORA0125_H002 NLDAS-2: North American Land Data Assimilation System Forcing Fields image_collection ee.ImageCollection('NASA/NLDAS/FORA0125_H002') NASA GES DISC at NASA Goddard Space Flight Center 1979-01-01 2024-10-29 -125.15, 24.85, -66.85, 53.28 False climate, evaporation, forcing, geophysical, hourly, humidity, ldas, nasa, nldas, precipitation, pressure, radiation, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NLDAS_FORA0125_H002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NLDAS_FORA0125_H002 proprietary NASA/OCEANDATA/MODIS-Aqua/L3SMI Ocean Color SMI: Standard Mapped Image MODIS Aqua Data image_collection ee.ImageCollection('NASA/OCEANDATA/MODIS-Aqua/L3SMI') NASA OB.DAAC at NASA Goddard Space Flight Center 2002-07-03 2022-02-28 -180, -90, 180, 90 False biology, chlorophyll, climate, modis, nasa, ocean, oceandata, reflectance, sst, temperature, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_OCEANDATA_MODIS-Aqua_L3SMI.json https://developers.google.com/earth-engine/datasets/catalog/NASA_OCEANDATA_MODIS-Aqua_L3SMI proprietary NASA/OCEANDATA/MODIS-Terra/L3SMI Ocean Color SMI: Standard Mapped Image MODIS Terra Data image_collection ee.ImageCollection('NASA/OCEANDATA/MODIS-Terra/L3SMI') NASA OB.DAAC at NASA Goddard Space Flight Center 2000-02-24 2022-02-28 -180, -90, 180, 90 False biology, chlorophyll, climate, modis, nasa, ocean, oceandata, reflectance, sst, temperature, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_OCEANDATA_MODIS-Terra_L3SMI.json https://developers.google.com/earth-engine/datasets/catalog/NASA_OCEANDATA_MODIS-Terra_L3SMI proprietary NASA/OCEANDATA/SeaWiFS/L3SMI Ocean Color SMI: Standard Mapped Image SeaWiFS Data image_collection ee.ImageCollection('NASA/OCEANDATA/SeaWiFS/L3SMI') NASA OB.DAAC at NASA Goddard Space Flight Center 1997-09-04 2010-12-10 -180, -90, 180, 90 False biology, chlorophyll, climate, nasa, ocean, oceandata, reflectance, seawifs, temperature, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_OCEANDATA_SeaWiFS_L3SMI.json https://developers.google.com/earth-engine/datasets/catalog/NASA_OCEANDATA_SeaWiFS_L3SMI proprietary @@ -589,19 +589,19 @@ NASA/ORNL/biomass_carbon_density/v1 Global Aboveground and Belowground Biomass C NASA/ORNL/global_forest_classification_2020/V1 Global 2020 Forest Classification for IPCC Aboveground Biomass Tier 1 Estimates, V1 image_collection ee.ImageCollection('NASA/ORNL/global_forest_classification_2020/V1') NASA ORNL DAAC at Oak Ridge National Laboratory 2020-01-01 2020-12-31 -180, -90, 180, 90 False aboveground, biomass, carbon, classification, forest, ipcc, nasa, primary_forest, secondary_forest https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_ORNL_global_forest_classification_2020_V1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_ORNL_global_forest_classification_2020_V1 proprietary NASA/SMAP/SPL3SMP_E/005 SPL3SMP_E.005 SMAP L3 Radiometer Global Daily 9 km Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL3SMP_E/005') Google and NSIDC 2015-03-31 2023-12-03 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL3SMP_E_005.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL3SMP_E_005 proprietary NASA/SMAP/SPL3SMP_E/006 SPL3SMP_E.006 SMAP L3 Radiometer Global Daily 9 km Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL3SMP_E/006') Google and NSIDC 2023-12-04 2024-10-30 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL3SMP_E_006.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL3SMP_E_006 proprietary -NASA/SMAP/SPL4SMGP/007 SPL4SMGP.007 SMAP L4 Global 3-hourly 9-km Surface and Root Zone Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL4SMGP/007') Google and NSIDC 2015-03-31 2024-10-29 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL4SMGP_007.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL4SMGP_007 proprietary -NASA/VIIRS/002/VNP09GA VNP09GA: VIIRS Surface Reflectance Daily 500m and 1km image_collection ee.ImageCollection('NASA/VIIRS/002/VNP09GA') NASA Land SIPS 2012-01-19 2024-10-20 -180, -90, 180, 90 False daily, nasa, noaa, npp, reflectance, sr, viirs, vnp09ga https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP09GA.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP09GA proprietary -NASA/VIIRS/002/VNP09H1 VNP09H1: VIIRS Surface Reflectance 8-Day L3 Global 500m image_collection ee.ImageCollection('NASA/VIIRS/002/VNP09H1') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-07 -180, -90, 180, 90 False daily, nasa, noaa, npp, reflectance, sr, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP09H1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP09H1 proprietary -NASA/VIIRS/002/VNP13A1 VNP13A1.002: VIIRS Vegetation Indices 16-Day 500m image_collection ee.ImageCollection('NASA/VIIRS/002/VNP13A1') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-09-29 -180, -90, 180, 90 False 16_day, evi, nasa, ndvi, noaa, npp, vegetation, viirs, vnp13a1 https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP13A1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP13A1 proprietary -NASA/VIIRS/002/VNP14A1 VNP14A1.002: Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid image_collection ee.ImageCollection('NASA/VIIRS/002/VNP14A1') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-20 -180, -90, 180, 90 False fire, land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP14A1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP14A1 proprietary -NASA/VIIRS/002/VNP15A2H VNP15A2H: LAI/FPAR 8-Day L4 Global 500m SIN Grid image_collection ee.ImageCollection('NASA/VIIRS/002/VNP15A2H') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-10-07 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP15A2H.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP15A2H proprietary -NASA/VIIRS/002/VNP21A1D VNP21A1D.002: Day Land Surface Temperature and Emissivity Daily 1km image_collection ee.ImageCollection('NASA/VIIRS/002/VNP21A1D') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-20 -180, -90, 180, 90 False daily, day, land, nasa, noaa, surface, temperature, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP21A1D.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP21A1D proprietary -NASA/VIIRS/002/VNP21A1N VNP21A1N.002: Night Land Surface Temperature and Emissivity Daily 1km image_collection ee.ImageCollection('NASA/VIIRS/002/VNP21A1N') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-22 -180, -90, 180, 90 False daily, land, nasa, night, noaa, surface, temperature, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP21A1N.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP21A1N proprietary +NASA/SMAP/SPL4SMGP/007 SPL4SMGP.007 SMAP L4 Global 3-hourly 9-km Surface and Root Zone Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL4SMGP/007') Google and NSIDC 2015-03-31 2024-10-30 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL4SMGP_007.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL4SMGP_007 proprietary +NASA/VIIRS/002/VNP09GA VNP09GA: VIIRS Surface Reflectance Daily 500m and 1km image_collection ee.ImageCollection('NASA/VIIRS/002/VNP09GA') NASA Land SIPS 2012-01-19 2024-10-30 -180, -90, 180, 90 False daily, nasa, noaa, npp, reflectance, sr, viirs, vnp09ga https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP09GA.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP09GA proprietary +NASA/VIIRS/002/VNP09H1 VNP09H1: VIIRS Surface Reflectance 8-Day L3 Global 500m image_collection ee.ImageCollection('NASA/VIIRS/002/VNP09H1') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-23 -180, -90, 180, 90 False daily, nasa, noaa, npp, reflectance, sr, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP09H1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP09H1 proprietary +NASA/VIIRS/002/VNP13A1 VNP13A1.002: VIIRS Vegetation Indices 16-Day 500m image_collection ee.ImageCollection('NASA/VIIRS/002/VNP13A1') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-10-15 -180, -90, 180, 90 False 16_day, evi, nasa, ndvi, noaa, npp, vegetation, viirs, vnp13a1 https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP13A1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP13A1 proprietary +NASA/VIIRS/002/VNP14A1 VNP14A1.002: Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid image_collection ee.ImageCollection('NASA/VIIRS/002/VNP14A1') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-30 -180, -90, 180, 90 False fire, land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP14A1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP14A1 proprietary +NASA/VIIRS/002/VNP15A2H VNP15A2H: LAI/FPAR 8-Day L4 Global 500m SIN Grid image_collection ee.ImageCollection('NASA/VIIRS/002/VNP15A2H') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-10-23 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP15A2H.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP15A2H proprietary +NASA/VIIRS/002/VNP21A1D VNP21A1D.002: Day Land Surface Temperature and Emissivity Daily 1km image_collection ee.ImageCollection('NASA/VIIRS/002/VNP21A1D') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-30 -180, -90, 180, 90 False daily, day, land, nasa, noaa, surface, temperature, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP21A1D.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP21A1D proprietary +NASA/VIIRS/002/VNP21A1N VNP21A1N.002: Night Land Surface Temperature and Emissivity Daily 1km image_collection ee.ImageCollection('NASA/VIIRS/002/VNP21A1N') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-30 -180, -90, 180, 90 False daily, land, nasa, night, noaa, surface, temperature, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP21A1N.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP21A1N proprietary NASA_USDA/HSL/SMAP10KM_soil_moisture NASA-USDA Enhanced SMAP Global Soil Moisture Data [deprecated] image_collection ee.ImageCollection('NASA_USDA/HSL/SMAP10KM_soil_moisture') NASA GSFC 2015-04-02 2022-08-02 -180, -60, 180, 90 True geophysical, hsl, nasa, smap, soil, soil_moisture, usda https://storage.googleapis.com/earthengine-stac/catalog/NASA_USDA/NASA_USDA_HSL_SMAP10KM_soil_moisture.json https://developers.google.com/earth-engine/datasets/catalog/NASA_USDA_HSL_SMAP10KM_soil_moisture proprietary NASA_USDA/HSL/SMAP_soil_moisture NASA-USDA SMAP Global Soil Moisture Data [deprecated] image_collection ee.ImageCollection('NASA_USDA/HSL/SMAP_soil_moisture') NASA GSFC 2015-04-02 2020-12-31 -180, -60, 180, 90 True geophysical, hsl, nasa, smap, soil, soil_moisture, usda https://storage.googleapis.com/earthengine-stac/catalog/NASA_USDA/NASA_USDA_HSL_SMAP_soil_moisture.json https://developers.google.com/earth-engine/datasets/catalog/NASA_USDA_HSL_SMAP_soil_moisture proprietary NASA_USDA/HSL/soil_moisture NASA-USDA Global Soil Moisture Data [deprecated] image_collection ee.ImageCollection('NASA_USDA/HSL/soil_moisture') NASA GSFC 2010-01-13 2020-12-31 -180, -60, 180, 90 True geophysical, hsl, nasa, smos, soil, soil_moisture, usda https://storage.googleapis.com/earthengine-stac/catalog/NASA_USDA/NASA_USDA_HSL_soil_moisture.json https://developers.google.com/earth-engine/datasets/catalog/NASA_USDA_HSL_soil_moisture proprietary NCEP_RE/sea_level_pressure NCEP/NCAR Reanalysis Data, Sea-Level Pressure image_collection ee.ImageCollection('NCEP_RE/sea_level_pressure') NCEP 1948-01-01 2024-10-28 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, pressure, reanalysis https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_sea_level_pressure.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_sea_level_pressure proprietary -NCEP_RE/surface_temp NCEP/NCAR Reanalysis Data, Surface Temperature image_collection ee.ImageCollection('NCEP_RE/surface_temp') NCEP 1948-01-01 2024-10-27 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, reanalysis, temperature https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_surface_temp.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_surface_temp proprietary +NCEP_RE/surface_temp NCEP/NCAR Reanalysis Data, Surface Temperature image_collection ee.ImageCollection('NCEP_RE/surface_temp') NCEP 1948-01-01 2024-10-28 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, reanalysis, temperature https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_surface_temp.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_surface_temp proprietary NCEP_RE/surface_wv NCEP/NCAR Reanalysis Data, Water Vapor image_collection ee.ImageCollection('NCEP_RE/surface_wv') NCEP 1948-01-01 2024-10-28 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, precipitable, reanalysis, vapor https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_surface_wv.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_surface_wv proprietary NOAA/CDR/ATMOS_NEAR_SURFACE/V2 NOAA CDR: Ocean Near-Surface Atmospheric Properties, Version 2 image_collection ee.ImageCollection('NOAA/CDR/ATMOS_NEAR_SURFACE/V2') NOAA 1988-01-01 2021-08-31 -180, -90, 180, 90 False air_temperature, atmospheric, cdr, hourly, humidity, noaa, ocean, osb, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_ATMOS_NEAR_SURFACE_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_ATMOS_NEAR_SURFACE_V2 proprietary NOAA/CDR/AVHRR/AOT/V3 NOAA CDR AVHRR AOT: Daily Aerosol Optical Thickness Over Global Oceans, v03 [deprecated] image_collection ee.ImageCollection('NOAA/CDR/AVHRR/AOT/V3') NOAA 1981-01-01 2022-03-31 -180, -90, 180, 90 True aerosol, aot, atmospheric, avhrr, cdr, daily, noaa, optical, pollution https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_AVHRR_AOT_V3.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_AVHRR_AOT_V3 proprietary @@ -615,36 +615,36 @@ NOAA/CDR/AVHRR/SR/V5 NOAA CDR AVHRR: Surface Reflectance, Version 5 image_collec NOAA/CDR/GRIDSAT-B1/V2 NOAA CDR GRIDSAT-B1: Geostationary IR Channel Brightness Temperature image_collection ee.ImageCollection('NOAA/CDR/GRIDSAT-B1/V2') NOAA 1980-01-01 2024-03-31 -180, -90, 180, 90 False brightness, cdr, fundamental, geostationary, infrared, isccp, noaa, reflectance, sr https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_GRIDSAT-B1_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_GRIDSAT-B1_V2 proprietary NOAA/CDR/HEAT_FLUXES/V2 NOAA CDR: Ocean Heat Fluxes, Version 2 image_collection ee.ImageCollection('NOAA/CDR/HEAT_FLUXES/V2') NOAA 1988-01-01 2021-08-31 -180, -90, 180, 90 False atmospheric, cdr, flux, heat, hourly, noaa, ocean, osb https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_HEAT_FLUXES_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_HEAT_FLUXES_V2 proprietary NOAA/CDR/OISST/V2 NOAA CDR OISST v2: Optimum Interpolation Sea Surface Temperature [deprecated] image_collection ee.ImageCollection('NOAA/CDR/OISST/V2') NOAA 1981-09-01 2020-04-26 -180, -90, 180, 90 True avhrr, cdr, daily, ice, noaa, ocean, oisst, real_time, sst, temperature https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_OISST_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_OISST_V2 proprietary -NOAA/CDR/OISST/V2_1 NOAA CDR OISST v02r01: Optimum Interpolation Sea Surface Temperature image_collection ee.ImageCollection('NOAA/CDR/OISST/V2_1') NOAA 1981-09-01 2024-10-28 -180, -90, 180, 90 False avhrr, cdr, daily, ice, noaa, ocean, oisst, real_time, sst, temperature https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_OISST_V2_1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_OISST_V2_1 proprietary +NOAA/CDR/OISST/V2_1 NOAA CDR OISST v02r01: Optimum Interpolation Sea Surface Temperature image_collection ee.ImageCollection('NOAA/CDR/OISST/V2_1') NOAA 1981-09-01 2024-10-29 -180, -90, 180, 90 False avhrr, cdr, daily, ice, noaa, ocean, oisst, real_time, sst, temperature https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_OISST_V2_1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_OISST_V2_1 proprietary NOAA/CDR/PATMOSX/V53 NOAA CDR PATMOSX: Cloud Properties, Reflectance, and Brightness Temperatures, Version 5.3 image_collection ee.ImageCollection('NOAA/CDR/PATMOSX/V53') NOAA 1979-01-01 2022-01-01 -180, -90, 180, 90 False atmospheric, avhrr, brightness, cdr, cloud, metop, noaa, optical, poes, reflectance, temperature https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_PATMOSX_V53.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_PATMOSX_V53 proprietary NOAA/CDR/SST_PATHFINDER/V53 NOAA AVHRR Pathfinder Version 5.3 Collated Global 4km Sea Surface Temperature image_collection ee.ImageCollection('NOAA/CDR/SST_PATHFINDER/V53') NOAA 1981-08-24 2023-12-30 -180, -90, 180, 90 False avhrr, noaa, pathfinder, sea_ice, sst, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_SST_PATHFINDER_V53.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_SST_PATHFINDER_V53 proprietary NOAA/CDR/SST_WHOI/V2 NOAA CDR WHOI: Sea Surface Temperature, Version 2 image_collection ee.ImageCollection('NOAA/CDR/SST_WHOI/V2') NOAA 1988-01-01 2021-08-31 -180, -90, 180, 90 False atmospheric, cdr, hourly, noaa, ocean, oisst, osb, sst, whoi https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_SST_WHOI_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_SST_WHOI_V2 proprietary -NOAA/CFSR CFSR: Climate Forecast System Reanalysis image_collection ee.ImageCollection('NOAA/CFSR') NOAA NWS National Centers for Environmental Prediction (NCEP) 2018-12-13 2024-10-30 -180, -90, 180, 90 False climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CFSR.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CFSR proprietary -NOAA/CFSV2/FOR6H CFSV2: NCEP Climate Forecast System Version 2, 6-Hourly Products image_collection ee.ImageCollection('NOAA/CFSV2/FOR6H') NOAA NWS National Centers for Environmental Prediction (NCEP) 1979-01-01 2024-10-30 -180, -90, 180, 90 False climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CFSV2_FOR6H.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CFSV2_FOR6H proprietary +NOAA/CFSR CFSR: Climate Forecast System Reanalysis image_collection ee.ImageCollection('NOAA/CFSR') NOAA NWS National Centers for Environmental Prediction (NCEP) 2018-12-13 2024-11-01 -180, -90, 180, 90 False climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CFSR.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CFSR proprietary +NOAA/CFSV2/FOR6H CFSV2: NCEP Climate Forecast System Version 2, 6-Hourly Products image_collection ee.ImageCollection('NOAA/CFSV2/FOR6H') NOAA NWS National Centers for Environmental Prediction (NCEP) 1979-01-01 2024-10-31 -180, -90, 180, 90 False climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CFSV2_FOR6H.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CFSV2_FOR6H proprietary NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4 DMSP OLS: Global Radiance-Calibrated Nighttime Lights Version 4, Defense Meteorological Program Operational Linescan System image_collection ee.ImageCollection('NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 1996-03-16 2011-07-31 -180, -65, 180, 75 False calibrated, dmsp, eog, imagery, lights, nighttime, ols, radiance, visible, yearly https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_DMSP-OLS_CALIBRATED_LIGHTS_V4.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_CALIBRATED_LIGHTS_V4 proprietary NOAA/DMSP-OLS/NIGHTTIME_LIGHTS DMSP OLS: Nighttime Lights Time Series Version 4, Defense Meteorological Program Operational Linescan System image_collection ee.ImageCollection('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 1992-01-01 2014-01-01 -180, -65, 180, 75 False dmsp, eog, imagery, lights, nighttime, ols, visible, yearly https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS proprietary -NOAA/GFS0P25 GFS: Global Forecast System 384-Hour Predicted Atmosphere Data image_collection ee.ImageCollection('NOAA/GFS0P25') NOAA/NCEP/EMC 2015-07-01 2024-10-31 -180, -90, 180, 90 False climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GFS0P25.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25 proprietary -NOAA/GOES/16/FDCC GOES-16 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/16/FDCC') NOAA 2017-05-24 2024-10-31 -152.11, 14, -49.18, 56.77 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCC proprietary -NOAA/GOES/16/FDCF GOES-16 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/FDCF') NOAA 2017-05-24 2024-10-31 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCF proprietary -NOAA/GOES/16/MCMIPC GOES-16 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPC') NOAA 2017-07-10 2024-10-31 -152.11, 14, -49.18, 56.77 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPC proprietary -NOAA/GOES/16/MCMIPF GOES-16 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPF') NOAA 2017-07-10 2024-10-31 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPF proprietary -NOAA/GOES/16/MCMIPM GOES-16 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Mesoscale image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPM') NOAA 2017-07-10 2024-10-31 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPM proprietary +NOAA/GFS0P25 GFS: Global Forecast System 384-Hour Predicted Atmosphere Data image_collection ee.ImageCollection('NOAA/GFS0P25') NOAA/NCEP/EMC 2015-07-01 2024-11-01 -180, -90, 180, 90 False climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GFS0P25.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25 proprietary +NOAA/GOES/16/FDCC GOES-16 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/16/FDCC') NOAA 2017-05-24 2024-11-01 -152.11, 14, -49.18, 56.77 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCC proprietary +NOAA/GOES/16/FDCF GOES-16 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/FDCF') NOAA 2017-05-24 2024-11-01 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCF proprietary +NOAA/GOES/16/MCMIPC GOES-16 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPC') NOAA 2017-07-10 2024-11-01 -152.11, 14, -49.18, 56.77 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPC proprietary +NOAA/GOES/16/MCMIPF GOES-16 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPF') NOAA 2017-07-10 2024-11-01 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPF proprietary +NOAA/GOES/16/MCMIPM GOES-16 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Mesoscale image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPM') NOAA 2017-07-10 2024-11-01 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPM proprietary NOAA/GOES/17/FDCC GOES-17 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/17/FDCC') NOAA 2018-08-27 2023-01-10 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_17, goes_s, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_FDCC proprietary NOAA/GOES/17/FDCF GOES-17 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/FDCF') NOAA 2018-08-27 2023-01-10 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_17, goes_s, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_FDCF proprietary NOAA/GOES/17/MCMIPC GOES-17 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPC') NOAA 2018-12-04 2023-01-10 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPC proprietary NOAA/GOES/17/MCMIPF GOES-17 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPF') NOAA 2018-12-04 2023-01-10 -180, -90, 180, 90 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPF proprietary NOAA/GOES/17/MCMIPM GOES-17 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPM') NOAA 2018-12-04 2023-01-10 -180, -90, 180, 90 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPM proprietary -NOAA/GOES/18/FDCC GOES-18 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/18/FDCC') NOAA 2022-10-13 2024-10-31 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCC proprietary -NOAA/GOES/18/FDCF GOES-18 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/FDCF') NOAA 2022-10-13 2024-10-31 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCF proprietary -NOAA/GOES/18/MCMIPC GOES-18 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPC') NOAA 2018-12-04 2024-10-31 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPC proprietary -NOAA/GOES/18/MCMIPF GOES-18 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPF') NOAA 2018-12-04 2024-10-31 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPF proprietary -NOAA/GOES/18/MCMIPM GOES-18 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPM') NOAA 2018-12-04 2024-10-31 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPM proprietary +NOAA/GOES/18/FDCC GOES-18 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/18/FDCC') NOAA 2022-10-13 2024-11-01 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCC proprietary +NOAA/GOES/18/FDCF GOES-18 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/FDCF') NOAA 2022-10-13 2024-11-01 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCF proprietary +NOAA/GOES/18/MCMIPC GOES-18 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPC') NOAA 2018-12-04 2024-11-01 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPC proprietary +NOAA/GOES/18/MCMIPF GOES-18 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPF') NOAA 2018-12-04 2024-11-01 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPF proprietary +NOAA/GOES/18/MCMIPM GOES-18 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPM') NOAA 2018-12-04 2024-11-01 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPM proprietary NOAA/IBTrACS/v4 International Best Track Archive for Climate Stewardship Project table ee.FeatureCollection('NOAA/IBTrACS/v4') NOAA NCEI 1842-10-25 2024-05-19 -180, 0.4, 180, 63.1 False hurricane, noaa, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_IBTrACS_v4.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_IBTrACS_v4 proprietary NOAA/NCEP_DOE_RE2/total_cloud_coverage NCEP-DOE Reanalysis 2 (Gaussian Grid), Total Cloud Coverage image_collection ee.ImageCollection('NOAA/NCEP_DOE_RE2/total_cloud_coverage') NOAA 1979-01-01 2024-09-30 -180, -90, 180, 90 False atmosphere, climate, cloud, geophysical, ncep, noaa, reanalysis https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NCEP_DOE_RE2_total_cloud_coverage.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NCEP_DOE_RE2_total_cloud_coverage proprietary NOAA/NGDC/ETOPO1 ETOPO1: Global 1 Arc-Minute Elevation image ee.Image('NOAA/NGDC/ETOPO1') NOAA 2008-08-01 2008-08-01 -180, -90, 180, 90 False bedrock, dem, elevation, geophysical, ice, noaa, topography https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NGDC_ETOPO1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NGDC_ETOPO1 proprietary NOAA/NHC/HURDAT2/atlantic NOAA NHC HURDAT2 Atlantic Hurricane Catalog table ee.FeatureCollection('NOAA/NHC/HURDAT2/atlantic') NOAA NHC 1851-06-25 2018-11-04 -109.5, 7.2, 63, 81 False hurricane, nhc, noaa, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NHC_HURDAT2_atlantic.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NHC_HURDAT2_atlantic proprietary NOAA/NHC/HURDAT2/pacific NOAA NHC HURDAT2 Pacific Hurricane Catalog table ee.FeatureCollection('NOAA/NHC/HURDAT2/pacific') NOAA NHC 1949-06-11 2018-11-09 -180, 0.4, 180, 63.1 False hurricane, nhc, noaa, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NHC_HURDAT2_pacific.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NHC_HURDAT2_pacific proprietary -NOAA/NWS/RTMA RTMA: Real-Time Mesoscale Analysis image_collection ee.ImageCollection('NOAA/NWS/RTMA') NOAA/NWS 2011-01-01 2024-10-30 -130.17, 20.15, -60.81, 52.91 False climate, cloud, geophysical, humidity, noaa, nws, precipitation, pressure, rtma, surface, temperature, visibility, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NWS_RTMA.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NWS_RTMA proprietary +NOAA/NWS/RTMA RTMA: Real-Time Mesoscale Analysis image_collection ee.ImageCollection('NOAA/NWS/RTMA') NOAA/NWS 2011-01-01 2024-11-01 -130.17, 20.15, -60.81, 52.91 False climate, cloud, geophysical, humidity, noaa, nws, precipitation, pressure, rtma, surface, temperature, visibility, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NWS_RTMA.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NWS_RTMA proprietary NOAA/PERSIANN-CDR PERSIANN-CDR: Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record image_collection ee.ImageCollection('NOAA/PERSIANN-CDR') NOAA NCDC 1983-01-01 2024-03-31 -180, -60, 180, 60 False cdr, climate, geophysical, ncdc, noaa, persiann, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_PERSIANN-CDR.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_PERSIANN-CDR proprietary NOAA/VIIRS/001/VNP09GA VNP09GA: VIIRS Surface Reflectance Daily 500m and 1km [deprecated] image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP09GA') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-06-16 -180, -90, 180, 90 True daily, nasa, noaa, npp, reflectance, sr, viirs, vnp09ga https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP09GA.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP09GA proprietary NOAA/VIIRS/001/VNP09H1 VNP09H1: VIIRS Surface Reflectance 8-Day L3 Global 500m [deprecated] image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP09H1') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-06-09 -180, -90, 180, 90 True daily, nasa, noaa, npp, reflectance, sr, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP09H1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP09H1 proprietary @@ -656,8 +656,8 @@ NOAA/VIIRS/001/VNP21A1N VNP21A1N.001: Night Land Surface Temperature and Emissiv NOAA/VIIRS/001/VNP22Q2 VNP22Q2: Land Surface Phenology Yearly L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP22Q2') NASA LP DAAC at the USGS EROS Center 2013-01-01 2022-01-01 -180, -90, 180, 90 False land, nasa, ndvi, noaa, npp, onset_greenness, phenology, surface, vegetation, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP22Q2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP22Q2 proprietary NOAA/VIIRS/001/VNP43IA1 VNP43IA1: BRDF/Albedo Model Parameters Daily L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP43IA1') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-06-09 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP43IA1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP43IA1 proprietary NOAA/VIIRS/001/VNP43IA2 VNP43IA2: BRDF/Albedo Quality Daily L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP43IA2') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-06-09 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP43IA2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP43IA2 proprietary -NOAA/VIIRS/001/VNP46A1 VNP46A1: VIIRS Daily Gridded Day Night Band 500m Linear Lat Lon Grid Night image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A1') NASA LAADS DAAC 2012-01-19 2024-10-30 -180, -90, 180, 90 False daily, dnb, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A1 proprietary -NOAA/VIIRS/001/VNP46A2 VNP46A2: VIIRS Lunar Gap-Filled BRDF Nighttime Lights Daily L3 Global 500m image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A2') NASA LAADS DAAC 2012-01-19 2024-10-21 -180, -90, 180, 90 False brdf, daily, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A2 proprietary +NOAA/VIIRS/001/VNP46A1 VNP46A1: VIIRS Daily Gridded Day Night Band 500m Linear Lat Lon Grid Night image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A1') NASA LAADS DAAC 2012-01-19 2024-10-31 -180, -90, 180, 90 False daily, dnb, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A1 proprietary +NOAA/VIIRS/001/VNP46A2 VNP46A2: VIIRS Lunar Gap-Filled BRDF Nighttime Lights Daily L3 Global 500m image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A2') NASA LAADS DAAC 2012-01-19 2024-10-24 -180, -90, 180, 90 False brdf, daily, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A2 proprietary NOAA/VIIRS/001/VNP64A1 VNP64A1: Burned Area Monthly L4 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP64A1') NASA LP DAAC at the USGS EROS Center 2014-01-01 2019-01-01 -180, -90, 180, 90 False burn, change_detection, land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP64A1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP64A1 proprietary NOAA/VIIRS/DNB/ANNUAL_V21 VIIRS Nighttime Day/Night Annual Band Composites V2.1 image_collection ee.ImageCollection('NOAA/VIIRS/DNB/ANNUAL_V21') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 2012-04-01 2021-01-01 -180, -65, 180, 75 False annual, dnb, eog, lights, nighttime, noaa, viirs, visible https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_DNB_ANNUAL_V21.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V21 proprietary NOAA/VIIRS/DNB/ANNUAL_V22 VIIRS Nighttime Day/Night Annual Band Composites V2.2 image_collection ee.ImageCollection('NOAA/VIIRS/DNB/ANNUAL_V22') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 2012-04-01 2023-01-01 -180, -65, 180, 75 False annual, dnb, eog, lights, nighttime, noaa, viirs, visible https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_DNB_ANNUAL_V22.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V22 proprietary @@ -665,7 +665,7 @@ NOAA/VIIRS/DNB/MONTHLY_V1/VCMCFG VIIRS Nighttime Day/Night Band Composites Versi NOAA/VIIRS/DNB/MONTHLY_V1/VCMSLCFG VIIRS Stray Light Corrected Nighttime Day/Night Band Composites Version 1 image_collection ee.ImageCollection('NOAA/VIIRS/DNB/MONTHLY_V1/VCMSLCFG') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 2014-01-01 2024-06-04 -180, -65, 180, 75 False dnb, eog, lights, monthly, nighttime, noaa, stray_light, viirs, visible https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_DNB_MONTHLY_V1_VCMSLCFG.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_MONTHLY_V1_VCMSLCFG proprietary NRCan/CDEM Canadian Digital Elevation Model image_collection ee.ImageCollection('NRCan/CDEM') NRCan 1945-01-01 2011-01-01 -142, 41, -52, 84 False canada, cdem, dem, elevation, geophysical, nrcan, topography https://storage.googleapis.com/earthengine-stac/catalog/NRCan/NRCan_CDEM.json https://developers.google.com/earth-engine/datasets/catalog/NRCan_CDEM OGL-Canada-2.0 Netherlands/Beeldmateriaal/LUCHTFOTO_RGB Netherlands orthophotos image_collection ee.ImageCollection('Netherlands/Beeldmateriaal/LUCHTFOTO_RGB') Beeldmateriaal Nederland 2021-01-01 2022-12-31 3.2, 50.75, 7.22, 53.7 False orthophoto, rgb, netherlands https://storage.googleapis.com/earthengine-stac/catalog/Netherlands/Netherlands_Beeldmateriaal_LUCHTFOTO_RGB.json https://developers.google.com/earth-engine/datasets/catalog/Netherlands_Beeldmateriaal_LUCHTFOTO_RGB CC-BY-4.0 -OREGONSTATE/PRISM/AN81d PRISM Daily Spatial Climate Dataset AN81d image_collection ee.ImageCollection('OREGONSTATE/PRISM/AN81d') PRISM / OREGONSTATE 1981-01-01 2024-10-27 -125, 24, -66, 50 False climate, daily, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_AN81d.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_AN81d proprietary +OREGONSTATE/PRISM/AN81d PRISM Daily Spatial Climate Dataset AN81d image_collection ee.ImageCollection('OREGONSTATE/PRISM/AN81d') PRISM / OREGONSTATE 1981-01-01 2024-10-29 -125, 24, -66, 50 False climate, daily, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_AN81d.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_AN81d proprietary OREGONSTATE/PRISM/AN81m PRISM Monthly Spatial Climate Dataset AN81m image_collection ee.ImageCollection('OREGONSTATE/PRISM/AN81m') PRISM / OREGONSTATE 1895-01-01 2024-09-01 -125, 24, -66, 50 False climate, geophysical, monthly, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_AN81m.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_AN81m proprietary OREGONSTATE/PRISM/Norm81m PRISM Long-Term Average Climate Dataset Norm81m [deprecated] image_collection ee.ImageCollection('OREGONSTATE/PRISM/Norm81m') PRISM / OREGONSTATE 1981-01-01 2010-12-31 -125, 24, -66, 50 True 30_year, climate, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_Norm81m.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_Norm81m proprietary OREGONSTATE/PRISM/Norm91m PRISM Long-Term Average Climate Dataset Norm91m image_collection ee.ImageCollection('OREGONSTATE/PRISM/Norm91m') PRISM / OREGONSTATE 1991-01-01 2020-12-31 -125, 24, -66, 50 False 30_year, climate, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_Norm91m.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_Norm91m proprietary @@ -728,7 +728,7 @@ TIGER/2018/States TIGER: US Census States 2018 table ee.FeatureCollection('TIGER TIGER/2020/BG TIGER: US Census Block Groups (BG) 2020 table ee.FeatureCollection('TIGER/2020/BG') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_BG.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_BG proprietary TIGER/2020/TABBLOCK20 TIGER: 2020 Tabulation (Census) Block table ee.FeatureCollection('TIGER/2020/TABBLOCK20') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_TABBLOCK20.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_TABBLOCK20 proprietary TIGER/2020/TRACT TIGER: US Census Tracts table ee.FeatureCollection('TIGER/2020/TRACT') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_TRACT.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_TRACT proprietary -TOMS/MERGED TOMS and OMI Merged Ozone Data image_collection ee.ImageCollection('TOMS/MERGED') NASA / GES DISC 1978-11-01 2024-10-29 -180, -90, 180, 90 False atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms https://storage.googleapis.com/earthengine-stac/catalog/TOMS/TOMS_MERGED.json https://developers.google.com/earth-engine/datasets/catalog/TOMS_MERGED proprietary +TOMS/MERGED TOMS and OMI Merged Ozone Data image_collection ee.ImageCollection('TOMS/MERGED') NASA / GES DISC 1978-11-01 2024-10-30 -180, -90, 180, 90 False atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms https://storage.googleapis.com/earthengine-stac/catalog/TOMS/TOMS_MERGED.json https://developers.google.com/earth-engine/datasets/catalog/TOMS_MERGED proprietary TRMM/3B42 TRMM 3B42: 3-Hourly Precipitation Estimates image_collection ee.ImageCollection('TRMM/3B42') NASA GES DISC at NASA Goddard Space Flight Center 1998-01-01 2019-12-31 -180, -50, 180, 50 False 3_hourly, climate, geophysical, jaxa, nasa, precipitation, rainfall, trmm, weather https://storage.googleapis.com/earthengine-stac/catalog/TRMM/TRMM_3B42.json https://developers.google.com/earth-engine/datasets/catalog/TRMM_3B42 proprietary TRMM/3B43V7 TRMM 3B43: Monthly Precipitation Estimates image_collection ee.ImageCollection('TRMM/3B43V7') NASA GES DISC at NASA Goddard Space Flight Center 1998-01-01 2019-12-01 -180, -50, 180, 50 False climate, geophysical, jaxa, nasa, precipitation, rainfall, trmm, weather https://storage.googleapis.com/earthengine-stac/catalog/TRMM/TRMM_3B43V7.json https://developers.google.com/earth-engine/datasets/catalog/TRMM_3B43V7 proprietary TUBerlin/BigEarthNet/v1 TUBerlin/BigEarthNet/v1 image_collection ee.ImageCollection('TUBerlin/BigEarthNet/v1') BigEarthNet 2017-06-01 2018-05-31 -9, 36.9, 31.6, 68.1 False chip, copernicus, corine_derived, label, ml, sentinel, tile https://storage.googleapis.com/earthengine-stac/catalog/TUBerlin/TUBerlin_BigEarthNet_v1.json https://developers.google.com/earth-engine/datasets/catalog/TUBerlin_BigEarthNet_v1 proprietary @@ -907,4 +907,4 @@ projects/planet-nicfi/assets/basemaps/americas NICFI Satellite Data Program Base projects/planet-nicfi/assets/basemaps/asia NICFI Satellite Data Program Basemaps for Tropical Forest Monitoring - Asia image_collection ee.ImageCollection('projects/planet-nicfi/assets/basemaps/asia') Planet 2015-12-01 2024-09-01 -180, -27.5, 180, 30.2 False basemaps, forest, nicfi, planet, sr, surface_reflectance, tropics https://storage.googleapis.com/earthengine-stac/catalog/planet-nicfi/projects_planet-nicfi_assets_basemaps_asia.json https://developers.google.com/earth-engine/datasets/catalog/projects_planet-nicfi_assets_basemaps_asia proprietary projects/sat-io/open-datasets/GLOBathy/GLOBathy_bathymetry GLOBathy Global lakes bathymetry dataset image ee.Image('projects/sat-io/open-datasets/GLOBathy/GLOBathy_bathymetry') Bahram Khazaei 2022-01-26 2022-01-26 -180, -90, 180, 90 False bathymetry, hydrology, lake https://storage.googleapis.com/earthengine-stac/catalog/sat-io/projects_sat-io_open-datasets_GLOBathy_GLOBathy_bathymetry.json https://developers.google.com/earth-engine/datasets/catalog/projects_sat-io_open-datasets_GLOBathy_GLOBathy_bathymetry CC0-1.0 projects/sat-io/open-datasets/ORNL/LANDSCAN_GLOBAL LandScan Population Data Global 1km image_collection ee.ImageCollection('projects/sat-io/open-datasets/ORNL/LANDSCAN_GLOBAL') Oak Ridge National Laboratory 2000-01-01 2022-12-31 -180, -90, 180, 90 False demography, landscan, population https://storage.googleapis.com/earthengine-stac/catalog/sat-io/projects_sat-io_open-datasets_ORNL_LANDSCAN_GLOBAL.json https://developers.google.com/earth-engine/datasets/catalog/projects_sat-io_open-datasets_ORNL_LANDSCAN_GLOBAL CC-BY-4.0 -projects/sat-io/open-datasets/us-drought-monitor United States Drought Monitor image_collection ee.ImageCollection('projects/sat-io/open-datasets/us-drought-monitor') National Drought Mitigation Center 2000-01-04 2024-10-15 -180, -90, 180, 90 False drought, ndmc, noaa, usda https://storage.googleapis.com/earthengine-stac/catalog/sat-io/projects_sat-io_open-datasets_us-drought-monitor.json https://developers.google.com/earth-engine/datasets/catalog/projects_sat-io_open-datasets_us-drought-monitor proprietary +projects/sat-io/open-datasets/us-drought-monitor United States Drought Monitor image_collection ee.ImageCollection('projects/sat-io/open-datasets/us-drought-monitor') National Drought Mitigation Center 2000-01-04 2024-10-22 -180, -90, 180, 90 False drought, ndmc, noaa, usda https://storage.googleapis.com/earthengine-stac/catalog/sat-io/projects_sat-io_open-datasets_us-drought-monitor.json https://developers.google.com/earth-engine/datasets/catalog/projects_sat-io_open-datasets_us-drought-monitor proprietary diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json index 29cbabc..cef8540 100644 --- a/nasa_cmr_catalog.json +++ b/nasa_cmr_catalog.json @@ -31553,26 +31553,26 @@ { "id": "ATL04_006", "title": "ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL04_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL04_006", "description": "ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, { "id": "ATL04_006", "title": "ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL04_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL04_006", "description": "ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, @@ -31735,26 +31735,26 @@ { "id": "ATL10_006", "title": "ATLAS/ICESat-2 L3A Sea Ice Freeboard V006", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL10_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL10_006", "description": "This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, { "id": "ATL10_006", "title": "ATLAS/ICESat-2 L3A Sea Ice Freeboard V006", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL10_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL10_006", "description": "This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, @@ -31852,52 +31852,52 @@ { "id": "ATL14_003", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2019-03-29", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL14_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL14_003", "description": "ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.", "license": "proprietary" }, { "id": "ATL14_003", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2019-03-29", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL14_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL14_003", "description": "ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.", "license": "proprietary" }, { "id": "ATL14_004", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2019-01-01", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL14_004", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL14_004", "description": "This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).", "license": "proprietary" }, { "id": "ATL14_004", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2019-01-01", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL14_004", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL14_004", "description": "This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).", "license": "proprietary" }, @@ -32008,26 +32008,26 @@ { "id": "ATL19_003", "title": "ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -88, 180, 88", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2746899536-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2746899536-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL19_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2754956786-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2754956786-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL19_003", "description": "This data set contains monthly gridded dynamic ocean topography (DOT), derived from along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided in this data set. Both single beam and all-beam gridded averages are available in this data set. Single beam averages are useful to identify biases among the beams and the all-beam averages are advised to use for physical oceanography.", "license": "proprietary" }, { "id": "ATL19_003", "title": "ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -88, 180, 88", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2754956786-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2754956786-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL19_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2746899536-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2746899536-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL19_003", "description": "This data set contains monthly gridded dynamic ocean topography (DOT), derived from along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided in this data set. Both single beam and all-beam gridded averages are available in this data set. Single beam averages are useful to identify biases among the beams and the all-beam averages are advised to use for physical oceanography.", "license": "proprietary" }, @@ -32060,26 +32060,26 @@ { "id": "ATL21_003", "title": "ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL21_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL21_003", "description": "ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids.", "license": "proprietary" }, { "id": "ATL21_003", "title": "ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL21_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL21_003", "description": "ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids.", "license": "proprietary" }, @@ -41339,32 +41339,6 @@ "description": "CAL_LID_L2_01kmCLay-Standard-V4-51 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 1 km Cloud Layer, Version 4-51 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Within this layer product are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products contain column descriptors associated with several layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. From June 13, 2006, to September 13, 2018, CALIPSO was part of the A-Train constellation for coincident Earth Observations. After September 13, 2018, the satellite was lowered from 705 to 688 km to resume flying in formation with CloudSat, called the C-Train.", "license": "proprietary" }, - { - "id": "CAL_LID_L2_05kmALay-Prov-V3-02_V3-02", - "title": "CALIPSO Lidar Level 2 5km Aerosol Layer data, Provisional V3-02", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "2011-11-01", - "end_date": "2013-03-01", - "bbox": "180, -90, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1522935473-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1522935473-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/CAL_LID_L2_05kmALay-Prov-V3-02_V3-02", - "description": "CAL_LID_L2_05kmALay-Prov-V3-02 data are Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5km aerosol layer data. Within the Lidar Aerosol Layer Product there are two general classes of data:- Column Properties (including position data and viewing geometry)- Layer Properties. The lidar layer products consist of a sequence of column descriptors, each one of which is associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. Version 3.02 represents a transition of the Lidar, IIR, and WFC processing and browse code to a new cluster computing system. No algorithm changes were introduced and very minor changes were observed between V3.01 and V3.02 as a result of the compiler and computer architecture differences. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in formation in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.", - "license": "proprietary" - }, - { - "id": "CAL_LID_L2_05kmALay-Prov-V3-30_V3-30", - "title": "CALIPSO Lidar Level 2 5km Aerosol Layer data, Provisional V3-30", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "2013-03-01", - "end_date": "2016-12-08", - "bbox": "180, -90, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1523564910-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1523564910-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/CAL_LID_L2_05kmALay-Prov-V3-30_V3-30", - "description": "CAL_LID_L2_05kmALay-Prov-V3-30 data are Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5km aerosol layer data, Provisional Version 3-30. Data collection for this product is complete. Within the Lidar Aerosol Layer Product there are two general classes of data:- Column Properties (including position data and viewing geometry)- Layer Properties. The lidar layer products consist of a sequence of column descriptors, each one of which is associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The science algorithms used to produce the V3.30 CALIOP data products are identical to those used to generate the V3.01 and V3.02 products; however, some of the ancillary data used in the V3.30 analyses is different. All CALIOP data products rely on meteorological data provided by NASA's Global Modeling and Assimilation Office (GMAO). The V3.01 and V3.02 data products were produced using the GMAO's GEOS 5.2 data products. CALIPSO was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite is comprised of three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.", - "license": "proprietary" - }, { "id": "CAL_LID_L2_05kmALay-Standard-V4-20_V4-20", "title": "CALIPSO Lidar Level 2 5 km Aerosol Layer Data, V4-20", @@ -41404,19 +41378,6 @@ "description": "CAL_LID_L2_05kmALay-Standard-V4-51 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5 km Aerosol Layer Data, Version 4-51 data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Within this layer product are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre national d'\u00e9tudes spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. From June 13, 2006, to September 13, 2018, CALIPSO was part of the A-Train constellation for coincident Earth Observations. After September 13, 2018, the satellite was lowered from 705 to 688 km to resume flying in formation with CloudSat, called the C-Train.", "license": "proprietary" }, - { - "id": "CAL_LID_L2_05kmAPro-Prov-V3-02_V3-02", - "title": "CALIPSO Lidar Level 2 5km Aerosol Profile data, Provisional V3-02", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "2011-11-01", - "end_date": "2013-03-01", - "bbox": "180, -90, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1522937252-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1522937252-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/CAL_LID_L2_05kmAPro-Prov-V3-02_V3-02", - "description": "CAL_LID_L2_05kmAPro-Prov-V3-02 data are Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 aerosol profile data using the CALIPSO Lidar Ratio selection algorithm. The Lidar Level 2 Aerosol Profile data products contain averaged aerosol profile data and ancillary data. There are no layer descriptors included in the lidar aerosol profile data products. The spatial distribution of the aerosol layers is instead completely characterized by the aerosol layer fraction and atmospheric volume description parameters. The aerosol profile products are generated at a uniform horizontal resolution of 5 km. The aerosol backscatter and extinction coefficients are computed using a lidar ratio selected by the CALIPSO Lidar Ratio selection algorithm. Version 3.02 represents a transition of the Lidar, IIR, and WFC processing and browse code to a new cluster computing system. No algorithm changes were introduced and very minor changes were observed between V3.01 and V3.02 as a result of the compiler and computer architecture differences. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.", - "license": "proprietary" - }, { "id": "CAL_LID_L2_05kmAPro-Standard-V4-20_V4-20", "title": "CALIPSO Lidar Level 2 Aerosol Profile, V4-20", @@ -41573,19 +41534,6 @@ "description": "CAL_LID_L2_05kmMLay-Standard-V4-51 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5 km Merged (cloud + aerosol) Layer Data, Version 4-51 data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Within this layer product are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. From June 13, 2006, to September 13, 2018, CALIPSO was part of the A-Train constellation for coincident Earth Observations. After September 13, 2018, the satellite was lowered from 705 to 688 km to resume flying in formation with CloudSat, called the C-Train.", "license": "proprietary" }, - { - "id": "CAL_LID_L2_333mCLay-ValStage1-V3-30_V3-30", - "title": "CALIPSO Lidar Level 2 1/3km Cloud Layer data, Validated Stage 1 V3-30", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "2013-03-01", - "end_date": "2016-12-08", - "bbox": "180, -90, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1523234283-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1523234283-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/CAL_LID_L2_333mCLay-ValStage1-V3-30_V3-30", - "description": "CAL_LID_L2_333mCLay-ValStage1-V3-30 data are Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 1/3km (333m) cloud layer data, Validated Stage 1 Version 3-30. Data collection for this product is complete. Within the Lidar Cloud Layer Product there are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each one of which is associated with a variable number of layer descriptors. The column descriptors specify the temporal and geo-physical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., cloud and/or aerosol layers) identified within the column. For each feature within a column, a set of layer descriptors is reported. The layer descriptors provide information about the spatial and optical characteristics of a feature, such as base and top altitudes, integrated attenuated backscatter, and optical depth. New parameters for the V3-01 product include column optical depths, layer top pressure, layer base pressure, layer mid-point pressure, layer top temperature, and layer base temperature. The science algorithms used to produce the V3.30 Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) data products are identical to those used to generate the V3.01 and V3.02 products; however, some of the ancillary data used in the V3.30 analyses are different. All CALIOP data products rely on meteorological data provided by NASA's Global Modeling and Assimilation Office (GMAO). The V3.01 and V3.02 data products were produced using the GMAO's GEOS 5.2 data products. CALIPSO was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite is comprised of three instruments, CALIOP, the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.", - "license": "proprietary" - }, { "id": "CAL_LID_L2_333mMLay-Standard-V4-20_V4-20", "title": "CALIPSO Lidar Level 2 1/3 km Merged Layer, V4-20", @@ -48749,19 +48697,6 @@ "description": "CER_ES9_NOAA20-FM6_Edition1, CERES ERBE-like Monthly Regional Averages NOAA-20 FM6 Edition 1, contains TOA fluxes from the Clouds and the Earth's Radiant Energy System (CERES) instrument using algorithms identical to those used by ERBE, regional averages of instantaneous footprint TOA fluxes only for the hours of satellite overpass (from ES-8 Level 2 product). The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time-averaged CERES data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9, along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is like the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. T The CERES instrument (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The last CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite on November 18, 2017.", "license": "proprietary" }, - { - "id": "CER_ES9_NPP-FM5_Edition1-CV", - "title": "CERES ERBE-like Monthly Regional Averages NPP FM5 Edition1-CV", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "2012-02-01", - "end_date": "2019-10-31", - "bbox": "180, -90, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C7057070-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C7057070-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/CER_ES9_NPP-FM5_Edition1-CV", - "description": "CER_ES9_NPP-FM5_Edition1-CV is the Clouds and the Earth's Radiant Energy System (CERES) Earth Radiation Budget Experiment (ERBE)-like Monthly Regional Averages from the Suomi National Polar-orbiting Partnership (NPP), CERES Flight Model 5 (CERES-FM5) Edition1-CV data product. Data for this product is collected by way of the CERES-FM5 instrument on the Suomi-NPP platform. Data collection for this product is complete. Note: Edition1-CV data are for instrument validation purposes only and not suited for science publications. CER_ES9_NPP-FM5_Edition1-CV data are CERES instrument Top-of-the-Atmosphere (TOA) fluxes using algorithms identical to those used by ERBE, regional averages of instantaneous footprint TOA fluxes only for the hours of satellite overpass (from ES-8 Level 2 product). Edition1-CV data are for instrument validation purposes only and not suited for science publications.The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave (SW) and long-wave (LW) fluxes at the TOA from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is like the algorithm used for ERBE. The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. CERES is a key component of the Earth Observing System (EOS) program. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions are a follow-on to the successful ERBE mission. The first CERES instrument, protoflight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017.", - "license": "proprietary" - }, { "id": "CER_ES9_NPP-FM5_Edition2", "title": "CERES ERBE-like Gridded Instantaneous TOA Fluxes (ES9) NPP CERES FM-5 Edition2", @@ -58954,19 +58889,6 @@ "description": "The concentration of heavy metals in seawater at four sites around Casey was determined via Diffusive Gradients in Thin films (DGT) loggers attached to experimental mesocosms suspended below the sea ice. Data are the concentration of heavy metals in micrograms per litre (ug/l), equivalent to parts per billion (ppb)/litre Two loggers were attached to each mesocosm (perforated 20 litre food buckets) at each site; one at the top and one at the bottom of each mesocosm. Mesocosms were suspended two to three metres below the bottom edge of the sea ice through a 1 metre diameter hole and were periodically raised to the surface for short periods (~1 hour). This experiment was part of the short-term biomonitoring program for the Thala Valley Tip Clean-up at Casey during summer 2003/04. During Runs 1 and 2 of the experiment mesocosms were deployed at Brown Bay Inner (S66 16.811 E110 32.475), Brown Bay Outer (S66 16.811 E110 32.526), McGrady Cove (S66 16.556 E110 34.392) and O'Brien Bay 1 (S66 18.730 E110 30.810). In Run 3 mesocosm were deployed in open water with no sea ice covering at Brown Bay Inner (S66 16.807 E110 32.556), Brown Bay Outer (S66 16.805 E110 32.607), McGrady Cove (S66 16.520 E110 34.257) and O'Brien Bay (S66 17.607 E110 31.247). These data were collected as part of ASAC project 2201 (ASAC_2201 - Natural variability and human induced change in Antarctic nearshore marine benthic communities). See also other metadata records by Glenn Johnstone for related information.", "license": "proprietary" }, - { - "id": "DISCOVER-AQ_Aircraft_Remote_Sensing_Aerosol_Data_1", - "title": "DISCOVER-AQ UC-12 Aircraft HSRL Aerosol Measurements", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "2011-07-01", - "end_date": "2013-09-04", - "bbox": "-123.86, 28.28, -74.71, 39.77", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1604617793-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1604617793-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/DISCOVER-AQ_Aircraft_Remote_Sensing_Aerosol_Data_1", - "description": "DISCOVER-AQ_Aircraft_Remote_Sensing_Aerosol_Data are NASA UC-12 aircraft HSRL measurements of extinction, backscattering, and depolarization profiles at 1064 and 532 nm made during the first deployment of the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations (DISCOVER-AQ). Data collection is complete.", - "license": "proprietary" - }, { "id": "DISCOVERAQ_California_Aerosol_AircraftInSitu_P3B_Data_1", "title": "DISCOVER-AQ California Deployment P-3B Aircraft In Situ Aerosol Data", @@ -59604,19 +59526,6 @@ "description": "DISCOVERAQ_Maryland_Ground_Padonia_Data contains data collected at the Padonia ground site during the Maryland (Baltimore-Washington) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.", "license": "proprietary" }, - { - "id": "DISCOVERAQ_Maryland_Ground_Pandora_Data_1", - "title": "DISCOVER-AQ Maryland Deployment Pandora Column Observations", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "2011-06-11", - "end_date": "2011-11-14", - "bbox": "-85, 30, 70, 45", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2358894935-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2358894935-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/DISCOVERAQ_Maryland_Ground_Pandora_Data_1", - "description": "DISCOVERAQ_Maryland_Pandora_Data contains all of the Pandora instrumentation data collected during the DISCOVER-AQ field study. Contained in this dataset are column measurements of NO2 and O3. Pandoras were situated at various ground sites across the study area, including Aldino, Beltsville, Edgewood, Essex, Fairhill, GSFC, Oldtown, Padonia, SERC, UMBC, UMD, and USNA. This data product contains only data from the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.", - "license": "proprietary" - }, { "id": "DISCOVERAQ_Maryland_Ground_UMBC_Data_1", "title": "DISCOVER-AQ Maryland Deployment UMBC Ground Site Data", @@ -61372,6 +61281,19 @@ "description": "This dataset provides sediment transport and land accretion model results at Wax Lake Delta (WLD), Atchafalaya Basin, in coastal Louisiana, USA. Data were simulated over the Delta-X Spring 2021 (2021-03-21 to 2021-04-03) and Fall 2021 (2021-08-14 to 2021-08-27) campaigns and the results are presented as annualized land accretion rate map. The model results for these two short-term campaigns are used to calculate the 1-year upscale land accretion rate at WLD in post-processing, which is also provided in this dataset. Model results for these two short-term campaigns were derived using inputs from an ANUGA hydrodynamic model. The Matlab sediment transport and land accretion model used to derive these data employs sediment transport theory that models floc behavior using a non-cohesive sediment transport framework. Data are presented in NetCDF (*.nc) format.", "license": "proprietary" }, + { + "id": "DeltaX_LandAccretion_WLD_2309_1", + "title": "Delta-X: Matlab Model for Wax Lake Delta Land Accretion", + "catalog": "ORNL_CLOUD STAC Catalog", + "state_date": "2021-03-20", + "end_date": "2021-08-27", + "bbox": "-91.58, 29.39, -91.33, 29.59", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281998337-ORNL_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281998337-ORNL_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/DeltaX_LandAccretion_WLD_2309_1", + "description": "This dataset provides the Matlab sediment transport and land accretion model at Wax Lake Delta (WLD), Atchafalaya Basin, in coastal Louisiana. The data include the Matlab scripts that solve the advection and Exner equations to simulate the suspended sediment transport and accretion at WLD. The model requires modeled flow information from a separate ANUGA hydrodynamic model as inputs. For this study, ANUGA modeled flow information from the Delta-X Spring and Fall 2021 campaigns were used as inputs. The ANUGA output files are converted to variables used by this Matlab model using pre-processing tools. The main code calculates suspended sediment fluxes and accretion rates of mud and sand as a function of space and time. The cumulative sediment accretion from each campaign was then used to estimate an annualized land accretion map using a weighted-average formula presented. The final product, the one-yr upscaled land accretion map, is archived as a separate dataset.", + "license": "proprietary" + }, { "id": "DeltaX_MarshAccretion_NUMAR_2354_1", "title": "Delta-X: NUMAR Predictive Model for Marsh Accretion Rates and Chemical Properties", @@ -61385,6 +61307,19 @@ "description": "This dataset provides input data and model code to run the Marsh Accretion Rates (NUMAR) process model used to predict soil accretion rates and chemical properties for marsh sites in the Mississippi River Delta. NUMAR is a modification of the NUMAN model by Chen and Twilley (1999) that was developed for mangrove environments. This dataset provides Python code, input data in comma separated values (CSV) format, and documentation for installing and running the model in Portable Document Format (PDF).", "license": "proprietary" }, + { + "id": "DeltaX_NUMAR_Soil_Accretion_2368_1", + "title": "Delta-X: NUMAR Soil Accretion Modeled to 2100, MRD, Louisiana, USA", + "catalog": "ORNL_CLOUD STAC Catalog", + "state_date": "2021-01-01", + "end_date": "2100-12-31", + "bbox": "-91.54, 29.08, -90.41, 29.7", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281999060-ORNL_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281999060-ORNL_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/DeltaX_NUMAR_Soil_Accretion_2368_1", + "description": "This dataset holds modeled estimates of soil accretion for the Atchafalaya and Terrebonne basins in the Mississippi River Delta of coastal Louisiana, U.S. Soil accretion was predicted from 2021-2100 using the Numerical Understanding of Marsh Accretion Resilience (NUMAR) model. This process-based model is an adaptation of the NUMAN model that was modified for marsh environments. The input parameters were aggregated within ecogeomorphic cells, areas of similar vegetation and elevation. The dataset includes spatially explicit input values, description of important parameters, and a shapefile of model outputs.", + "license": "proprietary" + }, { "id": "DeltaX_Particle_Size_LISST_V2_2077_2", "title": "Delta-X: In situ Beam Attenuation and Particle Size from LISST-200X, 2021", @@ -70812,7 +70747,7 @@ }, { "id": "GCOM-C_SGLI_L2_ARNP_NA", - "title": "GCOM-C/SGLI L2 Aerosol over the ocean-Land aerosol by near ultra violet", + "title": "GCOM-C/SGLI L2 AeRosol properties using Numerical Prediction", "catalog": "JAXA STAC Catalog", "state_date": "2018-01-01", "end_date": "", @@ -70820,7 +70755,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2698132339-JAXA.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2698132339-JAXA.html", "href": "https://cmr.earthdata.nasa.gov/stac/JAXA/collections/GCOM-C_SGLI_L2_ARNP_NA", - "description": "GCOM-C/SGLI L2 Aerosol over the ocean-Land aerosol by near ultra violet dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:ARAE_land, ARAE_ocean: Angstrom Exponent over Land and Ocean at 500 nm and 380 nm (dimensionless), respectively.AROT_land, AROT_ocean: Aerosol Optical Thickness over Land and Ocean at 500 nm (dimensionless), respectively.The utilized aerosol optical model for the retrieval is the same for both over land and ocean, and the coefficients are based on the skyradiometer observations. While the particle shapes, real parts of complex refraction indices, and size distributions of large and small particles are assumed to be fixed, the fraction of small particles and complex refraction indices (in terms of SSA) vary. The algorithm assumes reasonable aerosol parameters for the SGLI observations and derives the contents of this dataset.The provided format is HDF5. The spatial resolution is 1 km. The projection method is EQA. The spatial coverage is \"Tile\". The current version of the product is Version 3. The Version 2 is also available.", + "description": "GCOM-C/SGLI L2 AeRosol properties using Numerical Prediction dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:AROT: Aerosol Optical Thickness over land and ocean at 500 nm (dimensionless).ARAE: Angstrom Exponent over land and ocean at 500 nm and 380 nm (dimensionless).ASSA: Single Scattering Albedo over land and ocean at 380 nm (dimensionless).AROT_uncertainty, AROT_uncertainty, AROT_uncertainty: The uncertainties of AROT, ARAE and ASSA, respectively (dimensionless).The utilized aerosol optical model for the retrieval is the same for both over land and ocean, and the coefficients are based on the skyradiometer observations. While the particle shapes, real parts of complex refraction indices, and size distributions of large and small particles are assumed to be fixed, the fraction of small particles and complex refraction indices (in terms of SSA) vary. The algorithm assumes reasonable aerosol parameters for the SGLI observations and derives the contents of this dataset.The provided format is HDF5. The spatial resolution is 1 km. The projection method is EQA. The spatial coverage is \"Tile\". The current version of the product is Version 3. The Version 2 is also available.", "license": "proprietary" }, { @@ -71098,7 +71033,7 @@ }, { "id": "GCOM-C_SGLI_L2_global-ARNP_NA", - "title": "GCOM-C/SGLI L2 Global-Aerosol over the ocean-Land aerosol by near ultra violet", + "title": "GCOM-C/SGLI L2 Global-AeRosol properties using Numerical Prediction", "catalog": "JAXA STAC Catalog", "state_date": "2018-01-01", "end_date": "", @@ -71106,7 +71041,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2698132167-JAXA.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2698132167-JAXA.html", "href": "https://cmr.earthdata.nasa.gov/stac/JAXA/collections/GCOM-C_SGLI_L2_global-ARNP_NA", - "description": "GCOM-C/SGLI L2 Global-Aerosol over the ocean-Land aerosol by near ultra violet dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:ARAE_land, ARAE_ocean: Angstrom Exponent over Land and Ocean at 500 nm and 380 nm (dimensionless), respectively.AROT_land, AROT_ocean: Aerosol Optical Thickness over Land and Ocean at 500 nm (dimensionless), respectively.The utilized aerosol optical model for the retrieval is the same for both over land and ocean, and the coefficients are based on the skyradiometer observations. While the particle shapes, real parts of complex refraction indices, and size distributions of large and small particles are assumed to be fixed, the fraction of small particles and complex refraction indices (in terms of SSA) vary. The algorithm assumes reasonable aerosol parameters for the SGLI observations and derives the contents of this dataset.The provided format is HDF5. The spatial and temporal resolutions are 1/24 deg and daily, respectively. The projection method is EQA. The spatial coverage is Global. The current version of the product is Version 3. The Version 2 is also available, note that the QA_Flag data has been updated.", + "description": "GCOM-C/SGLI L2 Global-AeRosol properties using Numerical Prediction dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA).GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:AROT: Aerosol Optical Thickness over land and ocean at 500 nm (dimensionless).ARAE: Angstrom Exponent over land and ocean at 500 nm and 380 nm (dimensionless).ASSA: Single Scattering Albedo over land and ocean at 380 nm (dimensionless).AROT_uncertainty, AROT_uncertainty, AROT_uncertainty: The uncertainties of AROT, ARAE and ASSA, respectively (dimensionless).The utilized aerosol optical model for the retrieval is the same for both over land and ocean, and the coefficients are based on the skyradiometer observations. While the particle shapes, real parts of complex refraction indices, and size distributions of large and small particles are assumed to be fixed, the fraction of small particles and complex refraction indices (in terms of SSA) vary. The algorithm assumes reasonable aerosol parameters for the SGLI observations and derives the contents of this dataset.The provided format is HDF5. The spatial and temporal resolutions are 1/24 deg and daily, respectively. The projection method is EQA. The spatial coverage is Global. The current version of the product is Version 3. The Version 2 is also available, note that the QA_Flag data has been updated.", "license": "proprietary" }, { @@ -77775,7 +77710,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2698129808-JAXA.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2698129808-JAXA.html", "href": "https://cmr.earthdata.nasa.gov/stac/JAXA/collections/GCOM-W_AMSR2_L2_CLW_NA", - "description": "GCOM-W/AMSR2 Cloud Liquid Water dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 15 km. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The generation unit is scene (defined as a half orbit).", + "description": "GCOM-W/AMSR2 Cloud Liquid Water dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 15 km. The current version of the product is Version 2. The Version 1 is also available. The generation unit is scene (defined as a half orbit).", "license": "proprietary" }, { @@ -77879,7 +77814,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2698128998-JAXA.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2698128998-JAXA.html", "href": "https://cmr.earthdata.nasa.gov/stac/JAXA/collections/GCOM-W_AMSR2_L3_CLW_1day_0.1deg_NA", - "description": "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 day. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The projection method is EQR. The generation unit is global.", + "description": "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 day. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global.", "license": "proprietary" }, { @@ -77892,7 +77827,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2698129489-JAXA.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2698129489-JAXA.html", "href": "https://cmr.earthdata.nasa.gov/stac/JAXA/collections/GCOM-W_AMSR2_L3_CLW_1day_0.25deg_NA", - "description": "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 day. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The projection method is EQR. The generation unit is global.", + "description": "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 day. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global.", "license": "proprietary" }, { @@ -77905,7 +77840,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2698128896-JAXA.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2698128896-JAXA.html", "href": "https://cmr.earthdata.nasa.gov/stac/JAXA/collections/GCOM-W_AMSR2_L3_CLW_1month_0.1deg_NA", - "description": "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes Month Mean Cloud liquid water (CLW), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). CLW is amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Standard_Deviation is standard deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine \"Geophysical Data\". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 month. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The projection method is EQR. The generation unit is global.", + "description": "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes Month Mean Cloud liquid water (CLW), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). CLW is amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Standard_Deviation is standard deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine \"Geophysical Data\". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 month. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global.", "license": "proprietary" }, { @@ -77918,7 +77853,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2698131369-JAXA.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2698131369-JAXA.html", "href": "https://cmr.earthdata.nasa.gov/stac/JAXA/collections/GCOM-W_AMSR2_L3_CLW_1month_0.25deg_NA", - "description": "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). CLW is amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Standard_Deviation is standarad deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine \"Geophysical Data\". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 month. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The projection method is EQR. The generation unit is global.", + "description": "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the \"A-Train\" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth\u00e2\u0080\u0099s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). CLW is amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Standard_Deviation is standarad deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine \"Geophysical Data\". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 month. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global.", "license": "proprietary" }, { @@ -80121,104 +80056,104 @@ { "id": "GLAH04_033", "title": "GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH04_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH04_033", "description": "Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing.", "license": "proprietary" }, { "id": "GLAH04_033", "title": "GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH04_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH04_033", "description": "Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing.", "license": "proprietary" }, { "id": "GLAH05_034", "title": "GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V034", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000460-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000460-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH05_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549166-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549166-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH05_034", "description": "GLAH05 Level-1B waveform parameterization data include output parameters from the waveform characterization procedure and other parameters required to calculate surface slope and relief characteristics. GLAH05 contains parameterizations of both the transmitted and received pulses and other characteristics from which elevation and footprint-scale roughness and slope are calculated. The received pulse characterization uses two implementations of the retracking algorithms: one tuned for ice sheets, called the standard parameterization, used to calculate surface elevation for ice sheets, oceans, and sea ice; and another for land (the alternative parameterization). Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH05_034", "title": "GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V034", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549166-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549166-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH05_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000460-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000460-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH05_034", "description": "GLAH05 Level-1B waveform parameterization data include output parameters from the waveform characterization procedure and other parameters required to calculate surface slope and relief characteristics. GLAH05 contains parameterizations of both the transmitted and received pulses and other characteristics from which elevation and footprint-scale roughness and slope are calculated. The received pulse characterization uses two implementations of the retracking algorithms: one tuned for ice sheets, called the standard parameterization, used to calculate surface elevation for ice sheets, oceans, and sea ice; and another for land (the alternative parameterization). Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH06_034", "title": "GLAS/ICESat L1B Global Elevation Data (HDF5) V034", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000445-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000445-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH06_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2033638023-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2033638023-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH06_034", "description": "GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH06_034", "title": "GLAS/ICESat L1B Global Elevation Data (HDF5) V034", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2033638023-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2033638023-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH06_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000445-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000445-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH06_034", "description": "GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH07_033", "title": "GLAS/ICESat L1B Global Backscatter Data (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH07_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH07_033", "description": "GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH07_033", "title": "GLAS/ICESat L1B Global Backscatter Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH07_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH07_033", "description": "GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80248,19 +80183,6 @@ "description": "GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product.", "license": "proprietary" }, - { - "id": "GLAH09_033", - "title": "GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", - "state_date": "2003-02-20", - "end_date": "2009-10-11", - "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH09_033", - "description": "GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product.", - "license": "proprietary" - }, { "id": "GLAH09_033", "title": "GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033", @@ -80275,16 +80197,16 @@ "license": "proprietary" }, { - "id": "GLAH10_033", - "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033", + "id": "GLAH09_033", + "title": "GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033", "catalog": "NSIDC_CPRD STAC Catalog", - "state_date": "2003-09-25", + "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH10_033", - "description": "GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product.", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH09_033", + "description": "GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product.", "license": "proprietary" }, { @@ -80301,16 +80223,16 @@ "license": "proprietary" }, { - "id": "GLAH11_033", - "title": "GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033", + "id": "GLAH10_033", + "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033", "catalog": "NSIDC_CPRD STAC Catalog", - "state_date": "2003-02-20", + "state_date": "2003-09-25", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH11_033", - "description": "GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH10_033", + "description": "GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product.", "license": "proprietary" }, { @@ -80327,16 +80249,16 @@ "license": "proprietary" }, { - "id": "GLAH12_034", - "title": "GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034", + "id": "GLAH11_033", + "title": "GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033", "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH12_034", - "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH11_033", + "description": "GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.", "license": "proprietary" }, { @@ -80353,15 +80275,15 @@ "license": "proprietary" }, { - "id": "GLAH13_034", - "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034", + "id": "GLAH12_034", + "title": "GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034", "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH13_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH12_034", "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80378,6 +80300,19 @@ "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, + { + "id": "GLAH13_034", + "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034", + "catalog": "NSIDC_CPRD STAC Catalog", + "state_date": "2003-02-20", + "end_date": "2009-10-11", + "bbox": "-180, -86, 180, 86", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH13_034", + "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", + "license": "proprietary" + }, { "id": "GLAH14_034", "title": "GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034", @@ -86943,19 +86878,6 @@ "description": "This product provides level 3 monthly averages of tropospheric Nitrogen dioxide (NO2) vertical column density derived from the level 2 Tropospheric Monitoring Instrument (TROPOMI) across the globe oversampled to a spatial resolution of 0.1\u02da x 0.1\u02da (~10 km2) using a consistent algorithm from the European Space Agency (ESA) version 2.4 that can be used for trend analysis of air pollution. The dataset record began in January 2019 and continues to the present. This L3 product was developed by the George Washington University Air, Climate and Health Laboratory as part of the NASA Health Air Quality Applied Science Team (HAQAST) using Level 2 version 2.4 TROPOMI NO2 files from the ESA. The TROPOMI instrument on Sentinel-5 Precursor acquires tropospheric NO2 column contents from low Earth orbit (~824 km above ground level) once per day globally at approximately 13:30 local time. NO2 is an air pollutant that adversely affects the human respiratory system and leads to premature mortality. NO2 is also an important precursor for ozone and fine particulates, which also have severe health impacts. In urban areas, the majority of NO2 originates from anthropogenic NOx (=NO+NO2; most NOx is emitted as NO, which rapidly cycles to NO2) emissions during high-temperature fossil fuel combustion. Tropospheric NO2 vertical column contents are qualitatively representative of near-surface NO2 concentrations and NOx emissions in urban/polluted locations. ", "license": "proprietary" }, - { - "id": "HAWKEYE_L1_1", - "title": "SeaHawk-1 HawkEye Level-1A Data, version 1", - "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2018-12-03", - "end_date": "2023-10-27", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3160685741-OB_CLOUD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3160685741-OB_CLOUD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/HAWKEYE_L1_1", - "description": "The Hawkeye instrument, flown onboard the SeaHawk CubeSat, was optimized to provide high quality, high resolution imagery (120 meter) of the open ocean, coastal zones, lakes, estuaries and land features. This ability provides a valuable complement to the lower resolution measurements from previous missions like SeaWiFS, MODIS and VIIRS. The SeaHawk CubeSat mission is a partnership between NASA and the University of North Carolina, Wilmington (UNCW), Cloudland Instruments and AAC-Clyde Space and is funded by the Moore Foundation under a grant for the Sustained Ocean Color Observations with Nanosatellites (SOCON).", - "license": "proprietary" - }, { "id": "HAWKEYE_L1_1", "title": "SeaHawk HawkEye Level-1 Data, version 1", @@ -86969,6 +86891,19 @@ "description": "The Hawkeye instrument, flown onboard the SeaHawk CubeSat, was optimized to provide high quality, high resolution imagery (120 meter) of the open ocean, coastal zones, lakes, estuaries and land features. This ability provides a valuable complement to the lower resolution measurements from previous missions like SeaWiFS, MODIS and VIIRS. The SeaHawk CubeSat mission is a partnership between NASA and the University of North Carolina, Wilmington (UNCW), Cloudland Instruments and AAC-Clyde Space and is funded by the Moore Foundation under a grant for the Sustained Ocean Color Observations with Nanosatellites (SOCON).", "license": "proprietary" }, + { + "id": "HAWKEYE_L1_1", + "title": "SeaHawk-1 HawkEye Level-1A Data, version 1", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2018-12-03", + "end_date": "2023-10-27", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3160685741-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3160685741-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/HAWKEYE_L1_1", + "description": "The Hawkeye instrument, flown onboard the SeaHawk CubeSat, was optimized to provide high quality, high resolution imagery (120 meter) of the open ocean, coastal zones, lakes, estuaries and land features. This ability provides a valuable complement to the lower resolution measurements from previous missions like SeaWiFS, MODIS and VIIRS. The SeaHawk CubeSat mission is a partnership between NASA and the University of North Carolina, Wilmington (UNCW), Cloudland Instruments and AAC-Clyde Space and is funded by the Moore Foundation under a grant for the Sustained Ocean Color Observations with Nanosatellites (SOCON).", + "license": "proprietary" + }, { "id": "HAWKEYE_L2_OC_2018.0", "title": "SeaHawk HawkEye Regional Ocean Color (OC) Data, version 2018.0", @@ -119469,19 +119404,6 @@ "description": "This record relates to the Australian component of the Latitudinal Gradient Project. The LGP is largely a New Zealand, US and Italian venture, but a small contribution has been made by Australian scientists. The Australian component of this work was completed as part of ASAC projects 2361 and 2682 (ASAC_2361, and ASAC_2682). Data from this project were entered into the herbarium access database, which has been linked to this record. The list below contains details of where and when samples were collected, and also the type of sample and the method of sampling. Cape Hallett and vicinity (2000, 2004): Biodiversity assessment of terrestrial plants (mosses, lichens); Invertebrate collections (mites, Collembola); plant ecology and community analysis; photosynthetic physiology of mosses and lichens; molecular genetics of mosses and lichens. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, field laboratory experiments for physiological studies. Dry Valleys: Taylor Valley (1989, 1996), Garwood Valley (2001), Granite Harbour (1989; 1994, 1996) - plant ecology; plant physiology; biodiversity; invertebrate collections; molecular genetics of mosses. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, field laboratory experiments for physiological studies. Beaufort Island (1996) - plant biodiversity; molecular genetics of mosses. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, laboratory studies for molecular genetics. Darwin Glacier (1994): plant biodiversity; molecular genetics of invertebrates and mosses (random sampling for biodiversity; laboratory studies of invertebrate and moss molecular genetics). Project objectives: 1. Investigate the distribution of bryophytes and lichens in continental Antarctica 1a). to test the null hypothesis that species diversity does not change significantly with latitude; 1b). to explore the relationships between species and key environmental attributes including latitude, distance from the coast, temperature, substrate, snow cover, age of ice-free substrate. 2. To continue to participate in the Ross Sea Sector Latitudinal Gradient Project and develop an Australian corollary in the Prince Charles Mountains, involving international collaborators, incorporating the first two objectives of this project. 3. To develop an international collaborative biodiversity and ecophysiological program in the Prince Charles Mountains that will provide a parallel N-S latitude gradient study to mirror the LGP program in the Ross Sea region as part of the present RISCC cooperative program (to be superseded by the EBA (Evolution and Biodiversity of Antarctica) program) to address the above objectives. Taken from the 2008-2009 Progress Report: Progress against objectives: Continuing identification of moss and lichen samples previously collected from Cape Hallett, Granite Harbour and Darwin Glacier region. Lecidea s.l. lichens currently being studied in Austria by PhD student. Field work in Dry Valleys significantly curtailed by adverse weather. Field work planned for Darwin Glacier region and McMurdo Dry Valleys, particularly Taylor Valley and Granite Harbour region was severely curtailed due to adverse weather, helicopter diversions due to a Medical Evacuation, and other logistic constraints. 10 days of field time were lost. Limitations on field travel in Darwin Glacier region restricted the field work to a biologically depauperate region. The Prince Charles Mountains N-S transect, the only continental transect possibility for comparison with the Ross Sea area, unfortunately appears to have been abandoned through lack of logistic support. Taken from the 2009-2010 Progress Report: Identification of samples collected from AAT and Ross Sea Region continued during the year, interrupted significantly by the packing of the collection and transfer of specimens to the Tasmanian Herbarium. Work is now proceeding at the Herbarium with sorting, databasing and incorporation of packets into the Herbarium collection. The merging of the collection provides long-term security of curation and significantly boosts the cryptogam collections (35000 numbers) of the Tasmanian Herbarium.", "license": "proprietary" }, - { - "id": "LGRIP30_001", - "title": "Landsat-Derived Global Rainfed and Irrigated-Cropland Product 30 m V001", - "catalog": "LPDAAC_ECS STAC Catalog", - "state_date": "2014-01-01", - "end_date": "2017-12-31", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2592845930-LPDAAC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2592845930-LPDAAC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/LGRIP30_001", - "description": "The Landsat-Derived Global Rainfed and Irrigated-Cropland Product (LGRIP) provides high resolution, global cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data (GFSAD) project, LGRIP maps the world\u2019s agricultural lands by dividing them into irrigated and rainfed croplands, and calculates irrigated and rainfed areas for every country in the world. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2014-2017 time period to create a nominal 2015 product. Each LGRIP 30 meter resolution GeoTIFF file contains a contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation), irrigated cropland (cropland that had at least one irrigation during the crop growing period), non-cropland, and water bodies over a 10\u00b0 by 10\u00b0 area, as well as an accuracy assessment of the product. A low-resolution browse image is also available. ", - "license": "proprietary" - }, { "id": "LIDA", "title": "Lidar Data from Brazil", @@ -122849,6 +122771,32 @@ "description": "The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP) data set contains monthly 1.0-degree ocean-only estimates of cloud liquid water path (MACLWP_mean), total water path (MACTWP_mean) which includes both cloud and rain water, and monthly climatologies of cloud liquid water path diurnal cycle amplitudes and phases (MACLWP_diurnal). The MACTWP_mean field can also be used as a quality-control screen for the MACLWP_mean field as discussed in Elsaesser et al. (2017), where uncertainty increases as the ratio of cloud to total water path increases. The MAC-LWP algorithm uses as input the Remote Sensing Systems (RSS) Version 7 0.25 degree-resolution retrieval products (produced using the SSM/I, AMSR-E, TMI, AMSR-2, GMI, SSMIS, and WindSat satellite sensors), and performs a bias correction on all input RSS cloud water path products based on AMSR-E matchups to clear-sky MODIS scenes. The MAC-LWP algorithm ensures that spurious trends and variability in the cloud fields arising from drifting satellite overpass times are mitigated by simultaneously solving for the monthly average cloud and total water paths and monthly-mean diurnal cycles, as discussed in O’Dell et al. (2008). Additional details on the algorithm and data fields can be found in Elsaesser et al. (2017).", "license": "proprietary" }, + { + "id": "MAIA_ANC_SURFACEMONITOR_PM_2.5_SPECIES_C01", + "title": "Ancillary speciated PM data from the MAIA Surface Monitor Network", + "catalog": "LARC_ASDC STAC Catalog", + "state_date": "2021-01-01", + "end_date": "", + "bbox": "180, -90, -180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3271469628-LARC_ASDC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3271469628-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/MAIA_ANC_SURFACEMONITOR_PM_2.5_SPECIES_C01", + "description": "The MAIA Surface Monitor Stage 0 files are an ancillary dataset containing processed particulate matter (PM) measurements collected from a global in-situ surface monitoring network. The files are generated by the MAIA surface monitoring subsystem software at NASA\u2019s Atmospheric Science Data Center (ASDC).", + "license": "proprietary" + }, + { + "id": "MAIA_ANC_SURFACEMONITOR_PM_TOTAL_C01", + "title": "Ancillary total PM data from the MAIA Surface Monitor Network", + "catalog": "LARC_ASDC STAC Catalog", + "state_date": "2021-01-01", + "end_date": "", + "bbox": "180, -90, -180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3271469675-LARC_ASDC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3271469675-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/MAIA_ANC_SURFACEMONITOR_PM_TOTAL_C01", + "description": "The MAIA Surface Monitor Stage 0 files are an ancillary dataset containing processed particulate matter (PM) measurements collected from a global in-situ surface monitoring network. The files are generated by the MAIA surface monitoring subsystem software at NASA\u2019s Atmospheric Science Data Center (ASDC).", + "license": "proprietary" + }, { "id": "MALINA_0", "title": "Malina Oceanographic Expedition", @@ -126047,6 +125995,19 @@ "description": "This dataset contains the Global Mean Sea Level (GMSL) trend generated from the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.1. The GMSL trend is a 1-dimensional time series of globally averaged Sea Surface Height Anomalies (SSHA) from TOPEX/Poseidon, Jason-1, OSTM/Jason-2, and Jason-3 that covers September 1992 to present with a lag of up to 4 months. The data are reported as variations relative to a 20-year TOPEX/Jason collinear mean. Bias adjustments and cross-calibrations were applied to ensure SSHA data are consistent across the missions; Glacial Isostatic Adjustment (GIA) was also applied. The data are available as a table in ASCII format. Changes between the version 4.2 and version 5.x releases are described in detail in the user handbook.", "license": "proprietary" }, + { + "id": "MERIS_L1_FRS_4", + "title": "ENVISAT MERIS Level-1B Full Resolution, Full Swath (FRS) Data, version 4", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778834-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778834-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L1_FRS_4", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration.", + "license": "proprietary" + }, { "id": "MERIS_L1_FRS_4", "title": "ENVISAT MERIS Full Resolution, Full Swath (FRS) Data, version 4", @@ -126073,6 +126034,32 @@ "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration.", "license": "proprietary" }, + { + "id": "MERIS_L1_RR_4", + "title": "ENVISAT MERIS Level-1B Reduced Resolution (RR) Data, version 4", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778839-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778839-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L1_RR_4", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration.", + "license": "proprietary" + }, + { + "id": "MERIS_L2_FRS_IOP_2022.0", + "title": "ENVISAT MERIS Level-2 Regional Full Resolution, Full Swath (FRS) Inherent Optical Properties (IOP) Data, version 2022.0", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281901057-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281901057-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L2_FRS_IOP_2022.0", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L2_FRS_IOP_R2022.0", "title": "ENVISAT MERIS Regional Full Resolution, Full Swath (FRS) Inherent Optical Properties (IOP) Data, version R2022.0", @@ -126086,6 +126073,19 @@ "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. 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Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L3m_CHL_R2022.0", "title": "ENVISAT MERIS Global Mapped Chlorophyll (CHL) Data, version R2022.0", @@ -126307,6 +126450,19 @@ "description": "Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data. ", "license": "proprietary" }, + { + "id": "MERIS_L3m_FLH_2022.0", + "title": "ENVISAT MERIS Level-3 Global Mapped Fluorescence Line Height (FLH) Data, version 2022.0", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778906-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778906-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L3m_FLH_2022.0", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L3m_ILW_4", "title": "ENVISAT MERIS Regional Mapped Inland Waters (ILW) Data, version 4", @@ -126320,6 +126476,19 @@ "description": "The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.", "license": "proprietary" }, + { + "id": "MERIS_L3m_IOP_2022.0", + "title": "ENVISAT MERIS Level-3 Global Mapped Inherent Optical Properties (IOP) Data, version 2022.0", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778909-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778909-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L3m_IOP_2022.0", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L3m_IOP_R2022.0", "title": "ENVISAT MERIS Global Mapped Inherent Optical Properties (IOP) Data, version R2022.0", @@ -126333,6 +126502,19 @@ "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration.", "license": "proprietary" }, + { + "id": "MERIS_L3m_KD_2022.0", + "title": "ENVISAT MERIS Level-3 Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778916-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778916-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L3m_KD_2022.0", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L3m_KD_R2022.0", "title": "ENVISAT MERIS Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version R2022.0", @@ -126346,6 +126528,19 @@ "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration.", "license": "proprietary" }, + { + "id": "MERIS_L3m_PAR_2022.0", + "title": "ENVISAT MERIS Level-3 Global Mapped Photosynthetically Active Radiation (PAR) Data, version 2022.0", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778919-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778919-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L3m_PAR_2022.0", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L3m_PAR_R2022.0", "title": "ENVISAT MERIS Global Mapped Photosynthetically Available Radiation (PAR) Data, version R2022.0", @@ -126359,6 +126554,19 @@ "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration.", "license": "proprietary" }, + { + "id": "MERIS_L3m_PIC_2022.0", + "title": "ENVISAT MERIS Level-3 Global Mapped Particulate Inorganic Carbon (PIC) Data, version 2022.0", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778924-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778924-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L3m_PIC_2022.0", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L3m_PIC_R2022.0", "title": "ENVISAT MERIS Global Mapped Particulate Inorganic Carbon (PIC) Data, version R2022.0", @@ -126372,6 +126580,19 @@ "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration.", "license": "proprietary" }, + { + "id": "MERIS_L3m_POC_2022.0", + "title": "ENVISAT MERIS Level-3 Global Mapped Particulate Organic Carbon (POC) Data, version 2022.0", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778927-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778927-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L3m_POC_2022.0", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L3m_POC_R2022.0", "title": "ENVISAT MERIS Global Mapped Particulate Organic Carbon (POC) Data, version R2022.0", @@ -126385,6 +126606,19 @@ "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration.", "license": "proprietary" }, + { + "id": "MERIS_L3m_RRS_2022.0", + "title": "ENVISAT MERIS Level-3 Global Mapped Remote-Sensing Reflectance (RRS) Data, version 2022.0", + "catalog": "OB_CLOUD STAC Catalog", + "state_date": "2002-03-21", + "end_date": "2012-05-09", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778928-OB_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3281778928-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/MERIS_L3m_RRS_2022.0", + "description": "MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. ", + "license": "proprietary" + }, { "id": "MERIS_L3m_RRS_R2022.0", "title": "ENVISAT MERIS Global Mapped Remote-Sensing Reflectance (RRS) Data, version R2022.0", @@ -150409,19 +150643,6 @@ "description": "This Level-2G daily global gridded product OMAERUVG is based on the pixel level OMI Level-2 AERUV product OMAERUV. This Level-2G daily global gridded product OMAERUVG is based on the pixel level OMI Level-2 Aerosol product OMAERUV. OMAERUVG data product is a special Level-2 gridded product where pixel level products are binned into 0.25x0.25 degree global grids. It contains the data for all scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved without averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMAERUVG files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits mapped on the Global 0.25x0.25 deg Grids. The maximum file size for the OMAERUVG data product is about 50 Mbytes.", "license": "proprietary" }, - { - "id": "OMAERUV_003", - "title": "OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V003 NRT", - "catalog": "OMINRT STAC Catalog", - "state_date": "2004-07-15", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000120-OMINRT.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000120-OMINRT.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMAERUV_003", - "description": "The OMI/Aura level-2 near UV Aerosol data product 'OMAERUV', recently re-processed using an enhanced algorithm, is now released (April 2012) to the public. The data is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), http://disc.gsfc.nasa.gov/Aura/OMI/omaeruv_v003.shtml NASA Aura satellite sensors are tracking important atmospheric pollutants from space since its launch in July, 2004. The Ozone Monitoring Instrument(OMI), one of the four Aura satellite sensors with its 2600 km viewing swath width provides daily global measurements of four important US Environmental Protection Agency criteria pollutants (Tropospheric ozone, Nitrogen dioxide,Sulfur dioxide and Aerosols from biomass burning and industrial emissions, HCHO, BrO, OClO and surface UV irradiance. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). The Level-2 OMI Aerosol Product OMAERUV from the Aura-OMI is now available from NASAs GSFC Earth Sciences (GES) Data and Information Services Center (DISC) for public access. OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Absorption and Aerosol Extinction Optical Depths, and Single Scattering Albedo at three different wavelengths (354, 388 and 500 nm), Aerosol Index, and other ancillary and geolocation parameters, in the OMI field of view (13x24 km). Another standard OMI aerosol product is OMAERO, that is based on the KNMI multi-wavelength spectral fitting algorithm. OMAERUV files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 6 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A short OMAERUV Readme Document that includes brief algorithm description and currently known data quality issues is provided by the OMAERUV Algorithm lead (see http://disc.gsfc.nasa.gov/Aura/OMI/omaeruv_v003.shtml) For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . OMAERUV Data Groups and Parameters: The OMAERUV data file contains a swath which consists of two groups: Data fields: Total Aerosol Optical Depth (extinction optical depth) and Aerosol Absorption Optical Depths (at 354, 388 and 500 nm), Single Scattering Albedo, UV Aerosol Index, Visible Aerosol Index, and other intermediate and ancillary parameters (e.g. Estimates of Aerosol Total Extinction and Absorption Optical Depths and Single Scattering Albedo at five atmospheric levels, Aerosol Type, Aerosol Layer Height, Normalized Radiance, Lambert equivalent Reflectivity, Surface Albedo, Imaginary Component of Refractive Index) and Data Quality Flags. Geolocation Fields: Latitude, Longitude, Time(TAI93), Seconds, Solar Zenith Angles, Viewing Zenith Angles, Relative Azimuth Angle, Terrain Pressure, Ground Pixel Quality Flags. For the full set of Aura products available from the GES DISC, please see the link below. http://disc.sci.gsfc.nasa.gov/Aura/ Atmospheric Composition data from Aura and other satellite sensors can be ordered from the following sites: http://disc.sci.gsfc.nasa.gov/acdisc/ ", - "license": "proprietary" - }, { "id": "OMAERUV_003", "title": "OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V003 (OMAERUV) at GES DISC", @@ -150435,6 +150656,19 @@ "description": "The Aura Ozone Monitoring Instrument level-2 near UV Aerosol data product 'OMAERUV', recently re-processed using an enhanced algorithm, is now released (April 2012) to the public. The data are available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The shortname for this Level-2 near-UV Aerosol Product is OMAERUV_V003. The OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Absorption and Aerosol Extinction Optical Depths, and Single Scattering Albedo at three different wavelengths (354, 388 and 500 nm), Aerosol Index, and other ancillary and geolocation parameters, in the OMI field of view (13x24 km). The OMAERUV files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 6 Mbytes.", "license": "proprietary" }, + { + "id": "OMAERUV_003", + "title": "OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V003 NRT", + "catalog": "OMINRT STAC Catalog", + "state_date": "2004-07-15", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000120-OMINRT.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000120-OMINRT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMAERUV_003", + "description": "The OMI/Aura level-2 near UV Aerosol data product 'OMAERUV', recently re-processed using an enhanced algorithm, is now released (April 2012) to the public. The data is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), http://disc.gsfc.nasa.gov/Aura/OMI/omaeruv_v003.shtml NASA Aura satellite sensors are tracking important atmospheric pollutants from space since its launch in July, 2004. The Ozone Monitoring Instrument(OMI), one of the four Aura satellite sensors with its 2600 km viewing swath width provides daily global measurements of four important US Environmental Protection Agency criteria pollutants (Tropospheric ozone, Nitrogen dioxide,Sulfur dioxide and Aerosols from biomass burning and industrial emissions, HCHO, BrO, OClO and surface UV irradiance. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). The Level-2 OMI Aerosol Product OMAERUV from the Aura-OMI is now available from NASAs GSFC Earth Sciences (GES) Data and Information Services Center (DISC) for public access. OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Absorption and Aerosol Extinction Optical Depths, and Single Scattering Albedo at three different wavelengths (354, 388 and 500 nm), Aerosol Index, and other ancillary and geolocation parameters, in the OMI field of view (13x24 km). Another standard OMI aerosol product is OMAERO, that is based on the KNMI multi-wavelength spectral fitting algorithm. OMAERUV files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 6 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A short OMAERUV Readme Document that includes brief algorithm description and currently known data quality issues is provided by the OMAERUV Algorithm lead (see http://disc.gsfc.nasa.gov/Aura/OMI/omaeruv_v003.shtml) For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . OMAERUV Data Groups and Parameters: The OMAERUV data file contains a swath which consists of two groups: Data fields: Total Aerosol Optical Depth (extinction optical depth) and Aerosol Absorption Optical Depths (at 354, 388 and 500 nm), Single Scattering Albedo, UV Aerosol Index, Visible Aerosol Index, and other intermediate and ancillary parameters (e.g. Estimates of Aerosol Total Extinction and Absorption Optical Depths and Single Scattering Albedo at five atmospheric levels, Aerosol Type, Aerosol Layer Height, Normalized Radiance, Lambert equivalent Reflectivity, Surface Albedo, Imaginary Component of Refractive Index) and Data Quality Flags. Geolocation Fields: Latitude, Longitude, Time(TAI93), Seconds, Solar Zenith Angles, Viewing Zenith Angles, Relative Azimuth Angle, Terrain Pressure, Ground Pixel Quality Flags. For the full set of Aura products available from the GES DISC, please see the link below. http://disc.sci.gsfc.nasa.gov/Aura/ Atmospheric Composition data from Aura and other satellite sensors can be ordered from the following sites: http://disc.sci.gsfc.nasa.gov/acdisc/ ", + "license": "proprietary" + }, { "id": "OMAERUV_004", "title": "OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V004 (OMAERUV) at GES DISC", @@ -150552,19 +150786,6 @@ "description": "This Level-2G daily global gridded product OMCLDRRG is based on the pixel level OMI Level-2 CLDRR product OMCLDRR. This level-2G global cloud product (OMCLDRRG) provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The algorithm lead for the products OMCLDRR and OMCLDRRG is NASA OMI scientist Dr. Joanna Joinner. OMCLDRRG data product is a special Level-2G Gridded Global Product where pixel level data (OMCLDRR)are binned into 0.25x0.25 degree global grids. It contains the OMCLDRR data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved without Averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMCLDRRG data products are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each daily file contains data from the day lit portion of the orbits (~14 orbits). The average file size for the OMCLDRRG data product is about 75 Mbytes.", "license": "proprietary" }, - { - "id": "OMCLDRR_003", - "title": "OMI/Aura Effective Cloud Pressure and Fraction (Raman Scattering) 1-Orbit L2 Swath 13x24 km V003 (OMCLDRR) at GES DISC", - "catalog": "GES_DISC STAC Catalog", - "state_date": "2004-10-01", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966791-GES_DISC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966791-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/OMCLDRR_003", - "description": "The reprocessed Aura Ozone Monitoring Instrument (OMI) Version 003 Level 2 Cloud Data Product OMCLDRR is available to the public from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Aura OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product, OMCLDRR, provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner. The OMCLDRR files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes.", - "license": "proprietary" - }, { "id": "OMCLDRR_003", "title": "OMI/Aura Cloud Pressure and Fraction (Raman Scattering) 1-Orbit L2 Swath 13x24 km V003 NRT", @@ -150578,6 +150799,19 @@ "description": "The reprocessed Aura OMI Version 003 Level 2 Cloud Data Product OMCLDRR is made available (in April 2012) to the public from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). http://disc.gsfc.nasa.gov/Aura/OMI/omcldrr_v003.shtml ) Aura OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product (OMCLDRR) provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner. OMCLDRR files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml . A short OMCLDRR Readme Document that includes brief algorithm description and data quality is also provided by the OMCLDRR Algorithm lead. The Ozone Monitoring Instrument (OMI) was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products are archived at the NASA GES DISC. For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/instruments/omi/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMCLDRR data file contains one swath which consists of two groups: Data fields: Two Effective Cloud Fraction and two Cloud Top Pressures that are based on two different clear and cloudy scene reflectivity criteria, Chlorophyll Amount, Effective Reflectivity (394.1 micron), UV Aerosol Index (based on 360 and 388 nm), and many Auxiliary Algorithm Parameter and Quality Flags. Geolocation Fields: Latitude, Longitude, Time, Solar Zenith Angle, Viewing Zenith Angle, Relative Azimuth Angle, Terrain Height, and Ground Pixel Quality Flags. OMI Atmospheric data and documents are available from the following sites: http://disc.gsfc.nasa.gov/Aura/OMI/ http://mirador.gsfc.nasa.gov/", "license": "proprietary" }, + { + "id": "OMCLDRR_003", + "title": "OMI/Aura Effective Cloud Pressure and Fraction (Raman Scattering) 1-Orbit L2 Swath 13x24 km V003 (OMCLDRR) at GES DISC", + "catalog": "GES_DISC STAC Catalog", + "state_date": "2004-10-01", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966791-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966791-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/OMCLDRR_003", + "description": "The reprocessed Aura Ozone Monitoring Instrument (OMI) Version 003 Level 2 Cloud Data Product OMCLDRR is available to the public from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Aura OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product, OMCLDRR, provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner. The OMCLDRR files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes.", + "license": "proprietary" + }, { "id": "OMCLDRR_004", "title": "OMI/Aura Effective Cloud Pressure and Fraction (Raman Scattering) 1-Orbit L2 Swath 13x24 km V004 (OMCLDRR) at GES DISC", @@ -151631,19 +151865,6 @@ "description": "This Level-2G daily global gridded product OMTO3G is based on the pixel level OMI Level-2 Total Ozone Product OMTO3. The OMTO3 product is from the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. The OMTO3G data product is a special Level-2 Global Gridded Product where pixel level data are binned into 0.25x0.25 degree global grids. It contains the data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved Without Averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMTO3G data product contains almost all parameters that are contained in the OMTO3. For example, in addition to the total column ozone it also contains UV aerosol index, cloud fraction, cloud pressure, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The OMTO3G files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3G data product is about 150 Mbytes.", "license": "proprietary" }, - { - "id": "OMTO3_003", - "title": "OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT", - "catalog": "OMINRT STAC Catalog", - "state_date": "2004-07-15", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMTO3_003", - "description": "The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ .", - "license": "proprietary" - }, { "id": "OMTO3_003", "title": "OMI/Aura Ozone(O3) Total Column 1-Orbit L2 Swath 13x24 km V003 (OMTO3) at GES DISC", @@ -151657,6 +151878,19 @@ "description": "The Aura Ozone Monitoring Instrument (OMI) Level-2 Total Column Ozone Data Product OMTO3 (Version 003) is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. OMI provides two Level-2 (OMTO3 and OMDOAO3) total column ozone products at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms. This level-2 global total column ozone product (OMTO3) is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrievals (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3. The algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia. The OMTO3 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is approximately 35 MB.", "license": "proprietary" }, + { + "id": "OMTO3_003", + "title": "OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT", + "catalog": "OMINRT STAC Catalog", + "state_date": "2004-07-15", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMTO3_003", + "description": "The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ .", + "license": "proprietary" + }, { "id": "OMTO3_CPR_003", "title": "OMI/Aura Level 2 Ozone (O3) Total Column 1-Orbit Subset and Collocated Swath along CloudSat track 200-km wide at 13x24 km2 resolution", @@ -151683,19 +151917,6 @@ "description": "The OMI science team produces this Level-3 daily global TOMS-Like Total Column Ozone gridded product OMTO3d (1 deg Lat/Lon grids). The OMTO3d product is produced by gridding and averaging only good quality level-2 total column ozone orbital swath data (OMTO3, based on the enhanced TOMS version-8 algorithm) on the 1x1 degree global grids. The OMTO3d files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3d data product is about 0.65 Mbytes.", "license": "proprietary" }, - { - "id": "OMTO3e_003", - "title": "OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT", - "catalog": "OMINRT STAC Catalog", - "state_date": "2004-07-15", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMTO3e_003", - "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) .", - "license": "proprietary" - }, { "id": "OMTO3e_003", "title": "OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 1 day 0.25 degree x 0.25 degree V3 (OMTO3e) at GES DISC", @@ -151709,6 +151930,19 @@ "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. The OMTO3e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes.", "license": "proprietary" }, + { + "id": "OMTO3e_003", + "title": "OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT", + "catalog": "OMINRT STAC Catalog", + "state_date": "2004-07-15", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMTO3e_003", + "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) .", + "license": "proprietary" + }, { "id": "OMUANC_004", "title": "Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUANC) at GES DISC", @@ -167144,7 +167378,7 @@ "id": "SPL1BTB_NRT_105", "title": "Near Real-time SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V105", "catalog": "NSIDC_ECS STAC Catalog", - "state_date": "2024-10-09", + "state_date": "2024-10-17", "end_date": "", "bbox": "-180, -86.4, 180, 86.4", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2257958430-NSIDC_ECS.umm_json", @@ -167534,7 +167768,7 @@ "id": "SPL2SMP_NRT_107", "title": "Near Real-time SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V107", "catalog": "NSIDC_ECS STAC Catalog", - "state_date": "2024-10-09", + "state_date": "2024-10-17", "end_date": "", "bbox": "-180, -85.044, 180, 85.044", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2312096175-NSIDC_ECS.umm_json", @@ -168336,19 +168570,6 @@ "description": "The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is NASA-funded oceanographic process study and associated field program that aim to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. The project involves two field campaigns and a series of cruises in regions of the Atlantic and Pacific Oceans exhibiting salinity extremes. SPURS employs a suite of state-of-the-art in-situ sampling technologies that, combined with remotely sensed salinity fields from the Aquarius/SAC-D, SMAP and SMOS satellites, provide a detailed characterization of salinity structure over a continuum of spatio-temporal scales. The SPURS-2 campaign involved two month-long cruises by the R/V Revelle in August 2016 and October 2017 combined with complementary sampling on a more continuous basis over this period by the schooner Lady Amber. Focused around a central mooring located near 10N,125W, the objective of SPURS-2 was to study the dynamics of the rainfall-dominated surface ocean at the western edge of the eastern Pacific fresh pool subject to high seasonal variability and strong zonal flows associated with the North Equatorial Current and Countercurrent. Expendable bathythermograph (XBT) casts were undertaken at stations during both of the SPURS-2 R/V Revelle cruises. Launched off the side of the ship, XBT probes provide vertical profile measurements of the water column at fixed locations. There were a total of 25 and 11 XBT deployments made during the first and second R/V Revelle cruises respectively. There is one XBT data file per cruise, each containing the temperature profile data from all instrument deployments undertaken during that cruise.", "license": "proprietary" }, - { - "id": "SRB_REL3.0_SW_3HRLY_MONTHLY_UTC_NC_1", - "title": "Surface Radiation Budget (SRB) Release 3.0 Shortwave 3 hourly monthly UTC data in netcdf format", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1983-07-01", - "end_date": "2007-12-31", - "bbox": "180, -90, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2184128386-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2184128386-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/SRB_REL3.0_SW_3HRLY_MONTHLY_UTC_NC_1", - "description": "The data set contains monthly average/3-hourly (also calleddiurnally-resolved monthly average or just 'diurnal' for brevity) global fieldsof 11 shortwave (SW) surface radiative parameters derived with the Shortwavealgorithm of the NASA World Climate Research Programme /Global Energy andWater-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project.The data is generated using the Pinker/Laszlo shortwave algorithm (R.T. Pinkerand I. Laszlo, 1992: Modeling Surface Solar Irradiance for SatelliteApplications on a Global Scale, J. Appl. Met., 31, 194-211).These parameters were derived originally on a 3-hourly temporal resolution(i.e., a global instantaneous gridded field every 3 hours), at UT hours 00, 03,06, 09, 12, 15, 18, and 21 for every day of the month. The 3-hourly values wereused to compute monthly averages separately for each of the 8 UT hours. Thecurrent version of the data is identified as Release 3.0.", - "license": "proprietary" - }, { "id": "SRDB_V5_1827_5", "title": "A Global Database of Soil Respiration Data, Version 5.0", @@ -176396,19 +176617,6 @@ "description": "TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1 is the in situ collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data from the Multiple-Angle Spectrometer Probe (MASP), 2D-C Aerosol Probe, and FSSP Aerosol Size distributions are featured in this data product. Data collection is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", "license": "proprietary" }, - { - "id": "TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1", - "title": "Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 In Situ Aerosol Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-03", - "end_date": "1996-02-20", - "bbox": "180, -23.1, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736753162-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736753162-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1", - "description": "TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1 is the in situ collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data from the Multiple-Angle Spectrometer Probe (MASP), 2D-C Aerosol Probe, and FSSP Aerosol Size distributions are featured in this data product. Data collection is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, { "id": "TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1", "title": "Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Remotely Sensed Differential Absorption Lidar (DIAL) Data", @@ -176422,32 +176630,6 @@ "description": "TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1 is the remotely sensed Differential Absorption Lidar (DIAL) data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", "license": "proprietary" }, - { - "id": "TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1", - "title": "Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Remotely Sensed Differential Absorption Lidar (DIAL) Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-03", - "end_date": "1996-02-20", - "bbox": "180, -23.1, -180, 89.993", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736747109-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736747109-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1", - "description": "TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1 is the remotely sensed Differential Absorption Lidar (DIAL) data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, - { - "id": "TOTE-VOTE_AircraftRemoteSensing_DC8_Lidar_Data_1", - "title": "Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Remotely Sensed Lidar Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-03", - "end_date": "1996-02-20", - "bbox": "180, -10.68, -180, 89.993", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736752301-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736752301-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_AircraftRemoteSensing_DC8_Lidar_Data_1", - "description": "TOTE-VOTE_AircraftRemoteSensing_DC8_Lidar_Data_1 is the remotely sensed Raman Lidar data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Methane and water vapor data are featured in this dataset. Data collection is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, { "id": "TOTE-VOTE_AircraftRemoteSensing_DC8_Lidar_Data_1", "title": "Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Remotely Sensed Lidar Data", @@ -176474,32 +176656,6 @@ "description": "TOTE-VOTE_Analysis_DC8_Data_1 is the modeled meteorological data along the flight path for the DC-8 aircraft collected during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection for this product is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", "license": "proprietary" }, - { - "id": "TOTE-VOTE_Analysis_DC8_Data_1", - "title": "Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Analysis Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-03", - "end_date": "1996-02-20", - "bbox": "180, -23.1, -180, 89.993", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736731936-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736731936-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_Analysis_DC8_Data_1", - "description": "TOTE-VOTE_Analysis_DC8_Data_1 is the modeled meteorological data along the flight path for the DC-8 aircraft collected during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection for this product is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, - { - "id": "TOTE-VOTE_Ground_Data_1", - "title": "Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Ground Site Lidar Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-01", - "end_date": "1996-02-19", - "bbox": "-155.7, 19.5, -117.6, 34.4", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736718104-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736718104-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_Ground_Data_1", - "description": "TOTE-VOTE_Ground_Data_1 is the ground site data collected as part of the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data featured in the product includes data from the NASA GSFC Stratospheric Ozone Lidar Trailer Experiment (STROZ-LITE) at Mauna Loa, and the JPL Table Mountain Facility, Mauna Loa Lidar. Data collection for this product is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, { "id": "TOTE-VOTE_Ground_Data_1", "title": "Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Ground Site Lidar Data", @@ -176539,32 +176695,6 @@ "description": "TOTE-VOTE_Analysis_DC8_Data_1 is the ancillary datasets from the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. This dataset contains postscript files of datasets to support DC-8 aircraft measurements. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", "license": "proprietary" }, - { - "id": "TOTE-VOTE_Miscellaneous_DC8_Data_1", - "title": "Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Ancillary Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-03", - "end_date": "1996-02-20", - "bbox": "180, -23.1, -180, 89.993", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736739081-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736739081-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_Miscellaneous_DC8_Data_1", - "description": "TOTE-VOTE_Analysis_DC8_Data_1 is the ancillary datasets from the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. This dataset contains postscript files of datasets to support DC-8 aircraft measurements. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, - { - "id": "TOTE-VOTE_Satellite_Data_1", - "title": "Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Supplementary Satellite Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-03", - "end_date": "1996-02-19", - "bbox": "180, -90, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736712587-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736712587-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_Satellite_Data_1", - "description": "TOTE-VOTE_Satellite_Data_1 is the supplementary satellite data for the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data in this product includes GOES-7 infrared imagery and GOES-9 water vapor imagery. Data collection for this product is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, { "id": "TOTE-VOTE_Satellite_Data_1", "title": "Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Supplementary Satellite Data", @@ -176591,32 +176721,6 @@ "description": "TOTE-VOTE_Sondes_Data_1 is the radiosonde data collected during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection for this product is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", "license": "proprietary" }, - { - "id": "TOTE-VOTE_Sondes_Data_1", - "title": "Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Sonde Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-03", - "end_date": "1996-02-19", - "bbox": "179.22, -54.5, -180, 82.5", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736723318-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736723318-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_Sondes_Data_1", - "description": "TOTE-VOTE_Sondes_Data_1 is the radiosonde data collected during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection for this product is complete. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, - { - "id": "TOTE-VOTE_TraceGas_AircraftInSitu_DC8_Data_1", - "title": "Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 In Situ Trace Gas Data", - "catalog": "LARC_ASDC STAC Catalog", - "state_date": "1995-12-03", - "end_date": "1996-02-20", - "bbox": "180, -23.1, -180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736766511-LARC_ASDC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736766511-LARC_ASDC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/TOTE-VOTE_TraceGas_AircraftInSitu_DC8_Data_1", - "description": "TOTE-VOTE_TraceGas_AircraftInSitu_DC8_Data_1 is the in situ trace gas data collected onboard the DC-8 aircraft as part of the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collected by the DACOM, LICOR, and chemiluminescence are featured in this product. Data collection is completed. The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.", - "license": "proprietary" - }, { "id": "TOTE-VOTE_TraceGas_AircraftInSitu_DC8_Data_1", "title": "Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 In Situ Trace Gas Data", @@ -178632,6 +178736,19 @@ "description": "As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled \u201cMulti-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)\u201d will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2011), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats.", "license": "proprietary" }, + { + "id": "TROPOMI_SIF_Arctic_Ocean_2378_1", + "title": "Monthly SIF Estimates from TROPOMI over the Arctic Ocean, 2004-2020", + "catalog": "ORNL_CLOUD STAC Catalog", + "state_date": "2004-01-01", + "end_date": "2020-12-31", + "bbox": "-180, 50, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3282002388-ORNL_CLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3282002388-ORNL_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/TROPOMI_SIF_Arctic_Ocean_2378_1", + "description": "This dataset provides solar-induced chlorophyll fluorescence (SIF) estimates over the Arctic Ocean at a 0.05-degree resolution for each month from January 2004 through December 2020. Red SIF data from TROPOspheric Monitoring Instrument (TROPOMI) (2018 to 2021) were extended over the study period using a random forest machine learning model trained using TROPOMI SIF climatological records. These data are useful for monitoring the physiological responses of phytoplankton to ongoing climate change over this ocean region. The data are provided in cloud optimized GeoTIFF format.", + "license": "proprietary" + }, { "id": "TRPSCRAERNH42H2D_1", "title": "TROPESS Chemical Reanalysis Surface Aerosol NH4 2-Hourly 2-dimensional Product V1 (TRPSCRAERNH42H2D) at GES DISC", diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv index f9c447c..bd32013 100644 --- a/nasa_cmr_catalog.tsv +++ b/nasa_cmr_catalog.tsv @@ -2426,8 +2426,8 @@ ATL02_006 ATLAS/ICESat-2 L1B Converted Telemetry Data V006 NSIDC_CPRD STAC Catal ATL03_006 ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.umm_json This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03. proprietary ATL03_006 ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.umm_json This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03. proprietary ATL03_ANC_MASKS_1 ATLAS/ICESat-2 ATL03 Ancillary Masks, Version 1 NSIDCV0 STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2278879612-NSIDCV0.umm_json This ancillary ICESat-2 data set contains four static surface masks (land ice, sea ice, land, and ocean) provided by ATL03 to reduce the volume of data that each surface-specific along-track data product is required to process. For example, the land ice surface mask directs the ATL06 land ice algorithm to consider data from only those areas of interest to the land ice community. Similarly, the sea ice, land, and ocean masks direct ATL07, ATL08, and ATL12 algorithms, respectively. A detailed description of all four masks can be found in section 4 of the Algorithm Theoretical Basis Document (ATBD) for ATL03 linked under technical references. proprietary -ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary +ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL06_006 ATLAS/ICESat-2 L3A Land Ice Height V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2670138092-NSIDC_CPRD.umm_json This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL06_006 ATLAS/ICESat-2 L3A Land Ice Height V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2564427300-NSIDC_ECS.umm_json This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL07QL_006 ATLAS/ICESat-2 L3A Sea Ice Height Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548344839-NSIDC_ECS.umm_json ATL07QL is the quick look version of ATL07. Once final ATL07 files are available, the corresponding ATL07QL files will be removed. ATL07 contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary @@ -2440,8 +2440,8 @@ ATL09QL_006 ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric L ATL09_006 ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.umm_json This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL09_006 ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2607017115-NSIDC_ECS.umm_json This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL10QL_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2551529078-NSIDC_ECS.umm_json ATL10QL is the quick look version of ATL10. Once final ATL10 files are available the corresponding ATL10QL files will be removed. ATL10 contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary -ATL10_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.umm_json This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL10_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.umm_json This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary +ATL10_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.umm_json This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL11_006 ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2750966856-NSIDC_ECS.umm_json This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations. proprietary ATL11_006 ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2752556504-NSIDC_CPRD.umm_json This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations. proprietary ATL12_006 ATLAS/ICESat-2 L3A Ocean Surface Height V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2560378689-NSIDC_ECS.umm_json This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary @@ -2449,10 +2449,10 @@ ATL12_006 ATLAS/ICESat-2 L3A Ocean Surface Height V006 NSIDC_CPRD STAC Catalog 2 ATL13QL_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2650092501-NSIDC_ECS.umm_json ATL13QL is the quick look version of ATL13. Once final ATL13 files are available the corresponding ATL13QL files will be removed. ATL13 contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7 km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary ATL13_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2650116584-NSIDC_ECS.umm_json This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary ATL13_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2684928243-NSIDC_CPRD.umm_json This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary -ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary -ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary +ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_ECS STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary +ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary ATL15_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL15_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464171-NSIDC_ECS.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL15_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162334027-NSIDC_CPRD.umm_json This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary @@ -2461,12 +2461,12 @@ ATL16_005 ATLAS/ICESat-2 L3B Weekly Gridded Atmosphere V005 NSIDC_ECS STAC Catal ATL16_005 ATLAS/ICESat-2 L3B Weekly Gridded Atmosphere V005 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2769337070-NSIDC_CPRD.umm_json This product reports weekly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency. proprietary ATL17_005 ATLAS/ICESat-2 L3B Monthly Gridded Atmosphere V005 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2737997483-NSIDC_ECS.umm_json This data set contains a gridded summary of monthly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency. proprietary ATL17_005 ATLAS/ICESat-2 L3B Monthly Gridded Atmosphere V005 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2769338020-NSIDC_CPRD.umm_json This data set contains a gridded summary of monthly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency. proprietary -ATL19_003 ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003 NSIDC_ECS STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2746899536-NSIDC_ECS.umm_json This data set contains monthly gridded dynamic ocean topography (DOT), derived from along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided in this data set. Both single beam and all-beam gridded averages are available in this data set. Single beam averages are useful to identify biases among the beams and the all-beam averages are advised to use for physical oceanography. proprietary ATL19_003 ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2754956786-NSIDC_CPRD.umm_json This data set contains monthly gridded dynamic ocean topography (DOT), derived from along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided in this data set. Both single beam and all-beam gridded averages are available in this data set. Single beam averages are useful to identify biases among the beams and the all-beam averages are advised to use for physical oceanography. proprietary +ATL19_003 ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003 NSIDC_ECS STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2746899536-NSIDC_ECS.umm_json This data set contains monthly gridded dynamic ocean topography (DOT), derived from along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided in this data set. Both single beam and all-beam gridded averages are available in this data set. Single beam averages are useful to identify biases among the beams and the all-beam averages are advised to use for physical oceanography. proprietary ATL20_004 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2753295020-NSIDC_CPRD.umm_json ATL20 contains daily and monthly gridded estimates of sea ice freeboard, derived from along-track freeboard estimates in the ATLAS/ICESat-2 L3A Sea Ice Freeboard product (ATL10). Data are gridded at 25 km using the SSM/I Polar Stereographic Projection. proprietary ATL20_004 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2666857908-NSIDC_ECS.umm_json ATL20 contains daily and monthly gridded estimates of sea ice freeboard, derived from along-track freeboard estimates in the ATLAS/ICESat-2 L3A Sea Ice Freeboard product (ATL10). Data are gridded at 25 km using the SSM/I Polar Stereographic Projection. proprietary -ATL21_003 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids. proprietary ATL21_003 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.umm_json ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids. proprietary +ATL21_003 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids. proprietary ATL22_003 ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers. proprietary ATL22_003 ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers. proprietary ATL23_001 ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001 NSIDC_ECS STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.umm_json This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates. proprietary @@ -3180,12 +3180,9 @@ CAL_LID_L15-Standard-V1-01_V1-01 CALIPSO Lidar Level 1.5 Profile, V1-01 LARC_ASD CAL_LID_L2_01kmCLay-Standard-V4-20_V4-20 CALIPSO Lidar Level 2 1 km Cloud Layer, V4-20 LARC_ASDC STAC Catalog 2006-06-12 2020-07-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1556717898-LARC_ASDC.umm_json CAL_LID_L2_01kmCLay-Standard-V4-20 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 1 km Cloud Layer, Version 4-20 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Data generation and distribution of this V4.20 product ended on July 1, 2020, to support a change in the operating system of the CALIPSO production clusters. The V4.21 data product covers July 1, 2020, to January 19, 2020. CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National D’Etudes Spatiales). proprietary CAL_LID_L2_01kmCLay-Standard-V4-21_V4-21 CALIPSO Lidar Level 2 1 km Cloud Layer, V4-21 LARC_ASDC STAC Catalog 2020-07-01 2022-01-19 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1982418888-LARC_ASDC.umm_json CAL_LID_L2_01kmCLay-Standard-V4-21 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 1 km Cloud Layer, Version 4.21 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Data collection for this product is ongoing. The version of this product was changed from 4.20 to 4.21 to account for a change in the operating system of the CALIPSO production cluster. Data collection for this product is complete. CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre national d'études spatiales). proprietary CAL_LID_L2_01kmCLay-Standard-V4-51_V4-51 CALIPSO Lidar Level 2 1 km Cloud Layer, V4-51 LARC_ASDC STAC Catalog 2006-06-11 2023-06-30 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2667982883-LARC_ASDC.umm_json CAL_LID_L2_01kmCLay-Standard-V4-51 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 1 km Cloud Layer, Version 4-51 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Within this layer product are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products contain column descriptors associated with several layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. From June 13, 2006, to September 13, 2018, CALIPSO was part of the A-Train constellation for coincident Earth Observations. After September 13, 2018, the satellite was lowered from 705 to 688 km to resume flying in formation with CloudSat, called the C-Train. proprietary -CAL_LID_L2_05kmALay-Prov-V3-02_V3-02 CALIPSO Lidar Level 2 5km Aerosol Layer data, Provisional V3-02 LARC_ASDC STAC Catalog 2011-11-01 2013-03-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1522935473-LARC_ASDC.umm_json CAL_LID_L2_05kmALay-Prov-V3-02 data are Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5km aerosol layer data. Within the Lidar Aerosol Layer Product there are two general classes of data:- Column Properties (including position data and viewing geometry)- Layer Properties. The lidar layer products consist of a sequence of column descriptors, each one of which is associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. Version 3.02 represents a transition of the Lidar, IIR, and WFC processing and browse code to a new cluster computing system. No algorithm changes were introduced and very minor changes were observed between V3.01 and V3.02 as a result of the compiler and computer architecture differences. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in formation in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. proprietary -CAL_LID_L2_05kmALay-Prov-V3-30_V3-30 CALIPSO Lidar Level 2 5km Aerosol Layer data, Provisional V3-30 LARC_ASDC STAC Catalog 2013-03-01 2016-12-08 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1523564910-LARC_ASDC.umm_json CAL_LID_L2_05kmALay-Prov-V3-30 data are Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5km aerosol layer data, Provisional Version 3-30. Data collection for this product is complete. Within the Lidar Aerosol Layer Product there are two general classes of data:- Column Properties (including position data and viewing geometry)- Layer Properties. The lidar layer products consist of a sequence of column descriptors, each one of which is associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The science algorithms used to produce the V3.30 CALIOP data products are identical to those used to generate the V3.01 and V3.02 products; however, some of the ancillary data used in the V3.30 analyses is different. All CALIOP data products rely on meteorological data provided by NASA's Global Modeling and Assimilation Office (GMAO). The V3.01 and V3.02 data products were produced using the GMAO's GEOS 5.2 data products. CALIPSO was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite is comprised of three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. proprietary CAL_LID_L2_05kmALay-Standard-V4-20_V4-20 CALIPSO Lidar Level 2 5 km Aerosol Layer Data, V4-20 LARC_ASDC STAC Catalog 2006-06-12 2020-07-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1556717897-LARC_ASDC.umm_json CAL_LID_L2_05kmALay-Standard-V4-20 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5 km Aerosol Layer Data, Version 4-20 data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Data generation and distribution of this V4.20 product ended on July 1, 2020, to support a change in the operating system of the CALIPSO production clusters. The V4.21 data product covers July 1, 2020, to July 1, 2023. Within the Lidar Aerosol Layer Product, there are two general classes of data:- Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each one of which is associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. CALIPSO was launched on April 28, 2006, and continues to collect data necessary to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National D’Etudes Spatiales). proprietary CAL_LID_L2_05kmALay-Standard-V4-21_V4-21 CALIPSO Lidar Level 2 5 km Aerosol Layer Data, V4-21 LARC_ASDC STAC Catalog 2020-07-01 2022-01-19 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1978623212-LARC_ASDC.umm_json CAL_LID_L2_05kmALay-Standard-V4-21 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5 km Aerosol Layer Data, Version 4-21 data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The version of this product was changed from 4-20 to 4-21 to account for a change in the operating system of the CALIPSO production cluster. Data collection for this product is complete. Within the Lidar Aerosol Layer Product, there are two general classes of data:- Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. CALIPSO was launched on April 28, 2006, and continues to collect data necessary to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre national d'études spatiales). proprietary CAL_LID_L2_05kmALay-Standard-V4-51_V4-51 CALIPSO Lidar Level 2 5 km Aerosol Layer Data, V4-51 LARC_ASDC STAC Catalog 2006-06-11 2023-06-30 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2667982885-LARC_ASDC.umm_json CAL_LID_L2_05kmALay-Standard-V4-51 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5 km Aerosol Layer Data, Version 4-51 data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Within this layer product are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre national d'études spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. From June 13, 2006, to September 13, 2018, CALIPSO was part of the A-Train constellation for coincident Earth Observations. After September 13, 2018, the satellite was lowered from 705 to 688 km to resume flying in formation with CloudSat, called the C-Train. proprietary -CAL_LID_L2_05kmAPro-Prov-V3-02_V3-02 CALIPSO Lidar Level 2 5km Aerosol Profile data, Provisional V3-02 LARC_ASDC STAC Catalog 2011-11-01 2013-03-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1522937252-LARC_ASDC.umm_json CAL_LID_L2_05kmAPro-Prov-V3-02 data are Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 aerosol profile data using the CALIPSO Lidar Ratio selection algorithm. The Lidar Level 2 Aerosol Profile data products contain averaged aerosol profile data and ancillary data. There are no layer descriptors included in the lidar aerosol profile data products. The spatial distribution of the aerosol layers is instead completely characterized by the aerosol layer fraction and atmospheric volume description parameters. The aerosol profile products are generated at a uniform horizontal resolution of 5 km. The aerosol backscatter and extinction coefficients are computed using a lidar ratio selected by the CALIPSO Lidar Ratio selection algorithm. Version 3.02 represents a transition of the Lidar, IIR, and WFC processing and browse code to a new cluster computing system. No algorithm changes were introduced and very minor changes were observed between V3.01 and V3.02 as a result of the compiler and computer architecture differences. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. proprietary CAL_LID_L2_05kmAPro-Standard-V4-20_V4-20 CALIPSO Lidar Level 2 Aerosol Profile, V4-20 LARC_ASDC STAC Catalog 2006-06-12 2020-07-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1556717902-LARC_ASDC.umm_json CAL_LID_L2_05kmAPro-Standard-V4-20 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 Aerosol Profile, Version 4-20 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Data generation and distribution of this V4.20 product ended on July 1, 2020, to support a change in the operating system of the CALIPSO production clusters. The V4.21 data product covers July 1, 2020, to June 30, 2023. CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National D’Etudes Spatiales). proprietary CAL_LID_L2_05kmAPro-Standard-V4-21_V4-21 CALIPSO Lidar Level 2 Aerosol Profile, V4-21 LARC_ASDC STAC Catalog 2020-07-01 2022-01-19 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1978623316-LARC_ASDC.umm_json CAL_LID_L2_05kmAPro-Standard-V4-21 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 Aerosol Profile, Version 4-21 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The version of this product was changed from 4-20 to 4-21 to account for a change in the operating system of the CALIPSO production cluster. Data collection for this product is ongoing. CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). proprietary CAL_LID_L2_05kmAPro-Standard-V4-51_V4-51 CALIPSO Lidar Level 2 Aerosol Profile, V4-51 LARC_ASDC STAC Catalog 2006-06-11 2023-06-30 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2667982873-LARC_ASDC.umm_json CAL_LID_L2_05kmAPro-Standard-V4-51 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 Aerosol Profile, Version 4-51 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. From June 13, 2006, to September 13, 2018, CALIPSO was part of the A-Train constellation for coincident Earth Observations. After September 13, 2018, the satellite was lowered from 705 to 688 km to resume flying in formation with CloudSat, heretofore called the C-Train. proprietary @@ -3198,7 +3195,6 @@ CAL_LID_L2_05kmCPro-Standard-V4-51_V4-51 CALIPSO Lidar Level 2 Cloud Profile, V4 CAL_LID_L2_05kmMLay-Standard-V4-20_V4-20 CALIPSO Lidar Level 2 5 km Merged Layer, V4-20 LARC_ASDC STAC Catalog 2006-06-12 2020-07-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1602408375-LARC_ASDC.umm_json CAL_LID_L2_05kmMLay-Standard-V4-20 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 5 km Merged Layer, Version 4-20 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Data generation and distribution of this V4.20 product ended on July 1, 2020, to support a change in the operating system of the CALIPSO production clusters. The V4.21 data product covers July 1, 2020, to June 30, 2023. CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National D'Etudes Spatiales). proprietary CAL_LID_L2_05kmMLay-Standard-V4-21_V4-21 CALIPSO Lidar Level 2 5 km Merged Layer, V4-21 LARC_ASDC STAC Catalog 2020-07-01 2022-01-19 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1978623937-LARC_ASDC.umm_json CAL_LID_L2_05kmMLay-Standard-V4-21 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 5 km Merged Layer, Version 4-21 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The version of this product was changed from 4-20 to 4-21 to account for a change in the operating system of the CALIPSO production cluster. CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). proprietary CAL_LID_L2_05kmMLay-Standard-V4-51_V4-51 CALIPSO Lidar Level 2 5 km Merged Layer, V4-51 LARC_ASDC STAC Catalog 2006-06-11 2023-06-30 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2667982879-LARC_ASDC.umm_json CAL_LID_L2_05kmMLay-Standard-V4-51 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 5 km Merged (cloud + aerosol) Layer Data, Version 4-51 data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Within this layer product are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. From June 13, 2006, to September 13, 2018, CALIPSO was part of the A-Train constellation for coincident Earth Observations. After September 13, 2018, the satellite was lowered from 705 to 688 km to resume flying in formation with CloudSat, called the C-Train. proprietary -CAL_LID_L2_333mCLay-ValStage1-V3-30_V3-30 CALIPSO Lidar Level 2 1/3km Cloud Layer data, Validated Stage 1 V3-30 LARC_ASDC STAC Catalog 2013-03-01 2016-12-08 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1523234283-LARC_ASDC.umm_json CAL_LID_L2_333mCLay-ValStage1-V3-30 data are Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 1/3km (333m) cloud layer data, Validated Stage 1 Version 3-30. Data collection for this product is complete. Within the Lidar Cloud Layer Product there are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each one of which is associated with a variable number of layer descriptors. The column descriptors specify the temporal and geo-physical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., cloud and/or aerosol layers) identified within the column. For each feature within a column, a set of layer descriptors is reported. The layer descriptors provide information about the spatial and optical characteristics of a feature, such as base and top altitudes, integrated attenuated backscatter, and optical depth. New parameters for the V3-01 product include column optical depths, layer top pressure, layer base pressure, layer mid-point pressure, layer top temperature, and layer base temperature. The science algorithms used to produce the V3.30 Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) data products are identical to those used to generate the V3.01 and V3.02 products; however, some of the ancillary data used in the V3.30 analyses are different. All CALIOP data products rely on meteorological data provided by NASA's Global Modeling and Assimilation Office (GMAO). The V3.01 and V3.02 data products were produced using the GMAO's GEOS 5.2 data products. CALIPSO was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite is comprised of three instruments, CALIOP, the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. proprietary CAL_LID_L2_333mMLay-Standard-V4-20_V4-20 CALIPSO Lidar Level 2 1/3 km Merged Layer, V4-20 LARC_ASDC STAC Catalog 2006-06-12 2020-07-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1556717901-LARC_ASDC.umm_json CAL_LID_L2_333mMLay-Standard-V4-20 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 1/3 km Merged Layer, Version 4-20 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Data generation and distribution of this V4.20 product ended on July 1, 2020, to support a change in the operating system of the CALIPSO production clusters. The V4.21 data product covers July 1, 2020, to current. CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National D'Etudes Spatiales). proprietary CAL_LID_L2_333mMLay-Standard-V4-21_V4-21 CALIPSO Lidar Level 2 1/3 km Merged Layer, V4-21 LARC_ASDC STAC Catalog 2020-07-01 2022-01-19 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1978624018-LARC_ASDC.umm_json CAL_LID_L2_333mMLay-Standard-V4-21 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 2 1/3 km Merged Layer, Version 4-21 data product. Data for this product was collected using the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The version of this product was changed from 4-20 to 4-21 to account for a change in the operating system of the CALIPSO production cluster. Data collection for this product is ongoing. CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). proprietary CAL_LID_L2_333mMLay-Standard-V4-51_V4-51 CALIPSO Lidar Level 2 1/3 km Merged Layer, V4-51 LARC_ASDC STAC Catalog 2006-06-11 2023-06-30 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2667982891-LARC_ASDC.umm_json CAL_LID_L2_333mMLay-Standard-V4-51 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 333 m Merged (cloud + aerosol) Layer Data, Version 4-51 data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Within this layer product are two general classes of data: Column Properties (including position data and viewing geometry) and Layer Properties. The lidar layer products consist of a sequence of column descriptors, each associated with a variable number of layer descriptors. The column descriptors specify the temporal and geophysical location of the column of the atmosphere through which a given lidar pulse travels. Also included in the column descriptors are indicators of surface lighting conditions, information about the surface type, and the number of features (e.g., aerosol layers) identified within the column. The CALIPSO satellite comprises three instruments: CALIOP, Imaging Infrared Radiometer (IIR), and Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. From June 13, 2006, to September 13, 2018, CALIPSO was part of the A-Train constellation for coincident Earth Observations. After September 13, 2018, the satellite was lowered from 705 to 688 km to resume flying in formation with CloudSat, called the C-Train. proprietary @@ -3752,7 +3748,6 @@ CER_ES8_Terra-FM1_Edition4 CERES ERBE-like Instantaneous TOA Estimates Terra FM1 CER_ES8_Terra-FM2_Edition4 CERES ERBE-like Instantaneous TOA Estimates Terra FM2 Edition4 LARC_ASDC STAC Catalog 2000-02-29 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1419931602-LARC_ASDC.umm_json "CER_ES8_Terra-FM2_Edition4 is the Clouds and the Earth's Radiant Energy System (CERES) Earth Radiation Budget Experiment (ERBE)-like Instantaneous Top-of-the-Atmosphere (TOA) Estimates Terra Flight Model 2 (FM2) Edition 4 data product, which was collected using the CERES-FM2 instrument on the Terra platform. Data collection for this product is ongoing. The ERBE-like Footprint TOA Fluxes (ES-8) product contains 24 hours of instantaneous CERES data for a single scanner instrument, FM3, on the Aqua spacecraft. The ES-8 contains filtered radiances recorded every 0.01-second for the total (TOT), shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW and LW radiances at spacecraft altitude are converted to TOA fluxes with a scene identification algorithm and Angular Distribution Models (ADMs), which are ""like"" those used for the ERBE. The TOA fluxes, scene identification, and angular geometry are included in the ES-8. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions are a follow-on to the successful ERBE mission. The first CERES instrument, the protoflight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017." proprietary CER_ES9_Aqua-Xtrk_Edition4 CERES ERBE-like Gridded Instantaneous TOA Fluxes Aqua Crosstrack Edition4 LARC_ASDC STAC Catalog 2002-07-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1442085839-LARC_ASDC.umm_json "CER_ES9_Aqua-Xtrk_Edition4 is the Clouds and the Earth's Radiant Energy System (CERES) Earth Radiation Budget Experiment (ERBE)-like Gridded Instantaneous Top-of-the-Atmosphere (TOA) Fluxes Aqua Cross-track Edition 4 data product, which was collected using the CERES-Flight Model (FM3) and FM4 instruments on the Aqua platform. Data collection for this product is ongoing. The ERBE-like Monthly Regional Averages (ES-9) products contain a month of space and time-averaged CERES data for a single satellite using measurements from the primary cross-track instrument. All instantaneous shortwave and longwave fluxes at the TOA from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9, along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is ""like"" the algorithm used for ERBE. ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions are a follow-on to the successful ERBE mission. The first CERES instrument, the protoflight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017." proprietary CER_ES9_NOAA20-FM6_Edition1 CERES ERBE-like Monthly Regional Averages NOAA-20 FM6 Edition1 LARC_ASDC STAC Catalog 2018-05-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2246001698-LARC_ASDC.umm_json CER_ES9_NOAA20-FM6_Edition1, CERES ERBE-like Monthly Regional Averages NOAA-20 FM6 Edition 1, contains TOA fluxes from the Clouds and the Earth's Radiant Energy System (CERES) instrument using algorithms identical to those used by ERBE, regional averages of instantaneous footprint TOA fluxes only for the hours of satellite overpass (from ES-8 Level 2 product). The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time-averaged CERES data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9, along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is like the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. T The CERES instrument (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The last CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite on November 18, 2017. proprietary -CER_ES9_NPP-FM5_Edition1-CV CERES ERBE-like Monthly Regional Averages NPP FM5 Edition1-CV LARC_ASDC STAC Catalog 2012-02-01 2019-10-31 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C7057070-LARC_ASDC.umm_json CER_ES9_NPP-FM5_Edition1-CV is the Clouds and the Earth's Radiant Energy System (CERES) Earth Radiation Budget Experiment (ERBE)-like Monthly Regional Averages from the Suomi National Polar-orbiting Partnership (NPP), CERES Flight Model 5 (CERES-FM5) Edition1-CV data product. Data for this product is collected by way of the CERES-FM5 instrument on the Suomi-NPP platform. Data collection for this product is complete. Note: Edition1-CV data are for instrument validation purposes only and not suited for science publications. CER_ES9_NPP-FM5_Edition1-CV data are CERES instrument Top-of-the-Atmosphere (TOA) fluxes using algorithms identical to those used by ERBE, regional averages of instantaneous footprint TOA fluxes only for the hours of satellite overpass (from ES-8 Level 2 product). Edition1-CV data are for instrument validation purposes only and not suited for science publications.The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave (SW) and long-wave (LW) fluxes at the TOA from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is like the algorithm used for ERBE. The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. CERES is a key component of the Earth Observing System (EOS) program. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions are a follow-on to the successful ERBE mission. The first CERES instrument, protoflight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017. proprietary CER_ES9_NPP-FM5_Edition2 CERES ERBE-like Gridded Instantaneous TOA Fluxes (ES9) NPP CERES FM-5 Edition2 LARC_ASDC STAC Catalog 2012-02-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2246001720-LARC_ASDC.umm_json "The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time-averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single satellite using measurements from the primary cross-track instrument. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9, along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is ""like"" the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. The CERES instrument (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The last CERES instrument (FM6) was launched on board the Joint Polar Satellite System 1 (JPSS-1) satellite on November 18, 2017." proprietary CER_ES9_TRMM-PFM_Edition2 CERES ERBE-like Monthly Regional Averages TRMM PFM Edition2 LARC_ASDC STAC Catalog 1998-01-01 2000-03-31 180, -55, -180, 55 https://cmr.earthdata.nasa.gov/search/concepts/C7747951-LARC_ASDC.umm_json CER_ES9_TRMM-PFM_Edition2 is the Clouds and the Earth's Radiant Energy System (CERES) Earth Radiation Budget Experiment (ERBE)-like Monthly Regional Averages Tropical Rainfall Measuring Mission (TRMM) proto flight model (PFM) Edition 2 data product. Data for this product was collected by the CERES-PFM on the Tropical Rainfall Measuring Mission (TRMM) platform. Data collection for this product is complete. CER_ES9_TRMM-PFM_Edition2 data are CERES instrument Top-of-the-Atmosphere (TOA) fluxes that used algorithms identical to those used by ERBE, regional averages of instantaneous footprint TOA fluxes only for the hours of satellite overpass (from ES-8 Level 2 product). The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time-averaged CERES data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous short-wave and long-wave (LW) fluxes at the TOA from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9, along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is like the algorithm used for the ERBE. The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions are a follow-on to the successful ERBE mission. The first CERES instrument, PFM, was launched on November 27, 1997, as part of the TRMM. Two CERES instruments (FM1 and FM2) were launched into polar orbit onboard the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched onboard Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched onboard the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched onboard the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017. proprietary CER_ES9_Terra+Aqua_Edition4 CERES ERBE-like Gridded Instantaneous TOA Fluxes Terra and Aqua Cross-track Edition4 LARC_ASDC STAC Catalog 2002-07-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1443536139-LARC_ASDC.umm_json "CER_ES9_Terra+Aqua_Edition4 is the Clouds and the Earth's Radiant Energy System (CERES) Earth Radiation Budget Experiment (ERBE)-like Gridded Instantaneous Top-of-the-Atmosphere (TOA) Fluxes Terra and Aqua Cross-track Edition4 data product. Data for this product is collected through the CERES-Flight Model 1 (FM1) and FM2 on the Terra platform and FM3 and FM4 on the Aqua platform. Data collection for this product is ongoing. The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time-averaged CERES data for both the Terra and Aqua satellites using measurements from the primary cross-track instrument. All instantaneous shortwave and longwave (LW) fluxes at the TOA from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9, along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is ""like"" the algorithm used for ERBE. ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions are a follow-on to the successful ERBE mission. The first CERES instrument, the proto flight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit onboard the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched onboard Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched onboard the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched onboard the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017." proprietary @@ -4537,7 +4532,6 @@ DEVOTE_MetNav_AircraftInSitu_B200_Data_1 DEVOTE B-200 Aircraft In-Situ Meteorolo DEVOTE_MetNav_AircraftInSitu_UC12_Data_1 DEVOTE UC-12 Aircraft In-Situ Meteorological and Navigational Data LARC_ASDC STAC Catalog 2011-09-28 2011-10-27 -97, 25, -65, 50 https://cmr.earthdata.nasa.gov/search/concepts/C2179058091-LARC_ASDC.umm_json DEVOTE_MetNav_AircraftInSitu_UC12_Data are in-situ meteorological and navigational data collected onboard the UC-12 aircraft as part of the Development and Evaluation of satellite Validation Tools by Experimenters (DEVOTE) sub-orbital project. Data from the Applanix POSAV is included in this product. Data collection is complete. The Development and Evaluation of satellite Validation Tools by Experimenters (DEVOTE) project investigated aerosols and clouds with the specific goals of satellite validation and the improvement of satellite data retrieval algorithms. Conducted in September and October 2011, DEVOTE scientists collected measurements of aerosols and cloud optical and microphysical properties using airborne sensors over ground sites and along satellite overpasses to demonstrate the use of airborne platforms in future scientific measurement campaigns. These measurements were used to validate and improve satellite data retrieval algorithms from missions including the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission and the Aerosol, Cloud, Ecosystems (ACE) Decadal Survey mission. DEVOTE scientists conducted eleven science flights based at the NASA Langley Research Center throughout the campaign. The flight plans were specifically designed to coordinate with CALIPSO satellite overpasses and to fly over the Aerosol Robotic Network (AERONET) ground network sites. The DEVOTE sampling strategy required two aircraft dedicated to remote sensing and in-situ observations, which flew in coordinated flight patterns. This was implemented through use of the NASA UC-12 and the NASA B-200 airborne platforms. The UC-12 had the following remote sensing payload: the Research Scanning Polarimeter (RSP) and High Spectral Resolution Lidar (HSRL) instruments. The B-200 had an in-situ payload including the Polarized Imaging Nephelometer (PI-Neph), the Diode Laser Hygrometer (DLH), and Langley Aerosol Research Group Experiment (LARGE) instruments for aerosol microphysical and optical properties. DEVOTE was partly funded through the Hands-On Project Experience (HOPE) initiative. HOPE was a NASA development program designed to offer early career scientist opportunities to design, implement, and analyze small missions offering hands-on experience. Opportunities are increasingly limited for principal investigators, program managers, and system engineers to obtain mission life cycle training, and HOPE provides opportunities to those early on in their career or who are transitioning to a different field. Thus, DEVOTE had a focus on providing hands-on training in the mission life cycle to early career scientists in addition to its primary objective of using cloud and aerosol data collected from airborne sensors to validate and improve satellite data retrieval algorithms. Additionally, the information obtained from DEVOTE research was used to prepare for the implementation of ACE. proprietary DFO_Canada_Time_Series_0 Chlorophyll time series, Department of Fisheries and Oceans (DFO), Canada OB_DAAC STAC Catalog 2000-04-06 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360201-OB_DAAC.umm_json This time series of chl data was obtained from the BioChem archive run by the Department of Fisheries and Oceans, Canada. Water sampling and chlorophyll analysis methods are described in the Mitchell et al. (2002) protocol document accompanying the data.DFO (2014). BioChem: database of biological and chemical oceanographic data. Department of Fisheries and Oceans, Canada.http://isdm.gc.ca/biochem/biochem-eng.htm proprietary DGT-Heavymetals-Casey03-04_1 Concentration of heavy metals in marine waters around Casey station - summer 2003/04 AU_AADC STAC Catalog 2003-12-01 2004-02-19 110.5276, -66.2818, 110.5276, -66.2818 https://cmr.earthdata.nasa.gov/search/concepts/C1214308531-AU_AADC.umm_json The concentration of heavy metals in seawater at four sites around Casey was determined via Diffusive Gradients in Thin films (DGT) loggers attached to experimental mesocosms suspended below the sea ice. Data are the concentration of heavy metals in micrograms per litre (ug/l), equivalent to parts per billion (ppb)/litre Two loggers were attached to each mesocosm (perforated 20 litre food buckets) at each site; one at the top and one at the bottom of each mesocosm. Mesocosms were suspended two to three metres below the bottom edge of the sea ice through a 1 metre diameter hole and were periodically raised to the surface for short periods (~1 hour). This experiment was part of the short-term biomonitoring program for the Thala Valley Tip Clean-up at Casey during summer 2003/04. During Runs 1 and 2 of the experiment mesocosms were deployed at Brown Bay Inner (S66 16.811 E110 32.475), Brown Bay Outer (S66 16.811 E110 32.526), McGrady Cove (S66 16.556 E110 34.392) and O'Brien Bay 1 (S66 18.730 E110 30.810). In Run 3 mesocosm were deployed in open water with no sea ice covering at Brown Bay Inner (S66 16.807 E110 32.556), Brown Bay Outer (S66 16.805 E110 32.607), McGrady Cove (S66 16.520 E110 34.257) and O'Brien Bay (S66 17.607 E110 31.247). These data were collected as part of ASAC project 2201 (ASAC_2201 - Natural variability and human induced change in Antarctic nearshore marine benthic communities). See also other metadata records by Glenn Johnstone for related information. proprietary -DISCOVER-AQ_Aircraft_Remote_Sensing_Aerosol_Data_1 DISCOVER-AQ UC-12 Aircraft HSRL Aerosol Measurements LARC_ASDC STAC Catalog 2011-07-01 2013-09-04 -123.86, 28.28, -74.71, 39.77 https://cmr.earthdata.nasa.gov/search/concepts/C1604617793-LARC_ASDC.umm_json DISCOVER-AQ_Aircraft_Remote_Sensing_Aerosol_Data are NASA UC-12 aircraft HSRL measurements of extinction, backscattering, and depolarization profiles at 1064 and 532 nm made during the first deployment of the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations (DISCOVER-AQ). Data collection is complete. proprietary DISCOVERAQ_California_Aerosol_AircraftInSitu_P3B_Data_1 DISCOVER-AQ California Deployment P-3B Aircraft In Situ Aerosol Data LARC_ASDC STAC Catalog 2013-01-09 2013-02-10 -130, 25, -70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2245997372-LARC_ASDC.umm_json DISCOVERAQ_California_Aerosol_AircraftInSitu_P3B_Data contains in situ aerosol data collected onboard NASA's P-3B aircraft during the California (San Joaquin Valley) deployment of NASA's DISCOVER-AQ field study. Instruments utilized to collect data found in this data product include the PSAP, APS, CPC, CCN Counter, Nephelometer/PI-Neph, LAS, PILS, Ion Chromatographs, PILS/Total Organic Carbon Analyzer (TOC), SMPS, SP2 and UHSAS. This data product contains data for only the California deployment, and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary DISCOVERAQ_California_AircraftRemoteSensing_B200_ACAM_Data_1 DISCOVER-AQ California Deployment B-200 Aircraft Remotely Sensed Airborne Compact Atmospheric Mapper Data LARC_ASDC STAC Catalog 2013-01-12 2013-02-10 -130, 25, -70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2404262882-LARC_ASDC.umm_json DISCOVERAQ_California_AircraftRemoteSensing_B200_ACAM_Data contains remotely sensed data collected by the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's B-200 aircraft during the California (San Joaquin Valley) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the California deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary DISCOVERAQ_California_AircraftRemoteSensing_B200_HSRL2_Data_1 DISCOVER-AQ California Deployment B-200 Aircraft Remotely Sensed High Spectral Resolution Lidar (HSRL-2) Data LARC_ASDC STAC Catalog 2013-01-12 2013-02-10 -130, 25, -65, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2245997379-LARC_ASDC.umm_json DISCOVERAQ_California_AircraftRemoteSensing_B200_HSRL_Data contains remotely sensed data collected by the High Spectral Resolution Lidar (HSRL-2) onboard NASA's B-200 aircraft during the California (San Joaquin Valley) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary @@ -4587,7 +4581,6 @@ DISCOVERAQ_Maryland_Ground_Essex_Data_1 DISCOVER-AQ Maryland Deployment Essex Gr DISCOVERAQ_Maryland_Ground_Fairhill_Data_1 DISCOVER-AQ Maryland Deployment Fairhill Ground Site Data LARC_ASDC STAC Catalog 2011-06-11 2011-08-06 -85, 30, -70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2404262810-LARC_ASDC.umm_json DISCOVERAQ_Maryland_Ground_Fairhill_Data contains data collected at the Fairhill ground site during the Maryland (Baltimore-Washington) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary DISCOVERAQ_Maryland_Ground_Oldtown_Data_1 DISCOVER-AQ Maryland Deployment Oldtown Ground Site Data LARC_ASDC STAC Catalog 2011-06-17 2011-08-02 -85, 30, -70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2358899862-LARC_ASDC.umm_json DISCOVERAQ_Maryland_Ground_Oldtown_Data contains data collected at the Oldtown ground site during the Maryland (Baltimore-Washington) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary DISCOVERAQ_Maryland_Ground_Padonia_Data_1 DISCOVER-AQ Maryland Deployment Padonia Ground Site Data LARC_ASDC STAC Catalog 2011-06-17 2011-08-03 -85, 30, -70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2358890638-LARC_ASDC.umm_json DISCOVERAQ_Maryland_Ground_Padonia_Data contains data collected at the Padonia ground site during the Maryland (Baltimore-Washington) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary -DISCOVERAQ_Maryland_Ground_Pandora_Data_1 DISCOVER-AQ Maryland Deployment Pandora Column Observations LARC_ASDC STAC Catalog 2011-06-11 2011-11-14 -85, 30, 70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2358894935-LARC_ASDC.umm_json DISCOVERAQ_Maryland_Pandora_Data contains all of the Pandora instrumentation data collected during the DISCOVER-AQ field study. Contained in this dataset are column measurements of NO2 and O3. Pandoras were situated at various ground sites across the study area, including Aldino, Beltsville, Edgewood, Essex, Fairhill, GSFC, Oldtown, Padonia, SERC, UMBC, UMD, and USNA. This data product contains only data from the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary DISCOVERAQ_Maryland_Ground_UMBC_Data_1 DISCOVER-AQ Maryland Deployment UMBC Ground Site Data LARC_ASDC STAC Catalog 2011-06-26 2011-08-02 -85, 30, -70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2358915656-LARC_ASDC.umm_json DISCOVERAQ_Maryland_Ground_UMBC_Data contains data collected at the UMBC (University of Maryland Baltimore County) ground site during the Maryland (Baltimore-Washington) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary DISCOVERAQ_Maryland_Merge_Data_1 DISCOVER-AQ Maryland Deployment P-3B Aircraft Merged Data Files LARC_ASDC STAC Catalog 2011-06-29 2011-08-02 -85, 30, -70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2241876240-LARC_ASDC.umm_json DISCOVERAQ_Maryland_Merge_Data contains pre-generated merged data files created from measurements obtained onboard the P-3B aircraft during the Maryland (Baltimore-Washington) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary DISCOVERAQ_Maryland_MetNav_AircraftInSitu_P3B_Data_1 DISCOVER-AQ Maryland Deployment P-3B Aircraft In Situ Meteorological and Navigational Data LARC_ASDC STAC Catalog 2011-06-25 2011-08-02 -85, 30, -70, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2241863842-LARC_ASDC.umm_json DISCOVERAQ_Maryland_MetNav_AircraftInSitu_P3B_Data contains in situ meteorological and navigational data collected onboard NASA's P-3B aircraft during the Maryland (Baltimore-Washington) deployment of NASA's DISCOVER-AQ field study. This product features navigational data for the P-3B aircraft, along with data from the DLH. This data product contains data for only the Maryland deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes. proprietary @@ -4723,7 +4716,9 @@ DeltaX_L3_AVIRIS-NG_Water_V3_2152_3 Delta-X: AVIRIS-NG L3-derived Water Quality, DeltaX_L3_AirSWOT_WaterElev_V2_2349_2 Delta-X: AirSWOT L3 Water Surface Elevations, MRD, Louisiana, 2021, Version 2 ORNL_CLOUD STAC Catalog 2021-03-26 2021-09-12 -91.54, 29.07, -90.58, 29.76 https://cmr.earthdata.nasa.gov/search/concepts/C3235707681-ORNL_CLOUD.umm_json This dataset contains water surface elevations at selected point locations generated from the AirSWOT data collected during the Spring and Fall 2021 Delta-X deployments over the Atchafalaya and Terrebonne basins in Louisiana, USA. AirSWOT uses near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data. The Level 3 (L3) data were created by masking land areas out of the AirSWOT Level 2 products, then filtering and averaging to the AirSWOT heights to produce water surface elevations at selected points throughout the scene. The AirSWOT elevation data are useful for calibrating elevation and slopes along the main channels, as well as tying observations to open ocean tidal conditions. AirSWOT performance in the floodplain was limited by the presence of vegetation and the very small slope characteristic of two dimensional floodplain discharge. Therefore, the bulk of the AirSWOT data collections were targeted at the larger channels, since the channel discharge provides the necessary boundary conditions for potential overflow to islands and floodplains. The data are provided in comma-separated values (CSV) format. proprietary DeltaX_L3_UAVSAR_WaterLevels_2058_1.1 Delta-X: UAVSAR L3 Water Level Changes, MRD, Louisiana, 2021 ORNL_CLOUD STAC Catalog 2021-03-27 2021-09-13 -91.59, 29.01, -90.13, 29.78 https://cmr.earthdata.nasa.gov/search/concepts/C2428357062-ORNL_CLOUD.umm_json This dataset contains georeferenced InSAR-derived water level change maps for Delta-X flight lines acquired during the spring (2021-03-27 to 2021-04-18) and fall (2021-09-03 to 2021-09-13) deployments. Water-level change observations are provided throughout wetlands of the Atchafalaya and Terrebonne Basins, in Southern Louisiana, USA, within the Mississippi River Delta (MRD). The data were collected by Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), a polarimetric L-band synthetic aperture radar flown on the NASA Gulfstream-III (C20) aircraft as part of the Delta-X campaign. Water surface elevations were measured on multiple flights at 30-minute intervals. There are three types of gridded products available: temporalcoherence (which provide an index measuring quality of phase unwrapping ranging from 0 (poor) to 1 (correctly unwrapped)), waterlevelchange in centimeters (which provide cumulative changes in water levels at approximately 30-minute intervals), and waterlevelchange_ramp in centimeters (which provide a 2-dimensional linear trend in water-level estimates not related to changing water levels). The water-level change maps were estimated using the phase unwrapping corrected interferograms generated for nearest-neighbor (NN), NN+1, and NN+2 pairs for data acquired within a single flight (one day). This analysis was done for all flight lines. Water level changes are relative to the first sampling flight for that study area. Data quality was assessed by comparing water elevation estimates with data from in situ water level gauges throughout the study area. A series of quality assurance masks of troposphere-induced phase delay regions were generated for all SAR acquisition dates using a weather feature matching algorithm. proprietary DeltaX_LandAccretionMap_WLD_2308_1 Delta-X: Modeled Land Accretion Rate Maps, Wax Lake Delta, MRD, LA, USA, 2021 ORNL_CLOUD STAC Catalog 2021-03-20 2021-08-27 -91.58, 29.39, -91.33, 29.59 https://cmr.earthdata.nasa.gov/search/concepts/C3104728587-ORNL_CLOUD.umm_json This dataset provides sediment transport and land accretion model results at Wax Lake Delta (WLD), Atchafalaya Basin, in coastal Louisiana, USA. Data were simulated over the Delta-X Spring 2021 (2021-03-21 to 2021-04-03) and Fall 2021 (2021-08-14 to 2021-08-27) campaigns and the results are presented as annualized land accretion rate map. The model results for these two short-term campaigns are used to calculate the 1-year upscale land accretion rate at WLD in post-processing, which is also provided in this dataset. Model results for these two short-term campaigns were derived using inputs from an ANUGA hydrodynamic model. The Matlab sediment transport and land accretion model used to derive these data employs sediment transport theory that models floc behavior using a non-cohesive sediment transport framework. Data are presented in NetCDF (*.nc) format. proprietary +DeltaX_LandAccretion_WLD_2309_1 Delta-X: Matlab Model for Wax Lake Delta Land Accretion ORNL_CLOUD STAC Catalog 2021-03-20 2021-08-27 -91.58, 29.39, -91.33, 29.59 https://cmr.earthdata.nasa.gov/search/concepts/C3281998337-ORNL_CLOUD.umm_json This dataset provides the Matlab sediment transport and land accretion model at Wax Lake Delta (WLD), Atchafalaya Basin, in coastal Louisiana. The data include the Matlab scripts that solve the advection and Exner equations to simulate the suspended sediment transport and accretion at WLD. The model requires modeled flow information from a separate ANUGA hydrodynamic model as inputs. For this study, ANUGA modeled flow information from the Delta-X Spring and Fall 2021 campaigns were used as inputs. The ANUGA output files are converted to variables used by this Matlab model using pre-processing tools. The main code calculates suspended sediment fluxes and accretion rates of mud and sand as a function of space and time. The cumulative sediment accretion from each campaign was then used to estimate an annualized land accretion map using a weighted-average formula presented. The final product, the one-yr upscaled land accretion map, is archived as a separate dataset. proprietary DeltaX_MarshAccretion_NUMAR_2354_1 Delta-X: NUMAR Predictive Model for Marsh Accretion Rates and Chemical Properties ORNL_CLOUD STAC Catalog 2020-01-01 2022-12-31 -91.86, 28.72, -90.19, 29.76 https://cmr.earthdata.nasa.gov/search/concepts/C3235699055-ORNL_CLOUD.umm_json This dataset provides input data and model code to run the Marsh Accretion Rates (NUMAR) process model used to predict soil accretion rates and chemical properties for marsh sites in the Mississippi River Delta. NUMAR is a modification of the NUMAN model by Chen and Twilley (1999) that was developed for mangrove environments. This dataset provides Python code, input data in comma separated values (CSV) format, and documentation for installing and running the model in Portable Document Format (PDF). proprietary +DeltaX_NUMAR_Soil_Accretion_2368_1 Delta-X: NUMAR Soil Accretion Modeled to 2100, MRD, Louisiana, USA ORNL_CLOUD STAC Catalog 2021-01-01 2100-12-31 -91.54, 29.08, -90.41, 29.7 https://cmr.earthdata.nasa.gov/search/concepts/C3281999060-ORNL_CLOUD.umm_json This dataset holds modeled estimates of soil accretion for the Atchafalaya and Terrebonne basins in the Mississippi River Delta of coastal Louisiana, U.S. Soil accretion was predicted from 2021-2100 using the Numerical Understanding of Marsh Accretion Resilience (NUMAR) model. This process-based model is an adaptation of the NUMAN model that was modified for marsh environments. The input parameters were aggregated within ecogeomorphic cells, areas of similar vegetation and elevation. The dataset includes spatially explicit input values, description of important parameters, and a shapefile of model outputs. proprietary DeltaX_Particle_Size_LISST_V2_2077_2 Delta-X: In situ Beam Attenuation and Particle Size from LISST-200X, 2021 ORNL_CLOUD STAC Catalog 2021-03-25 2021-09-24 -91.47, 28.79, -90.57, 29.75 https://cmr.earthdata.nasa.gov/search/concepts/C2515316269-ORNL_CLOUD.umm_json This dataset provides in situ measurements of beam attenuation coefficient at 670 nm, average suspended particle size, particle size distribution, and water temperature in surface waters (~0.5 m) of the Atchafalaya and Terrebonne Basins on the southern coast of Louisiana. The field studies were conducted in the Spring and Fall in support of the Delta-X mission and include measurements made in 2021 during March 25 - April 22 and August 14 - September 24. Measurements were made using the Sequoia Scientific Laser In-Situ Scattering and Transmissometer instrument (LISST-200X) in multiple channels of varying width (from a few meters to >100m), near Delta-X intensive study sites and in open bays and lakes and at a few locations in the nearshore Gulf of Mexico. The data are provided in comma-separated (CSV) format. proprietary DeltaX_RTK_Elevation_2071_1 Delta-X: Real-Time Kinematic Elevation Measurements for Coastal Wetlands, LA, 2021 ORNL_CLOUD STAC Catalog 2021-03-21 2021-04-21 -91.45, 29.17, -90.82, 29.51 https://cmr.earthdata.nasa.gov/search/concepts/C2432627361-ORNL_CLOUD.umm_json This dataset provides real-time kinematic (RTK) GPS elevation measurements, along with horizontal and vertical precision errors, obtained along transects near Louisiana's Coastwide Reference Monitoring Systems (CRMS) sites and on Mike Island in Wax Lake Delta (WLD). The data were collected during the Delta-X Spring Campaign from 2021-03-24 to 2021-04-02. The data are provided in comma-separated values (CSV) format. proprietary DeltaX_Sediment_Grain_Size_V2_2135_2 Delta-X: Bed and Suspended Sediment Grain Size, MRD, LA, USA, 2021, Version 2 ORNL_CLOUD STAC Catalog 2021-03-24 2021-08-25 -91.45, 29.17, -90.82, 29.7 https://cmr.earthdata.nasa.gov/search/concepts/C2619216342-ORNL_CLOUD.umm_json This dataset provides sediment concentration and grain size distribution measurements from suspended and bed sediment samples collected in the Atchafalaya and Terrebonne River Basins as part of the Delta-X Spring campaign between March 24 to April 2, 2021 and Delta-X Fall campaign between August 17-25, 2021. During the field campaign, samples were collected in the main distributary channels and the interior of Mike Island in the Wax Lake Delta, Louisiana and at site CRMS0421 inside the Terrebonne River Basin. Sediment samples were collected from a boat using a Van Dorn sampler (for suspended sediment samples) or a Ponar bed sampler (for bed samples). Suspended sediment samples were collected from a boat drifting at approximately the same velocity as the water flow. One sample was collected per drift. Bed samples were collected in a similar fashion. Data includes measurements of sediment grain size, total sediment concentration, as well as water temperature, velocity, salinity, and depth. This Version 2 includes the initial release of Fall 2021 data and an update to the Version 1 (Spring 2021) data file in which an error in the data was resolved. proprietary @@ -5449,7 +5444,7 @@ GCOM-C_SGLI_L1B_Visible_and_Near_Infrared_NP_1km_NA GCOM-C/SGLI L1B Visible and GCOM-C_SGLI_L1B_Visible_and_Near_Infrared_NP_250m_NA GCOM-C/SGLI L1B Visible and Near Infrared (Non-Polarization) (250m) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129085-JAXA.umm_json GCOM-C/SGLI L1B Visible and Near Infrared (Non-Polarization) (250m) dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. GCOM-C/SGLI Level 1B products are using the data contained in Level 1A products as inputs, and the following processes are applied on the input data, calculation of spectral radiance, re-sampling of geometric correction, data and observation data to L1B, Reference Coordinate System, calculation of land/water flag, creation of quality information. This product is top of atmosphere radiance SI (Scaled Integer) data, using the Level 1A product as input. The provided format is HDF5. The spatial resolution is 250 m. 1 km is also available. Radiometric correction is stored. The geometries are projected to L1B reference coordinates commonly for VNR-NP and IRS, and the ground observation position in each band are same. Therefore, as geometric information, latitude, longitude, solar azimuth angle and solar zenith angle of 10 pixels interval are stored commonly for band. On the other hand, since the precise satellite position in observed pixels is varied depending on band, the satellite azimuth angle and the satellite zenith angle are stored by 10 pixels interval for each band. The stored geometric information is the center position of the pixel. In addition, The current version of the product is Version 2. QA flag corresponding to the observation image is appended to Level 1B product. proprietary GCOM-C_SGLI_L1B_Visible_and_Near_Infrared_PL_1km_NA GCOM-C/SGLI L1B Visible and Near Infrared (Polarization) (1km) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698132069-JAXA.umm_json GCOM-C/SGLI L1B Visible and Near Infrared (Polarization) (1km) dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. GCOM-C/SGLI Level 1B products are using the data contained in Level 1A products as inputs, and the following processes are applied on the input data, calculation of spectral radiance, re-sampling of geometric correction, data and observation data to L1B, Reference Coordinate System, calculation of land/water flag, creation of quality information. This product is top of atmosphere radiance SI (Scaled Integer) data, using the Level 1A product as input. The provided format is HDF5. The spatial resolution is 1km. Radiometric correction is stored. The geometries are projected to L1B reference coordinates commonly for VNR-NP and IRS, and the ground observation position in each band are same. Therefore, as geometric information, latitude, longitude, solar azimuth angle and solar zenith angle of 10 pixels interval are stored commonly for band. On the other hand, since the precise satellite position in observed pixels is varied depending on band, the satellite azimuth angle and the satellite zenith angle are stored by 10 pixels interval for each band. The stored geometric information is the center position of the pixel. In addition, The current version of the product is Version 2. QA flag corresponding to the observation image is appended to Level1B product. proprietary GCOM-C_SGLI_L2_AGB_NA GCOM-C/SGLI L2 Above Ground Biomass and Vegetation Roughness Index JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129780-JAXA.umm_json GCOM-C/SGLI L2 Above Ground Biomass and Vegetation Roughness Index dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products are defined to be products composed of physical quantity data that is calculated based on Level 1B products and meteorological data, as well as various additional data related to the physical quantity data. This dataset includes Above Ground Biomass (AGB), Vegetation Roughness Index (VRI) and quality flag (QA_Flag). AGB is the volume of aboveground biomass shown in dry weight and estimated using two sets of the red and near-infrared channel data observed from nadir and slant viewing direction by SGLI sensor. The physical quantity unit is t/ha. VRI is the index expressing 3D structural information of vegetation (the unevenness changes in spatial distribution of canopy density). It is related to both the area ratio of shadows produced by the vegetation canopy in the sensor's field of view and the vegetation coverage. It is a parameter for calculating AGB. The physical quantity unit is dimensionless. The QA_flag shows flag of quality and observation condition. The provided format is HDF5. The spatial resolution is 250 m. The projection method is EQA. The generation unit is Tile. The current version of the product is Version 3. The Version 2 is also available, but please note that the QA_Flag data has been changed. proprietary -GCOM-C_SGLI_L2_ARNP_NA GCOM-C/SGLI L2 Aerosol over the ocean-Land aerosol by near ultra violet JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698132339-JAXA.umm_json "GCOM-C/SGLI L2 Aerosol over the ocean-Land aerosol by near ultra violet dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:ARAE_land, ARAE_ocean: Angstrom Exponent over Land and Ocean at 500 nm and 380 nm (dimensionless), respectively.AROT_land, AROT_ocean: Aerosol Optical Thickness over Land and Ocean at 500 nm (dimensionless), respectively.The utilized aerosol optical model for the retrieval is the same for both over land and ocean, and the coefficients are based on the skyradiometer observations. While the particle shapes, real parts of complex refraction indices, and size distributions of large and small particles are assumed to be fixed, the fraction of small particles and complex refraction indices (in terms of SSA) vary. The algorithm assumes reasonable aerosol parameters for the SGLI observations and derives the contents of this dataset.The provided format is HDF5. The spatial resolution is 1 km. The projection method is EQA. The spatial coverage is ""Tile"". The current version of the product is Version 3. The Version 2 is also available." proprietary +GCOM-C_SGLI_L2_ARNP_NA GCOM-C/SGLI L2 AeRosol properties using Numerical Prediction JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698132339-JAXA.umm_json "GCOM-C/SGLI L2 AeRosol properties using Numerical Prediction dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:AROT: Aerosol Optical Thickness over land and ocean at 500 nm (dimensionless).ARAE: Angstrom Exponent over land and ocean at 500 nm and 380 nm (dimensionless).ASSA: Single Scattering Albedo over land and ocean at 380 nm (dimensionless).AROT_uncertainty, AROT_uncertainty, AROT_uncertainty: The uncertainties of AROT, ARAE and ASSA, respectively (dimensionless).The utilized aerosol optical model for the retrieval is the same for both over land and ocean, and the coefficients are based on the skyradiometer observations. While the particle shapes, real parts of complex refraction indices, and size distributions of large and small particles are assumed to be fixed, the fraction of small particles and complex refraction indices (in terms of SSA) vary. The algorithm assumes reasonable aerosol parameters for the SGLI observations and derives the contents of this dataset.The provided format is HDF5. The spatial resolution is 1 km. The projection method is EQA. The spatial coverage is ""Tile"". The current version of the product is Version 3. The Version 2 is also available." proprietary GCOM-C_SGLI_L2_CLFG_1km_NA GCOM-C/SGLI L2 Cloud flag Classification (1km) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698130267-JAXA.umm_json "GCOM-C/SGLI L2 Cloud Flag Classification (1km) dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The CLFG dataset includes Clear Confidence Level (0~1, 1 is clear), Cloud Inhomogeneity, phase, and the relevant information.The cloud/clear discrimination algorithm (CLAUDIA) and the cloud microphysical properties algorithm (CAPCOM) are utilized, and Nakajima et al. 2019 (https://doi.org/10.1186/s40645-019-0295-9 ) describe the methodologies in detail.The provided format is HDF5. The spatial resolution is 1 km. The projection method is EQA. The spatial coverage is ""Tile"". The current version of the product is Version 3. The Version 2 is also available" proprietary GCOM-C_SGLI_L2_CLFG_250m_NA GCOM-C/SGLI L2 Cloud flag Classification (250m) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698130095-JAXA.umm_json "GCOM-C/SGLI L2 Cloud Flag Classification (250m) dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The CLFG dataset includes Clear Confidence Level (0~1, 1 is clear), Cloud Inhomogeneity, phase, and the relevant information.The cloud/clear discrimination algorithm (CLAUDIA) and the cloud microphysical properties algorithm (CAPCOM) are utilized, and Nakajima et al. 2019 (https://doi.org/10.1186/s40645-019-0295-9 ) describe the methodologies in detail.The provided format is HDF5. The spatial resolution is 250m . The projection method is EQA. The spatial coverage is ""Tile"". The current version of the product is Version 3. The Version 2 is also available" proprietary GCOM-C_SGLI_L2_CLPR_NA GCOM-C/SGLI L2 Cloud properties JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129304-JAXA.umm_json GCOM-C/SGLI L2 Cloud properties dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:CLOT_W and CLOR_W: Optical thickness (unitless) and effective radius of water cloud droplets (mm), respectively.CLOT_I are CLER_I: Optical thickness (unitless) and effective radius of ice cloud droplets (mm), respectively.CLTT and CLTH: Temperature and Height of the cloud top layer (kelvin and km), respectively.CLTYPE: Cloud discrimination flag including the classification of cloud type and phase (unitless)The cloud properties are retrieved with the Comprehensive Analysis Program for Cloud Optical Measurements (CAPCOM), initially developed for the GLI mission. The current algorithm is optimized for the SGLI characteristics and uses L2 Cloud flag classification.The provided format is HDF5. The spatial resolution is 1 km. The projection method is EQA. The spatial coverage is Tile. The current version of the product is Version 3. The Version 2 is also available proprietary @@ -5471,7 +5466,7 @@ GCOM-C_SGLI_L2_SIPR_250m_NA GCOM-C/SGLI L2 Snow and Ice Physical Properties (250 GCOM-C_SGLI_L2_SST_1km_NA GCOM-C/SGLI L2 Sea surface temperature (1km) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698130204-JAXA.umm_json GCOM-C/SGLI L2 Sea Surface Temperature (1km) dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products are defined to be products composed of physical quantity data that is calculated based on Level 1B products and meteorological data, as well as various additional data related to the physical quantity data.This dataset includes Sea Surface Temperature (SST) and Cloud probability (Cloud_probability).SST data is the temperature of sea surface. The physical quantity unit is degree.Cloud Probability data is possibly affected by clouds for each SST pixel. The unit is %.The package includes not only this product but also QA_Flag data with the same spatial resolution as the auxiliary data. The provided format is HDF5. The Spatial resolution is 1 km. The projection method is L1B reference coordinates. The generation unit is Scene. The current version of the product is Version 3. The Version 2 is also available, but please note that the QA_Flag data has been changed. proprietary GCOM-C_SGLI_L2_SST_250m_NA GCOM-C/SGLI L2 Sea surface temperature (250m) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129871-JAXA.umm_json GCOM-C/SGLI L2 Sea Surface Temperature (250m) dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products are defined to be products composed of physical quantity data that is calculated based on Level 1B products and meteorological data, as well as various additional data related to the physical quantity data.This dataset includes Sea Surface Temperature (SST) and Cloud probability (Cloud_probability).SST data is the temperature of sea surface. The physical quantity unit is degree.Cloud Probability data is possibly affected by clouds for each SST pixel. The physical quantity unit is %.The package includes not only this product but also QA_Flag data with the same spatial resolution as the auxiliary data. The provided format is HDF5. The Spatial resolution is 250 m. The projection method is L1B reference coordinates. The generation unit is Scene. The current version of the product is Version 3. The Version 2 is also available, but please note that the QA_Flag data has been changed. proprietary GCOM-C_SGLI_L2_VGI_NA GCOM-C/SGLI L2 Vegetation Indices JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129250-JAXA.umm_json "GCOM-C/SGLI L2 Vegetation Indices dataset is obtained from the SGLI sensor onboard GCOM-C produced by the Japan Aerospace Exploration Agency (JAXA). The product is the vegetation indices and shadow index. GCOM-C is sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017 and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products are defined to be granule scene and global (tile) data of physical quantity derived from Level-1B or Level-2 products and ancillary data such as meteorological data and various additional data related to the physical quantity.This dataset includes Enhanced Vegetation Index (EVI), Normalized Defferemce Difference Vegetation Index (NDVI), Shadow Index (SDI), and quality flag (QA_flag). NDVI is a simple normalized index that can be used to indicate the activity of vegetation making use of the reflectance at red and near-infrared wavelengths where the reflectance of vegetation exhibits a steep increase like a step function. The physical quantity is dimensionless. EVI is an improved version of vegetation indices designed to enhance the vegetation signal in high density vegetation area. The physical quantity is dimensionless. SDI is the fraction of shadow generated by conformation of vegetation (shadow area proportion within a pixel) and is estimated from SW03 surface reflectance. SDI reflects the canopy shape and density. The physical quantity is dimensionless. The QA_flag shows flag of quality and observation condition. The provided format is HDF5. The Spatial resolution is 250 m. The projection method is EQA. The data projection type is ""Tile"". The current version of the product is Version 3. The Version 2 is also available." proprietary -GCOM-C_SGLI_L2_global-ARNP_NA GCOM-C/SGLI L2 Global-Aerosol over the ocean-Land aerosol by near ultra violet JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698132167-JAXA.umm_json GCOM-C/SGLI L2 Global-Aerosol over the ocean-Land aerosol by near ultra violet dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:ARAE_land, ARAE_ocean: Angstrom Exponent over Land and Ocean at 500 nm and 380 nm (dimensionless), respectively.AROT_land, AROT_ocean: Aerosol Optical Thickness over Land and Ocean at 500 nm (dimensionless), respectively.The utilized aerosol optical model for the retrieval is the same for both over land and ocean, and the coefficients are based on the skyradiometer observations. While the particle shapes, real parts of complex refraction indices, and size distributions of large and small particles are assumed to be fixed, the fraction of small particles and complex refraction indices (in terms of SSA) vary. The algorithm assumes reasonable aerosol parameters for the SGLI observations and derives the contents of this dataset.The provided format is HDF5. The spatial and temporal resolutions are 1/24 deg and daily, respectively. The projection method is EQA. The spatial coverage is Global. The current version of the product is Version 3. The Version 2 is also available, note that the QA_Flag data has been updated. proprietary +GCOM-C_SGLI_L2_global-ARNP_NA GCOM-C/SGLI L2 Global-AeRosol properties using Numerical Prediction JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698132167-JAXA.umm_json GCOM-C/SGLI L2 Global-AeRosol properties using Numerical Prediction dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA).GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are listed in the following:AROT: Aerosol Optical Thickness over land and ocean at 500 nm (dimensionless).ARAE: Angstrom Exponent over land and ocean at 500 nm and 380 nm (dimensionless).ASSA: Single Scattering Albedo over land and ocean at 380 nm (dimensionless).AROT_uncertainty, AROT_uncertainty, AROT_uncertainty: The uncertainties of AROT, ARAE and ASSA, respectively (dimensionless).The utilized aerosol optical model for the retrieval is the same for both over land and ocean, and the coefficients are based on the skyradiometer observations. While the particle shapes, real parts of complex refraction indices, and size distributions of large and small particles are assumed to be fixed, the fraction of small particles and complex refraction indices (in terms of SSA) vary. The algorithm assumes reasonable aerosol parameters for the SGLI observations and derives the contents of this dataset.The provided format is HDF5. The spatial and temporal resolutions are 1/24 deg and daily, respectively. The projection method is EQA. The spatial coverage is Global. The current version of the product is Version 3. The Version 2 is also available, note that the QA_Flag data has been updated. proprietary GCOM-C_SGLI_L2_global-LCLR_NA GCOM-C/SGLI L2 Global-TOA radiance JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698130163-JAXA.umm_json GCOM-C/SGLI L2 Global Top of atmosphere radiance is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data.The contents are each band's Top of atmosphere radiance (W/m^2/str/mm) and Land water flag.This product is generated from the Level1B (1 km) daily products. The provided format is HDF5. The spatial and temporal resolutions is are 1/24 degree and daily, respectively. The projection method is EQA. The spatial coverage is Global. The current version of the product is Version 3. The Version 2 is also available proprietary GCOM-C_SGLI_L2_global-LTOA_NA GCOM-C/SGLI L2 Global-TOA radiance (clear sky) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698128886-JAXA.umm_json GCOM-C/SGLI L2 Global Top of atmosphere radiance (clear sky) is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is a Sun-synchronous sub-recurrent orbit satellite launched on December 23, 2017. It mounts SGLI sensor to observe long-term geophysical conditions based on 28 variables, including aerosol and vegetation, out of four Earth subsystems: atmosphere, land, ocean, and cryosphere. These data are helpful to improve the global warming prediction accuracy. The SGLI has a swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 products consist of derived physical variables based on Level 1B products, such as meteorological data. The contents are each band's Top of atmosphere radiance (W/m^2/str/mm) and Land water flag. TOA radiances are initially derived from daily 1-km resolution TOA radiance and cloud flag products, which spatial coverage is Tile. Consequently, this product is generated from the clear (cloud-free) pixels. The provided format is HDF5. The spatial and temporal resolutions are 1/24 deg and daily, respectively. The projection method is EQA. The spatial coverage is Global. The current version of the product is Version 3. The Version 2 is also available proprietary GCOM-C_SGLI_L2_statistics-AGB_1month_250m_NA GCOM-C/SGLI L2 Statistics-Above Ground Biomass (AGB) (1-Month,250m) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129161-JAXA.umm_json GCOM-C/SGLI L2 Statistics-Above Ground Biomass (AGB) (1-Month,250m) dataset is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. Level 2 statistics products are using the Level2 product of land and cryosphere (Daily, Tile, 250 m or 1 km resolution) as input, it calculates and outputs the temporal statistics of 8-days or 1-month. The region definition and spatial resolutions of the output product are kept those of input data. This dataset includes Above Ground Biomass (AGB). AGB is the volume of aboveground biomass shown in dry weight and estimated using two sets of the red and near-infrared channel data observed from nadir and slant viewing direction by SGLI sensor. The physical quantity unit is t/ha.The statistics values stored to product are average (AVE), root-mean-square (RMS), maximum value (MAX), minimum value (MIN), number of input data (Ninput), number of used data (Nused), date of observation (Date), and quality flag (QA_flag).The provided format is HDF5. The spatial resolution is 250m. The statistical period is 1 month also 8 days statistics is available. The projection method is EQA. The generation unit is Tile.The current version of the product is Version 3. The Version 2 is also available. proprietary @@ -5984,7 +5979,7 @@ GCOM-C_SGLI_L3M_VRI_1month_1-24deg_NA GCOM-C/SGLI L3 Map Vegetation Roughness In GCOM-C_SGLI_L3M_VRI_8days_1-24deg_NA GCOM-C/SGLI L3 Map Vegetation Roughness Index (VRI) (8-Days,1/24 deg) JAXA STAC Catalog 2018-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698133105-JAXA.umm_json GCOM-C/SGLI L3 Map Vegetation Roughness Index (VRI) (8-Days,1/24 deg) is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band. Level 3 products are defined to be products derived from Level 1B and Level 2 products by statistically processing the Level 1B and Level 2 products in time and space domains.This dataset is 8 days map-projected statistics product. This dataset includes VRI: Vegetation Roughness Index. Physical quantity unit is dimensionless. The stored statistics values are average (AVE) and quality flag (QA_flag). The statistical period is 8 days, also 1 day and 1 month statistics are available. The projection method is EQR. The generation unit is Global. The current version of the product is Version 3. The Version 2 is also available. proprietary GCOM-W_AMSR2_L1B_TB_NA GCOM-W/AMSR2 L1B Brightness Temperature JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698128857-JAXA.umm_json "GCOM-W/AMSR2 L1B Brightness Temperature dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 1B product uses Level 1A product as the input and converting digital output values from the sensor to brightness temperatures. Values that are calculated from sensor counts and are proportional to the power of observed electromagnetic wave. They are expressed by the physical temperature of blackbody, which can emit the electromagnetic wave with the same power. This product is the Level 1B brightness temperatures which converted from digital output values from the sensor. The physical quantity unit is Kelvin. The provided format is HDF5. The physical quantity unit is Kelvin. The sampling resolution is 5-50km. The current version of the product is Version 2. The Version 1 is also available. The generation unit is Scene (defined as a half orbit)." proprietary GCOM-W_AMSR2_L1R_TB_NA GCOM-W/AMSR2 L1R Brightness Temperature JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698130493-JAXA.umm_json "GCOM-W/AMSR2 L1R Brightness Temperature dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. This product is The Level 1R brightness data which resampled the Level 1B brightness temperature data in proportion to the low-frequency resolution. Resampling takes place by overlaying the original brightness temperature data with weighted parameters (resampling coefficients) calculated using the Backus-Gilbert Method. The center latitude and longitude of data is adjusted to the 89 GHz A channel receiver data. The provided format is HDF5. The physical quantity unit is Kelvin. The Sampling resolution are 5-50km. The current version of the product is Version 2. The Version 1 is also available. The generation unit is scene (defined as a half orbit)." proprietary -GCOM-W_AMSR2_L2_CLW_NA GCOM-W/AMSR2 L2 Cloud Liquid Water JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129808-JAXA.umm_json "GCOM-W/AMSR2 Cloud Liquid Water dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 15 km. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The generation unit is scene (defined as a half orbit)." proprietary +GCOM-W_AMSR2_L2_CLW_NA GCOM-W/AMSR2 L2 Cloud Liquid Water JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129808-JAXA.umm_json "GCOM-W/AMSR2 Cloud Liquid Water dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 15 km. The current version of the product is Version 2. The Version 1 is also available. The generation unit is scene (defined as a half orbit)." proprietary GCOM-W_AMSR2_L2_PRC_NA GCOM-W/AMSR2 L2 Precipitation JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129620-JAXA.umm_json "GCOM-W/AMSR2 L2 Precipitation dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Precipitation (PRC). Although ""precipitation"" is usually defined as amount of water, which reaches the surface of the earth from atmosphere as rain and/or snow, microwave imager's precipitation products provide amount of rain (surface rainfall). Coverage of the product is global, and unit is [mm/h]. Accuracy of rainfall estimate over land, however tends to be lower than that over the ocean. Method of rainfall estimate used in AMSR2 precipitation product is also applied to ""Global Rainfall Watch"" system, which distributes global rainfall map in near-real-time. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 15 km. The current version of the product is Version 2. The Version 1 is also available. The generation unit is scene (defined as a half orbit)." proprietary GCOM-W_AMSR2_L2_SIC_NA GCOM-W/AMSR2 L2 Sea Ice Concentration JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698130287-JAXA.umm_json "GCOM-W/AMSR2 L2 Sea Ice Concentration dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Sea Ice Concentration (SIC), percentage of sea ice coverage within target ocean area. Coverage of the product is over the ocean around Arctic and Antarctic Sea, and unit is [%]. There is no sea ice within pixel area when sea ice concentration is 0%, and all pixel area is covered by sea ice when it shows 100%. We can learn distribution of sea ice immediately using this product, and it will become more and more important because of recent decrease of Arctic sea ice cover. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 15 km. The current version of the product is Version 3. The Version 2 is also available. The generation unit is scene (defined as a half orbit)." proprietary GCOM-W_AMSR2_L2_SMC_NA GCOM-W/AMSR2 L2 Soil Moisture Content JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698131616-JAXA.umm_json "GCOM-W/AMSR2 L2 Soil Moisture Content dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Soil Moisture Content (SMC), amount of soil wetness near the ground surface as volume water content. Coverage of the product is over land only, and unit is [%]. Soil moisture cannot be estimated near the coast, around big lakes and marshes, or areas with wide spread dense forests. Since microwave radiometer can get data constantly and frequently, this product is used in monitoring of large-scale cultivation areas in the continents. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 50 km. The current version of the product is Version 3. The Version 2 is also available. The generation unit is scene (defined as a half orbit)." proprietary @@ -5992,10 +5987,10 @@ GCOM-W_AMSR2_L2_SND_NA GCOM-W/AMSR2 L2 Snow Depth JAXA STAC Catalog 2012-07-02 GCOM-W_AMSR2_L2_SST_NA GCOM-W/AMSR2 L2 Sea Surface Temperature JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129182-JAXA.umm_json "GCOM-W/AMSR2 L2 Sea Surface Temperature dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Sea Surface Temperature (SST), temperature of water at ocean surface. Coverage of the product is over the ocean only, and unit is [degree]. Its horizontal resolution is about 20-30 km and coarser than that of optical instruments. Microwave radiometer, however, can observe ocean surface through clouds, and monitor continuous change of sea surface temperature over the ocean where few clear region can be found in specific areas or seasons. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 50 km. The current version of the product is Version 4. The Version 3 is also available. The generation unit is scene (defined as a half orbit)." proprietary GCOM-W_AMSR2_L2_SSW_NA GCOM-W/AMSR2 L2 Sea Surface Wind Speed JAXA STAC Catalog 2012-07-02 -180, -40, 180, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2698128920-JAXA.umm_json "GCOM-W/AMSR2 L2 Sea Surface Wind Speed dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Sea Surface Wind Speed (SSW). Coverage of the product is over the ocean only, and unit is [m/s]. Microwave radiometer can observe wind speed under the clouds, but it is difficult to estimate where there is rainfall and will be missing value. Wind speed around tropical cyclones, however, is important parameter in weather forecast, and we provide research product, which includes wind speed in rainy area over the ocean, as all-weather wind speed research product. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 15 km. The current version of the product is Version 4. The Version 3 is also available. The generation unit is scene (defined as a half orbit)." proprietary GCOM-W_AMSR2_L2_WV_NA GCOM-W/AMSR2 L2 Integrated Water Vapor JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698130144-JAXA.umm_json "GCOM-W/AMSR2 L2 Integrated Water Vapor dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. Level 2 products calculates various geophysical parameters related to water using the Level 1B or 1R products as inputs. This dataset includes Integrated Water Vapor (WV), amount of vertically accumulated water vapor (H2O in gaseous state) in the atmosphere, and defined as amount of water per unit area. Coverage of the product is over the ocean only, and unit is [kg/m2]. Total precipitable water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and cloud liquid water. The Pixel_Data_Quality is quality flag stored for each observation point. The provided format is HDF5. The Sampling resolution is 15 km. The current version of the product is Version 2. The Version 1 is also available. The generation unit is scene (defined as a half orbit)." proprietary -GCOM-W_AMSR2_L3_CLW_1day_0.1deg_NA GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.1 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698128998-JAXA.umm_json "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 day. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The projection method is EQR. The generation unit is global." proprietary -GCOM-W_AMSR2_L3_CLW_1day_0.25deg_NA GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.25 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129489-JAXA.umm_json "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 day. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The projection method is EQR. The generation unit is global." proprietary -GCOM-W_AMSR2_L3_CLW_1month_0.1deg_NA GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.1 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698128896-JAXA.umm_json "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes Month Mean Cloud liquid water (CLW), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). CLW is amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Standard_Deviation is standard deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine ""Geophysical Data"". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 month. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The projection method is EQR. The generation unit is global." proprietary -GCOM-W_AMSR2_L3_CLW_1month_0.25deg_NA GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.25 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698131369-JAXA.umm_json "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). CLW is amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Standard_Deviation is standarad deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine ""Geophysical Data"". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 month. The current version of the product is Version 3. The Version 1 and Version 2 are also available. The projection method is EQR. The generation unit is global." proprietary +GCOM-W_AMSR2_L3_CLW_1day_0.1deg_NA GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.1 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698128998-JAXA.umm_json "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 day. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global." proprietary +GCOM-W_AMSR2_L3_CLW_1day_0.25deg_NA GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.25 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129489-JAXA.umm_json "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Day,0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 day. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global." proprietary +GCOM-W_AMSR2_L3_CLW_1month_0.1deg_NA GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.1 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698128896-JAXA.umm_json "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes Month Mean Cloud liquid water (CLW), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). CLW is amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Standard_Deviation is standard deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine ""Geophysical Data"". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 month. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global." proprietary +GCOM-W_AMSR2_L3_CLW_1month_0.25deg_NA GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.25 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698131369-JAXA.umm_json "GCOM-W/AMSR2 L3 Cloud Liquid Water (1-Month, 0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes averaged Cloud liquid water (CLW), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). CLW is amount of vertically accumulated cloud droplet in the atmosphere, defined as amount of water per unit area. Coverage of the product is over the ocean only and Vertically integrated (columnar) cloud liquid water. Sea ice and precipitating areas are expected. The physical quantity unit is [kg/m2]. Cloud liquid water is one of essential hydrological parameters describing state of the atmosphere along with precipitation and total precipitable water. Standard_Deviation is standarad deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine ""Geophysical Data"". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 month. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global." proprietary GCOM-W_AMSR2_L3_PRC_1day_0.1deg_NA GCOM-W/AMSR2 L3 Precipitation (1-Day,0.1 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698129865-JAXA.umm_json "GCOM-W/AMSR2 L3 Precipitation (1-Day,0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes Precipitation (PRC) overwritten by latest data. Although ""precipitation"" is usually defined as amount of water, which reaches the surface of the earth from atmosphere as rain and/or snow, microwave imager's precipitation products provide amount of rain (surface rainfall). Coverage of the product is global, and unit is [mm/h]. Accuracy of rainfall estimate over land, however tends to be lower than that over the ocean. Method of rainfall estimate used in AMSR2 precipitation product is also applied to ""Global Rainfall Watch"" system, which distributes global rainfall map in near-real-time. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 day. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global." proprietary GCOM-W_AMSR2_L3_PRC_1day_0.25deg_NA GCOM-W/AMSR2 L3 Precipitation (1-Day,0.25 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698132862-JAXA.umm_json "GCOM-W/AMSR2 L3 Precipitation (1-Day,0.25 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes Precipitation (PRC) overwritten by latest data. Although ""precipitation"" is usually defined as amount of water, which reaches the surface of the earth from atmosphere as rain and/or snow, microwave imager's precipitation products provide amount of rain (surface rainfall). Coverage of the product is global, and unit is [mm/h]. Accuracy of rainfall estimate over land, however tends to be lower than that over the ocean. Method of rainfall estimate used in AMSR2 precipitation product is also applied to ""Global Rainfall Watch"" system, which distributes global rainfall map in near-real-time. Missing value is -32768. When there is no geophysical data within observation swath, this value is set up when computing neither the case where the amount of geophysics is incomputable, nor the amount of geophysics. Error values are -32761 to -32767. It is outside observation swath data. The provided format is HDF5. The Sampling resolution is 0.25degree grid. The statistical period is 1 day. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global." proprietary GCOM-W_AMSR2_L3_PRC_1month_0.1deg_NA GCOM-W/AMSR2 L3 Precipitation (1-Month, 0.1 deg) JAXA STAC Catalog 2012-07-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698134112-JAXA.umm_json "GCOM-W/AMSR2 L3 Precipitation (1-Month, 0.1 deg) dataset is obtained from the AMSR2 sensor onboard GCOM-W and produced by the Japan Aerospace Exploration Agency (JAXA). GCOM-W was launched by the H-IIA Launch Vehicle No. 21 (H-IIA F21) at 1:39 a.m. on May 18th, 2012 (Japan Standard Time, JST) and inserted into a planned position on the ""A-Train"" orbit. GCOM-W equipped with AMSR2 takes measurements at multiple microwave frequencies and multiple polarizations of weak electromagnetic waves in the microwave band radiated from the Earth’s surface and the atmosphere. AMSR2 has swath of 1450 km and 7 microwave bands. The observation data will enable the creation of long-term trustworthy data sets of global physical amount. The Level 3 process uses as its inputs one day's worth of Level 1B data and Level 2 data and calculates, by taking a simple arithmetic mean, the daily statistical mean value at each grid point in the specified mapping projection method (either equi-rectangular or polar stereo). Furthermore, Level 3 processing takes one month's worth of each geophysical parameter's Level 3 daily statistical mean values and calculates the monthly statistical mean value at each grid point using a simple arithmetic mean in the same way as the daily statistical mean calculation. The statistical means are calculated separately for observations along the satellite's ascending and descending tracks. This dataset includes Month Mean Precipitation (PRC), Standard Deviation (Standard_Deviation), Average Number (Average_Number) and Total Number (Total_Number). Although ""precipitation"" is usually defined as amount of water, which reaches the surface of the earth from atmosphere as rain and/or snow, microwave imager's precipitation products provide amount of rain (surface rainfall). Coverage of the product is global, and unit is [mm/h]. Accuracy of rainfall estimate over land, however tends to be lower than that over the ocean. Method of rainfall estimate used in AMSR2 precipitation product is also applied to ""Global Rainfall Watch"" system, which distributes global rainfall map in near-real-time. Standard_Deviation is standard deviation value for each pixel. This item is only stored in monthly product. Average_Number is the number of valid physical quantity data (except error and missing) which was used to determine ""Geophysical Data"". Total_Number is the number of physical quantity data included in the grid (include valid and invalid). The provided format is HDF5. The Sampling resolution is 0.1degree grid. The statistical period is 1 month. The current version of the product is Version 2. The Version 1 is also available. The projection method is EQR. The generation unit is global." proprietary @@ -6165,26 +6160,26 @@ GLAH02_033 GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033 NSIDC_CPRD STAC Ca GLAH02_033 GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product. proprietary GLAH03_033 GLAS/ICESat L1A Global Engineering Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991863-NSIDC_ECS.umm_json Level-1A global engineering data (GLAH03) include satellite housekeeping data used to calibrate data values for GLA01 and GLA02. proprietary GLAH03_033 GLAS/ICESat L1A Global Engineering Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547514-NSIDC_CPRD.umm_json Level-1A global engineering data (GLAH03) include satellite housekeeping data used to calibrate data values for GLA01 and GLA02. proprietary -GLAH04_033 GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.umm_json Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing. proprietary GLAH04_033 GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.umm_json Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing. proprietary -GLAH05_034 GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000460-NSIDC_ECS.umm_json GLAH05 Level-1B waveform parameterization data include output parameters from the waveform characterization procedure and other parameters required to calculate surface slope and relief characteristics. GLAH05 contains parameterizations of both the transmitted and received pulses and other characteristics from which elevation and footprint-scale roughness and slope are calculated. The received pulse characterization uses two implementations of the retracking algorithms: one tuned for ice sheets, called the standard parameterization, used to calculate surface elevation for ice sheets, oceans, and sea ice; and another for land (the alternative parameterization). Each data granule has an associated browse product. proprietary +GLAH04_033 GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.umm_json Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing. proprietary GLAH05_034 GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549166-NSIDC_CPRD.umm_json GLAH05 Level-1B waveform parameterization data include output parameters from the waveform characterization procedure and other parameters required to calculate surface slope and relief characteristics. GLAH05 contains parameterizations of both the transmitted and received pulses and other characteristics from which elevation and footprint-scale roughness and slope are calculated. The received pulse characterization uses two implementations of the retracking algorithms: one tuned for ice sheets, called the standard parameterization, used to calculate surface elevation for ice sheets, oceans, and sea ice; and another for land (the alternative parameterization). Each data granule has an associated browse product. proprietary -GLAH06_034 GLAS/ICESat L1B Global Elevation Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000445-NSIDC_ECS.umm_json GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product. proprietary +GLAH05_034 GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000460-NSIDC_ECS.umm_json GLAH05 Level-1B waveform parameterization data include output parameters from the waveform characterization procedure and other parameters required to calculate surface slope and relief characteristics. GLAH05 contains parameterizations of both the transmitted and received pulses and other characteristics from which elevation and footprint-scale roughness and slope are calculated. The received pulse characterization uses two implementations of the retracking algorithms: one tuned for ice sheets, called the standard parameterization, used to calculate surface elevation for ice sheets, oceans, and sea ice; and another for land (the alternative parameterization). Each data granule has an associated browse product. proprietary GLAH06_034 GLAS/ICESat L1B Global Elevation Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2033638023-NSIDC_CPRD.umm_json GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product. proprietary -GLAH07_033 GLAS/ICESat L1B Global Backscatter Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.umm_json GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product. proprietary +GLAH06_034 GLAS/ICESat L1B Global Elevation Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000445-NSIDC_ECS.umm_json GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product. proprietary GLAH07_033 GLAS/ICESat L1B Global Backscatter Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.umm_json GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product. proprietary +GLAH07_033 GLAS/ICESat L1B Global Backscatter Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.umm_json GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product. proprietary GLAH08_033 GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549511-NSIDC_CPRD.umm_json GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product. proprietary GLAH08_033 GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.umm_json GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product. proprietary -GLAH09_033 GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product. proprietary GLAH09_033 GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991869-NSIDC_ECS.umm_json GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product. proprietary -GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary +GLAH09_033 GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product. proprietary GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary -GLAH11_033 GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product. proprietary +GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary GLAH11_033 GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991871-NSIDC_ECS.umm_json GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product. proprietary -GLAH12_034 GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH11_033 GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product. proprietary GLAH12_034 GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary -GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH12_034 GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000464-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH14_034 GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000443-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH14_034 GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH15_034 GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary @@ -6690,8 +6685,8 @@ HAQ_TROPOMI_NO2_CONUS_M_L3_2.4 HAQAST Sentinel-5P TROPOMI Nitrogen Dioxide (NO2) HAQ_TROPOMI_NO2_CONUS_S_L3_2.4 HAQAST Sentinel-5P TROPOMI Nitrogen Dioxide (NO2) CONUS Seasonal Level 3 0.01 x 0.01 Degree Gridded Data V2.4 (HAQ_TROPOMI_NO2_CONUS_S_L3) at GES DISC GES_DISC STAC Catalog 2018-06-01 -124.75, 24.5, -66.76, 49.49 https://cmr.earthdata.nasa.gov/search/concepts/C2839237223-GES_DISC.umm_json This product provides level 3 seasonal averages of tropospheric Nitrogen dioxide (NO2) vertical column density derived from the level 2 Tropospheric Monitoring Instrument (TROPOMI) across the Continental United States oversampled to a spatial resolution of 0.01˚ x 0.01˚ (~1 km2) using a consistent algorithm from the European Space Agency (ESA) version 2.4 that can be used for trend analysis of air pollution. The dataset record began in June-August 2018 and continues to the present. This L3 product was developed by the George Washington University Air, Climate and Health Laboratory as part of the NASA Health Air Quality Applied Science Team (HAQAST) using Level 2 version 2.4 TROPOMI NO2 files from the ESA. The TROPOMI instrument on Sentinel-5 Precursor acquires tropospheric NO2 column contents from low Earth orbit (~824 km above ground level) once per day globally at approximately 13:30 local time. NO2 is an air pollutant that adversely affects the human respiratory system and leads to premature mortality. NO2 is also an important precursor for ozone and fine particulates, which also have severe health impacts. In urban areas, the majority of NO2 originates from anthropogenic NOx (=NO+NO2; most NOx is emitted as NO, which rapidly cycles to NO2) emissions during high-temperature fossil fuel combustion. Tropospheric NO2 vertical column contents are qualitatively representative of near-surface NO2 concentrations and NOx emissions in urban/polluted locations. proprietary HAQ_TROPOMI_NO2_GLOBAL_A_L3_2.4 HAQAST Sentinel-5P TROPOMI Nitrogen Dioxide (NO2) GLOBAL Annual Level 3 0.1 x 0.1 Degree Gridded Data Version 2.4 (HAQ_TROPOMI_NO2_GLOBAL_A_L3) at GES DISC GES_DISC STAC Catalog 2019-01-01 -179.5, -60, 179.5, 75 https://cmr.earthdata.nasa.gov/search/concepts/C3087325001-GES_DISC.umm_json This product provides level 3 annual averages of tropospheric Nitrogen dioxide (NO2) vertical column density derived from the level 2 Tropospheric Monitoring Instrument (TROPOMI) across the globe oversampled to a spatial resolution of 0.1˚ x 0.1˚ (~10 km2) using a consistent algorithm from the European Space Agency (ESA) version 2.4 that can be used for trend analysis of air pollution. The dataset record began in January 2019 and continues to the present. This L3 product was developed by the George Washington University Air, Climate and Health Laboratory as part of the NASA Health Air Quality Applied Science Team (HAQAST) using Level 2 version 2.4 TROPOMI NO2 files from the ESA. The TROPOMI instrument on Sentinel-5 Precursor acquires tropospheric NO2 column contents from low Earth orbit (~824 km above ground level) once per day globally at approximately 13:30 local time. NO2 is an air pollutant that adversely affects the human respiratory system and leads to premature mortality. NO2 is also an important precursor for ozone and fine particulates, which also have severe health impacts. In urban areas, the majority of NO2 originates from anthropogenic NOx (=NO+NO2; most NOx is emitted as NO, which rapidly cycles to NO2) emissions during high-temperature fossil fuel combustion. Tropospheric NO2 vertical column contents are qualitatively representative of near-surface NO2 concentrations and NOx emissions in urban/polluted locations. proprietary HAQ_TROPOMI_NO2_GLOBAL_M_L3_2.4 HAQAST Sentinel-5P TROPOMI Nitrogen Dioxide (NO2) GLOBAL Monthly Level 3 0.1 x 0.1 Degree Gridded Data Version 2.4 (HAQ_TROPOMI_NO2_GLOBAL_M_L3) at GES DISC GES_DISC STAC Catalog 2019-01-01 -179.5, -60, 179.5, 75 https://cmr.earthdata.nasa.gov/search/concepts/C3087325222-GES_DISC.umm_json This product provides level 3 monthly averages of tropospheric Nitrogen dioxide (NO2) vertical column density derived from the level 2 Tropospheric Monitoring Instrument (TROPOMI) across the globe oversampled to a spatial resolution of 0.1˚ x 0.1˚ (~10 km2) using a consistent algorithm from the European Space Agency (ESA) version 2.4 that can be used for trend analysis of air pollution. The dataset record began in January 2019 and continues to the present. This L3 product was developed by the George Washington University Air, Climate and Health Laboratory as part of the NASA Health Air Quality Applied Science Team (HAQAST) using Level 2 version 2.4 TROPOMI NO2 files from the ESA. The TROPOMI instrument on Sentinel-5 Precursor acquires tropospheric NO2 column contents from low Earth orbit (~824 km above ground level) once per day globally at approximately 13:30 local time. NO2 is an air pollutant that adversely affects the human respiratory system and leads to premature mortality. NO2 is also an important precursor for ozone and fine particulates, which also have severe health impacts. In urban areas, the majority of NO2 originates from anthropogenic NOx (=NO+NO2; most NOx is emitted as NO, which rapidly cycles to NO2) emissions during high-temperature fossil fuel combustion. Tropospheric NO2 vertical column contents are qualitatively representative of near-surface NO2 concentrations and NOx emissions in urban/polluted locations. proprietary -HAWKEYE_L1_1 SeaHawk-1 HawkEye Level-1A Data, version 1 OB_CLOUD STAC Catalog 2018-12-03 2023-10-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3160685741-OB_CLOUD.umm_json The Hawkeye instrument, flown onboard the SeaHawk CubeSat, was optimized to provide high quality, high resolution imagery (120 meter) of the open ocean, coastal zones, lakes, estuaries and land features. This ability provides a valuable complement to the lower resolution measurements from previous missions like SeaWiFS, MODIS and VIIRS. The SeaHawk CubeSat mission is a partnership between NASA and the University of North Carolina, Wilmington (UNCW), Cloudland Instruments and AAC-Clyde Space and is funded by the Moore Foundation under a grant for the Sustained Ocean Color Observations with Nanosatellites (SOCON). proprietary HAWKEYE_L1_1 SeaHawk HawkEye Level-1 Data, version 1 OB_DAAC STAC Catalog 2018-12-03 -180, 90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2124738110-OB_DAAC.umm_json The Hawkeye instrument, flown onboard the SeaHawk CubeSat, was optimized to provide high quality, high resolution imagery (120 meter) of the open ocean, coastal zones, lakes, estuaries and land features. This ability provides a valuable complement to the lower resolution measurements from previous missions like SeaWiFS, MODIS and VIIRS. The SeaHawk CubeSat mission is a partnership between NASA and the University of North Carolina, Wilmington (UNCW), Cloudland Instruments and AAC-Clyde Space and is funded by the Moore Foundation under a grant for the Sustained Ocean Color Observations with Nanosatellites (SOCON). proprietary +HAWKEYE_L1_1 SeaHawk-1 HawkEye Level-1A Data, version 1 OB_CLOUD STAC Catalog 2018-12-03 2023-10-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3160685741-OB_CLOUD.umm_json The Hawkeye instrument, flown onboard the SeaHawk CubeSat, was optimized to provide high quality, high resolution imagery (120 meter) of the open ocean, coastal zones, lakes, estuaries and land features. This ability provides a valuable complement to the lower resolution measurements from previous missions like SeaWiFS, MODIS and VIIRS. The SeaHawk CubeSat mission is a partnership between NASA and the University of North Carolina, Wilmington (UNCW), Cloudland Instruments and AAC-Clyde Space and is funded by the Moore Foundation under a grant for the Sustained Ocean Color Observations with Nanosatellites (SOCON). proprietary HAWKEYE_L2_OC_2018.0 SeaHawk HawkEye Regional Ocean Color (OC) Data, version 2018.0 OB_DAAC STAC Catalog 2021-04-16 2023-10-27 -180, 90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2124738174-OB_DAAC.umm_json The Hawkeye instrument, flown onboard the SeaHawk CubeSat, was optimized to provide high quality, high resolution imagery (120 meter) of the open ocean, coastal zones, lakes, estuaries and land features. This ability provides a valuable complement to the lower resolution measurements from previous missions like SeaWiFS, MODIS and VIIRS. The SeaHawk CubeSat mission is a partnership between NASA and the University of North Carolina, Wilmington (UNCW), Cloudland Instruments and AAC-Clyde Space and is funded by the Moore Foundation under a grant for the Sustained Ocean Color Observations with Nanosatellites (SOCON). proprietary HAWKEYE_L2_OC_2022.0 SeaHawk-1 HawkEye Level-2 Regional Ocean Color (OC) Data, version 2022.0 OB_CLOUD STAC Catalog 2019-03-21 2023-10-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3160685780-OB_CLOUD.umm_json The Hawkeye instrument, flown onboard the SeaHawk CubeSat, was optimized to provide high quality, high resolution imagery (120 meter) of the open ocean, coastal zones, lakes, estuaries and land features. This ability provides a valuable complement to the lower resolution measurements from previous missions like SeaWiFS, MODIS and VIIRS. The SeaHawk CubeSat mission is a partnership between NASA and the University of North Carolina, Wilmington (UNCW), Cloudland Instruments and AAC-Clyde Space and is funded by the Moore Foundation under a grant for the Sustained Ocean Color Observations with Nanosatellites (SOCON). proprietary HCDN_810_1 Monthly Climate Data for Selected USGS HCDN Sites, 1951-1990, R1 ORNL_CLOUD STAC Catalog 1951-01-01 1990-12-31 -125.15, 24.16, -66.74, 49.39 https://cmr.earthdata.nasa.gov/search/concepts/C2756285170-ORNL_CLOUD.umm_json Time series of monthly minimum and maximum temperature, precipitation, and potential evapotranspiration were derived for 1,469 watersheds in the conterminous United States for which stream flow measurements were also available from the national streamflow database, termed the Hydro-Climatic Data Network (HCDN), developed by Slack et al. (1993a,b). Monthly climate estimates were derived for the years 1951-1990.The climate characteristic estimates of temperature and precipitation were estimated using the PRISM (Daly et al. 1994, 1997) climate analysis system as described in Vogel, et al. 1999.Estimates of monthly potential evaporation were obtained using a method introduced by Hargreaves and Samani (1982) which is based on monthly time series of average minimum and maximum temperature data along with extraterrestrial solar radiation. Extraterrestrial solar radiation was estimated for each basin by computing the solar radiation over 0.1 degree grids using the method introduced by Duffie and Beckman (1980) and then summing those estimates for each river basin. This process is described in Sankarasubramanian, et al. (2001). Revision Notes: This data set has been revised to update the number of watersheds included in the data set and to updated the units for the potential evapotranspiration variable. Please see the Data Set Revisions section of this document for detailed information. proprietary @@ -9192,7 +9187,6 @@ LGB_Gra_traverse_1 Earth gravity field for ice thickness data: LGB traverses 198 LGB_Ht_traverse_1 Ice sheet surface elevation data: LGB traverses 1989-95 AU_AADC STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313577-AU_AADC.umm_json The ANARE Lambert Glacier Basin (LGB) series of oversnow traverses were conducted during the period 1989-95. Field operations were carried out along the proximity of the 2500 m elevation contour around the interior basin between Mawson and Davis stations. The main traverse route covered some 2014 km of track from LGB00 at 68.6543 S, 61.1201 E, and LGB72 at 69.9209 S, 76.4933 E. An offset route (50 km upslope) parallels the main traverse track around the western half of the basin. Raw data were stored in binary files containing pressure, temperature, navigational position and a variety of other parameters at an approximately 10 m spacing associated with each 2 km long section of track. Processed data were stored as 2 km averaged ice sheet surface elevation spreadsheet files (MS Excel). The data available at the url below are stored in various formats. Summary data (2 km spatial average) can be obtained from CRC Research Note No. 27 'Ice Thicknesses and Surface and Bedrock Elevations from the Lambert Glacier Basin Traverses 1989-95'. This work was completed as part of ASAC projects 3 and 2216. proprietary LGB_Vel_traverse_1 Ice sheet surface velocity data: LGB traverses 1989-95 AU_AADC STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313578-AU_AADC.umm_json The ANARE Lambert Glacier Basin (LGB) series of oversnow traverses were conducted during the period 1989-95. Field operations were carried out along the proximity of the 2500 m elevation contour around the interior basin between Mawson and Davis stations. The main traverse route covered some 2014 km of track from LGB00 at 68.6543 S, 61.1201 E, and LGB72 at 69.9209 S, 76.4933 E. Ice sheet surface velocities were obtained for 73 sites known as Ice Movement Stations (IMS), spaced approximately 30 km apart between LGB00 and LGB72. Raw data were recorded in Wild-Leitz (WM102) or Leica-Wild (200-series) proprietary mode including data, observation, almanac and ephemeris files. Processed data were stored in proprietary software output modes and has been written to standard spreadsheet (MS Excel) files for sharing with downstream processing programs. The data available at the url below are stored in various formats. Summary data (2 km spatial average) can be obtained from CRC Research Note No. 23, 'Ice Sheet Surface Velocities along the Lambert Basin Traverse Route'. Documents providing archive details of the logbooks are available for download from the provided URL. This work was completed as part of ASAC projects 3 and 2216. proprietary LGP_2 Latitudinal Gradient Project - Australian contributions AU_AADC STAC Catalog 1989-01-01 2009-12-31 168, -86, 180, -72 https://cmr.earthdata.nasa.gov/search/concepts/C1214313600-AU_AADC.umm_json This record relates to the Australian component of the Latitudinal Gradient Project. The LGP is largely a New Zealand, US and Italian venture, but a small contribution has been made by Australian scientists. The Australian component of this work was completed as part of ASAC projects 2361 and 2682 (ASAC_2361, and ASAC_2682). Data from this project were entered into the herbarium access database, which has been linked to this record. The list below contains details of where and when samples were collected, and also the type of sample and the method of sampling. Cape Hallett and vicinity (2000, 2004): Biodiversity assessment of terrestrial plants (mosses, lichens); Invertebrate collections (mites, Collembola); plant ecology and community analysis; photosynthetic physiology of mosses and lichens; molecular genetics of mosses and lichens. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, field laboratory experiments for physiological studies. Dry Valleys: Taylor Valley (1989, 1996), Garwood Valley (2001), Granite Harbour (1989; 1994, 1996) - plant ecology; plant physiology; biodiversity; invertebrate collections; molecular genetics of mosses. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, field laboratory experiments for physiological studies. Beaufort Island (1996) - plant biodiversity; molecular genetics of mosses. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, laboratory studies for molecular genetics. Darwin Glacier (1994): plant biodiversity; molecular genetics of invertebrates and mosses (random sampling for biodiversity; laboratory studies of invertebrate and moss molecular genetics). Project objectives: 1. Investigate the distribution of bryophytes and lichens in continental Antarctica 1a). to test the null hypothesis that species diversity does not change significantly with latitude; 1b). to explore the relationships between species and key environmental attributes including latitude, distance from the coast, temperature, substrate, snow cover, age of ice-free substrate. 2. To continue to participate in the Ross Sea Sector Latitudinal Gradient Project and develop an Australian corollary in the Prince Charles Mountains, involving international collaborators, incorporating the first two objectives of this project. 3. To develop an international collaborative biodiversity and ecophysiological program in the Prince Charles Mountains that will provide a parallel N-S latitude gradient study to mirror the LGP program in the Ross Sea region as part of the present RISCC cooperative program (to be superseded by the EBA (Evolution and Biodiversity of Antarctica) program) to address the above objectives. Taken from the 2008-2009 Progress Report: Progress against objectives: Continuing identification of moss and lichen samples previously collected from Cape Hallett, Granite Harbour and Darwin Glacier region. Lecidea s.l. lichens currently being studied in Austria by PhD student. Field work in Dry Valleys significantly curtailed by adverse weather. Field work planned for Darwin Glacier region and McMurdo Dry Valleys, particularly Taylor Valley and Granite Harbour region was severely curtailed due to adverse weather, helicopter diversions due to a Medical Evacuation, and other logistic constraints. 10 days of field time were lost. Limitations on field travel in Darwin Glacier region restricted the field work to a biologically depauperate region. The Prince Charles Mountains N-S transect, the only continental transect possibility for comparison with the Ross Sea area, unfortunately appears to have been abandoned through lack of logistic support. Taken from the 2009-2010 Progress Report: Identification of samples collected from AAT and Ross Sea Region continued during the year, interrupted significantly by the packing of the collection and transfer of specimens to the Tasmanian Herbarium. Work is now proceeding at the Herbarium with sorting, databasing and incorporation of packets into the Herbarium collection. The merging of the collection provides long-term security of curation and significantly boosts the cryptogam collections (35000 numbers) of the Tasmanian Herbarium. proprietary -LGRIP30_001 Landsat-Derived Global Rainfed and Irrigated-Cropland Product 30 m V001 LPDAAC_ECS STAC Catalog 2014-01-01 2017-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2592845930-LPDAAC_ECS.umm_json The Landsat-Derived Global Rainfed and Irrigated-Cropland Product (LGRIP) provides high resolution, global cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data (GFSAD) project, LGRIP maps the world’s agricultural lands by dividing them into irrigated and rainfed croplands, and calculates irrigated and rainfed areas for every country in the world. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2014-2017 time period to create a nominal 2015 product. Each LGRIP 30 meter resolution GeoTIFF file contains a contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation), irrigated cropland (cropland that had at least one irrigation during the crop growing period), non-cropland, and water bodies over a 10° by 10° area, as well as an accuracy assessment of the product. A low-resolution browse image is also available. proprietary LIDA Lidar Data from Brazil CEOS_EXTRA STAC Catalog 1972-02-23 -45, -23, -45, -23 https://cmr.earthdata.nasa.gov/search/concepts/C2227456105-CEOS_EXTRA.umm_json The FISAT home page on the WWW is http://www.laser.inpe.br/fisat/ . This set contains data obtained at the location of Sao Jose dos Campos (23 degrees S, 45 degrees W), only. >From 1972 to 1981 only night-time data of the Lidar backscatter return at 589.0 nm are available. The periodicity of the data is irregular. Generally short-duration measurements (less than 2 hours) are available at about one measurerent per week. Long-duration data covering most of the night are available in a few campaigns. Data are also given, in processed form, providing aerosol backscatter ratio from 15 to 30 km altitude and sodium density from 75 to 105 km altitude. >From 1981 to 1993, campaigns of sodium measurements taken during the day, including several diurnal cycles are also available. >From 1983 to the present day a new powerful laser at 593.0 nm provides the Rayleigh scatter profiles giving the atmospheric density and temperatures from 35 to nearly 70 km altitude. Data are currently obtained, approximately, on a weekly basis. proprietary LIDAR_0 Pigment measurements from 1989 and 1990 in the Gulf of St Lawrence OB_DAAC STAC Catalog 1989-09-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360430-OB_DAAC.umm_json Pigment measurements from 1989 and 1990 in the Gulf of St Lawrence. proprietary LIDAR_FOREST_CANOPY_HEIGHTS_1271_1 CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008 ORNL_CLOUD STAC Catalog 2004-10-03 2004-11-08 -161.41, -55.45, 179.89, 69.29 https://cmr.earthdata.nasa.gov/search/concepts/C2343105406-ORNL_CLOUD.umm_json This data set provides estimates of forest canopy height derived from the Geoscience Laser Altimeter System (GLAS) LiDAR instrument that was aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite. A global GLAS waveform data set (n=12,336,553) from collection periods between October 2004 and March 2008 was processed to obtain canopy height estimates.Estimates of GLAS maximum canopy height and crown-area-weighted Lorey's height are provided for 18,578 statistically-selected globally distributed forested sites in a point shapefile. Country is included as a site attribute.Also provided is the average canopy height for the forested area of each country, plus the number of GLAS data footprints (shots), number of selected sample sites, and estimates of the variance for each country. proprietary @@ -9452,6 +9446,8 @@ MACPEX_TraceGas_AircraftInSitu_WB57_Data_1 MACPEX WB-57 Aircraft In-situ Trace G MACPEX_Water_AircraftInSitu_WB57_Data_1 MACPEX WB-57 Aircraft In-situ Water Data LARC_ASDC STAC Catalog 2011-03-18 2011-04-27 -107, 15, -80, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2218601461-LARC_ASDC.umm_json MACPEX_Water_AircraftInSitu_WB57_Data is the in-situ water data collection during the Mid-latitude Airborne Cirrus Properties Experiment (MACPEX). Data was collected by the Harvard Water Vapor (HWV), Closed-path Laser Hygrometer (CLH), Diode Laser Hygrometer (DLH), JPL Laser Hygrometer (JLH), Unmanned Aerial System Laser Hygrometer (ULH), Fast In-situ Stratospheric Hygrometer (FISH), NOAA Chemical Ionization Mass Spectrometer (CIMS), and the Aircraft Laser Infrared Absorption Spectrometer (ALIAS). Data collection for this product is complete. The MACPEX mission was an airborne field campaign that deployed from March 18th to April 26th, 2011. MACPEX sought to investigate cirrus cloud properties and the processes that affect their impact on radiation. The campaign conducted science flights using the NASA WB-57 aircraft based out of Ellington Airfield, Texas. Science flights were focused on the central North America vicinity, with an emphasis over the Southern Great Plains atmospheric observatory (established by the Department of Energy’s (DoE) Atmospheric Radiation Measurement (ARM) user facility) site in Oklahoma. MACPEX was a joint effort between NASA, the NOAA Earth System Research Laboratory (ESRL), the National Center for Atmospheric Research (NCAR), and several U.S. universities. The WB-57 contained a comprehensive instrument payload for detailed in-situ measurements that were targeted to answer MACPEX’s four major science questions. The first science question that MACPEX explored was how prevalent the smaller crystals are in cirrus clouds, and how important they are for extinction, radiative forcing, and radiative heating. MACPEX also sought to understand how cirrus microphysical properties (particle size distribution, ice crystal habit, extinction, ice water content) are related to the dynamical forcing driving cloud formation. Researchers also investigated how cirrus microphysical properties are related to aerosol loading and composition, including the abundance of heterogeneous ice nuclei. Lastly, this campaign examined how cirrus microphysical properties evolve through the lifecycles of the clouds, and the role radiatively driven dynamical motions play. In addition to the in-situ measurements, four flights were coordinated to validate the NASA EOS/A-Train satellite observations. NOAA also launched balloon sondes and ozonesondes, which were used to acquire data about the frost point and water vapor in the atmosphere. The balloon sondes and ozonesondes also acquired pressure, temperature, and humidity data, as well as measurements regarding the ozone in the atmosphere. proprietary MACQ_NO2_4 Macquarie Island nitrogen dioxide AU_AADC STAC Catalog 1996-01-01 158.75793, -54.78485, 158.96118, -54.47483 https://cmr.earthdata.nasa.gov/search/concepts/C1214313627-AU_AADC.umm_json "Slant column densities of stratospheric nitrogen dioxide (NO2) determined from spectroscopic measurements of zenith scattered twilight at wavelengths from 430-485 nanometres. These data are provided by the NDACC (Network for the Detection of Atmospheric Composition Change) on an annual basis and then stored at the AADC. Only data that are two years old are made available. Further information about the dataset is available from the URL given below. This work was performed as part of ASAC project 2244, but this project has since been replaced by AAS project 4193, ""Long-term measurements of atmospheric nitrogen dioxide at Macquarie Island"". The fields in this dataset are: NO2 slant column density (molecules/cm**2) Error in NO2 slant column density (molecules/cm**2) NO2 Air Mass Factor (AMF) NO2 vertical column density (molecules/cm**2) Year of Observation (UT) Month (UT) Day of month (UT) Hour (UT) Minutes (UT) Latitude of observation site; decimal degrees Longitude of observation site; decimal degrees Elevation of site; meters Solar zenith angle at time of observation; decimal degrees Taken from the 2008-2009 Progress Report: Public summary of the season progress: Ground-based measurements of nitrogen dioxide (NO2), one of the key trace gases in the atmosphere, have been made at Macquarie Island since 1996 and span now more than 12 years. These long-term observations made at Macquarie Island help us to bridge the gap between measurements made in the Antarctic and at mid-latitudes. The observations during the 2008/2009 season went smoothly and we have no problems to report." proprietary MACTWP_mean_1 Multisensor Advanced Climatology Total Liquid Water Path L3 Monthly 1 degree x 1 degree V1 (MACTWP_mean) at GES DISC GES_DISC STAC Catalog 1988-01-01 2016-12-31 180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1368522053-GES_DISC.umm_json The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP) data set contains monthly 1.0-degree ocean-only estimates of cloud liquid water path (MACLWP_mean), total water path (MACTWP_mean) which includes both cloud and rain water, and monthly climatologies of cloud liquid water path diurnal cycle amplitudes and phases (MACLWP_diurnal). The MACTWP_mean field can also be used as a quality-control screen for the MACLWP_mean field as discussed in Elsaesser et al. (2017), where uncertainty increases as the ratio of cloud to total water path increases. The MAC-LWP algorithm uses as input the Remote Sensing Systems (RSS) Version 7 0.25 degree-resolution retrieval products (produced using the SSM/I, AMSR-E, TMI, AMSR-2, GMI, SSMIS, and WindSat satellite sensors), and performs a bias correction on all input RSS cloud water path products based on AMSR-E matchups to clear-sky MODIS scenes. The MAC-LWP algorithm ensures that spurious trends and variability in the cloud fields arising from drifting satellite overpass times are mitigated by simultaneously solving for the monthly average cloud and total water paths and monthly-mean diurnal cycles, as discussed in O’Dell et al. (2008). Additional details on the algorithm and data fields can be found in Elsaesser et al. (2017). proprietary +MAIA_ANC_SURFACEMONITOR_PM_2.5_SPECIES_C01 Ancillary speciated PM data from the MAIA Surface Monitor Network LARC_ASDC STAC Catalog 2021-01-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3271469628-LARC_ASDC.umm_json The MAIA Surface Monitor Stage 0 files are an ancillary dataset containing processed particulate matter (PM) measurements collected from a global in-situ surface monitoring network. The files are generated by the MAIA surface monitoring subsystem software at NASA’s Atmospheric Science Data Center (ASDC). proprietary +MAIA_ANC_SURFACEMONITOR_PM_TOTAL_C01 Ancillary total PM data from the MAIA Surface Monitor Network LARC_ASDC STAC Catalog 2021-01-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3271469675-LARC_ASDC.umm_json The MAIA Surface Monitor Stage 0 files are an ancillary dataset containing processed particulate matter (PM) measurements collected from a global in-situ surface monitoring network. The files are generated by the MAIA surface monitoring subsystem software at NASA’s Atmospheric Science Data Center (ASDC). proprietary MALINA_0 Malina Oceanographic Expedition OB_DAAC STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360471-OB_DAAC.umm_json The MALINA oceanographic campaign was conducted during summer 2009 to investigate the carbon stocks and the processes controlling the carbon fluxes in the Mackenzie River estuary and the Beaufort Sea. During the campaign, an extensive suite of physical, chemical and biological variables were measured across seven shelf–basin transects (south–north) to capture the meridional gradient between the estuary and the open ocean. Key variables such as temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured onboard the Canadian research icebreaker CCGS Amundsen and from a barge in shallow coastal areas or for sampling within broken ice fields. Massicotte et al., 2021 (https://doi.org/10.17882/75345) proprietary MAM03S0_002 MODIS/Aqua Geolocation Fields 1km 5-Min 1A Swath Subset along MLS V002 (MAM03S0) at GES DISC GES_DISC STAC Catalog 2004-08-08 2008-01-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350971-GES_DISC.umm_json This is the MODIS/Aqua subset along the Microwave Limb Sounder (MLS) field of view track. The goal of the subset is to select and return MODIS data that are within +-100 km across the MLS track. I.e. the resultant MODIS subset swath is about 200 km cross-track. Thus, MAM03S0 cross-track width is 201 pixels. Along-track, all MODIS pixels from the original product are preserved. In the standard product, geolocation fields are calculated for each 1 km MODIS Instantaneous Field of Views (IFOV) for all orbits daily. The locations and ancillary information corresponds to the intersection of the centers of each IFOV from 10 detectors in an ideal 1 km band on the Earth's surface. A digital terrain model is used to model the Earth's surface. The main inputs are the spacecraft attitude and orbit, the instrument telemetry and the digital elevation model. The geolocation fields include geodetic Latitude, Longitude, surface height above geoid, solar zenith and azimuth angles, satellite zenith and azimuth angles, and a land/sea mask for each 1 km sample. Additional information is included in the header to enable the calculation of the approximate location of the center of the detectors of any of the 36 MODIS bands. This product is used as input by a large number of subsequent MODIS products, particularly the products produced by the Land team. (The shortname for this product is MAM03S0). proprietary MAM04S0_002 MODIS/Aqua Aerosol 5-Min L2 Swath Subset 10km along MLS V002 (MAM04S0) at GES DISC GES_DISC STAC Catalog 2004-08-08 2008-01-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350972-GES_DISC.umm_json This is the MODIS/Aqua subset along MLS field of view track. The goal of the subset is to select and return MODIS data that are within +-100 km across the MLS track. I.e. the resultant MODIS subset swath is sought to be about 200 km cross-track. However, the original MYD04_L2 has 10-km pixels. Thus, MAM04S0 cross-track width is 21 pixels, and the resultant cross-track swath width is about 200 km. Along-track, all MODIS pixels from the original product are preserved. In the stardard product, the MODIS level-2 atmospheric aerosol product provides retrieved ambient aerosol optical properties (e.g., optical thickness and size distribution), mass concentration, look-up table derived reflected and transmitted fluxes, as well as quality assurance and other ancillary parameters, globally over ocean and near globally over land. (The shortname for this product is MAM04S0). proprietary @@ -9698,32 +9694,54 @@ MERGED_S3_OLCI_L3m_ILW_4 Merged Sentinel-3A and Sentinel-3B OLCI Regional Mapped MERGED_TP_J1_OSTM_OST_ALL_V52_5.2 Integrated Multi-Mission Ocean Altimeter Data for Climate Research complete time series Version 5.2 POCLOUD STAC Catalog 1992-09-25 -180, -66, 180, 66 https://cmr.earthdata.nasa.gov/search/concepts/C2901524183-POCLOUD.umm_json The Integrated Multi-Mission Ocean Altimeter Sea Surface Height (SSH) Version 5.2 dataset provides level 2 along track sea surface height anomalies (SSHA) from the TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6A missions geo-referenced to a mean reference orbit. It is produced by NASA Sea Surface Height (NASA-SSH) project investigators at Goddard Space Flight Center and Jet Propulsion Laboratory with support from NASA’s Physical Oceanography program, and was developed originally as an Earth System Data Record (ESDR) under the Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, which supported forward processing and incremental refinements through version 5.1 (released in April 2022).
Geophysical Data Records (GDRs) from each altimetry mission were interpolated to a common reference orbit with biases and cross-calibrations applied so that the derived SSHA are consistent between satellites to form a single homogeneous climate data record. The entire multi-mission data record covers the period from September 1992 to present; it is extended to include new observations approximately once each quarter. The previous release (version 5.1) integrated Jason-3 data and applied revised internal tides and pole tide across missions (GDR_F standard). The current release (version 5.2) includes the following revisions: a) GSFC std2006_cs21 orbit for all missions, b) GOT5.1 ocean tide model, c) TOPEX/Poseidon GDR_F data, d) Sentinel-6 LR version F08 data, e) Jason-3 re-calibrated radiometer wet troposphere correction. More information about the data content and derivation can be found in the v5.2 User’s Handbook (https://doi.org/10.5067/ALTUG-TJ152).
Please note that this collection is the same data as https://doi.org/10.5067/ALTCY-TJA52 but with all cycles included in one netCDF file. proprietary MERGED_TP_J1_OSTM_OST_CYCLES_V52_5.2 Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.2 POCLOUD STAC Catalog 1992-09-25 -180, -66, 180, 66 https://cmr.earthdata.nasa.gov/search/concepts/C2901523432-POCLOUD.umm_json The Integrated Multi-Mission Ocean Altimeter Sea Surface Height (SSH) Version 5.2 dataset provides level 2 along track sea surface height anomalies (SSHA) for 10-day cycles from the TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6A missions geo-referenced to a mean reference orbit. It is produced by NASA Sea Surface Height (NASA-SSH) project investigators at Goddard Space Flight Center and Jet Propulsion Laboratory with support from NASA’s Physical Oceanography program, and was developed originally as an Earth System Data Record (ESDR) under the Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, which supported forward processing and incremental refinements through version 5.1 (released in April 2022).
Geophysical Data Records (GDRs) from each altimetry mission were interpolated to a common reference orbit with biases and cross-calibrations applied so that the derived SSHA are consistent between satellites to form a single homogeneous climate data record. The entire multi-mission data record covers the period from September 1992 to present; it is extended to include new observations approximately once each quarter. The previous release (version 5.1) integrated Jason-3 data and applied revised internal tides and pole tide across missions (GDR_F standard). The current release (version 5.2) includes the following revisions: a) GSFC std2006_cs21 orbit for all missions, b) GOT5.1 ocean tide model, c) TOPEX/Poseidon GDR_F data, d) Sentinel-6 LR version F08 data, e) Jason-3 re-calibrated radiometer wet troposphere correction. More information about the data content and derivation can be found in the v5.2 User’s Handbook (https://doi.org/10.5067/ALTUG-TJ152).
Please note that this collection contains the same data as https://doi.org/10.5067/ALTTS-TJA52, re-organized into one netCDF file per cycle for convenience. proprietary MERGED_TP_J1_OSTM_OST_GMSL_ASCII_V51_5.1 Global Mean Sea Level Trend from Integrated Multi-Mission Ocean Altimeters TOPEX/Poseidon, Jason-1, OSTM/Jason-2, and Jason-3 Version 5.1 POCLOUD STAC Catalog 1992-09-01 -180, -66, 180, 66 https://cmr.earthdata.nasa.gov/search/concepts/C2205556193-POCLOUD.umm_json This dataset contains the Global Mean Sea Level (GMSL) trend generated from the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.1. The GMSL trend is a 1-dimensional time series of globally averaged Sea Surface Height Anomalies (SSHA) from TOPEX/Poseidon, Jason-1, OSTM/Jason-2, and Jason-3 that covers September 1992 to present with a lag of up to 4 months. The data are reported as variations relative to a 20-year TOPEX/Jason collinear mean. Bias adjustments and cross-calibrations were applied to ensure SSHA data are consistent across the missions; Glacial Isostatic Adjustment (GIA) was also applied. The data are available as a table in ASCII format. Changes between the version 4.2 and version 5.x releases are described in detail in the user handbook. proprietary +MERIS_L1_FRS_4 ENVISAT MERIS Level-1B Full Resolution, Full Swath (FRS) Data, version 4 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778834-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L1_FRS_4 ENVISAT MERIS Full Resolution, Full Swath (FRS) Data, version 4 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1569867387-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L1_RR_4 ENVISAT MERIS Reduced Resolution (RR) Data, version 4 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1569867388-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L1_RR_4 ENVISAT MERIS Level-1B Reduced Resolution (RR) Data, version 4 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778839-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L2_FRS_IOP_2022.0 ENVISAT MERIS Level-2 Regional Full Resolution, Full Swath (FRS) Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281901057-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L2_FRS_IOP_R2022.0 ENVISAT MERIS Regional Full Resolution, Full Swath (FRS) Inherent Optical Properties (IOP) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672029-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L2_FRS_OC_2022.0 ENVISAT MERIS Level-2 Regional Full Resolution, Full Swath (FRS) Ocean Color (OC) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778845-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L2_FRS_OC_R2022.0 ENVISAT MERIS Regional Full Resolution, Full Swath (FRS) Ocean Color (OC) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672030-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L2_ILW_4 ENVISAT MERIS Regional Inland Waters (ILW) Data, version 4 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2954423359-OB_DAAC.umm_json The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site. proprietary +MERIS_L2_RR_IOP_2022.0 ENVISAT MERIS Level-2 Regional Reduced Resolution (RR) Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281901072-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L2_RR_IOP_R2022.0 ENVISAT MERIS Regional Reduced Resolution (RR) Inherent Optical Properties (IOP) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672032-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L2_RR_OC_2022.0 ENVISAT MERIS Level-2 Regional Reduced Resolution (RR) Ocean Color (OC) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778850-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L2_RR_OC_R2022.0 ENVISAT MERIS Regional Reduced Resolution (RR) Ocean Color (OC) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672033-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3b_CHL_2022.0 ENVISAT MERIS Level-3 Global Binned Chlorophyll (CHL) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778854-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_CHL_R2022.0 ENVISAT MERIS Global Binned Chlorophyll (CHL) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672034-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_CYANTC_5.0 ENVISAT MERIS Global Binned CyAN Project, True Color (TC) Data, version 5.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561580570-OB_DAAC.umm_json Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data. proprietary MERIS_L3b_CYAN_5.0 ENVISAT MERIS Global Binned Cyanobacteria Index (CI) Data, version 5.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561580568-OB_DAAC.umm_json Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data. proprietary +MERIS_L3b_FLH_2022.0 ENVISAT MERIS Level-3 Global Binned Fluorescence Line Height (FLH) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778857-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_ILW_4 ENVISAT MERIS Regional Binned Inland Waters (ILW) Data, version 4 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2954423607-OB_DAAC.umm_json The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site. proprietary +MERIS_L3b_IOP_2022.0 ENVISAT MERIS Level-3 Global Binned Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778868-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_IOP_R2022.0 ENVISAT MERIS Global Binned Inherent Optical Properties (IOP) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672035-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3b_KD_2022.0 ENVISAT MERIS Level-3 Global Binned Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778872-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_KD_R2022.0 ENVISAT MERIS Global Binned Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672036-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3b_PAR_2022.0 ENVISAT MERIS Level-3 Global Binned Photosynthetically Active Radiation (PAR) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778878-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_PAR_R2022.0 ENVISAT MERIS Global Binned Photosynthetically Available Radiation (PAR) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672040-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3b_PIC_2022.0 ENVISAT MERIS Level-3 Global Binned Particulate Inorganic Carbon (PIC) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778885-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_PIC_R2022.0 ENVISAT MERIS Global Binned Particulate Inorganic Carbon (PIC) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672041-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3b_POC_2022.0 ENVISAT MERIS Level-3 Global Binned Particulate Organic Carbon (POC) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778891-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_POC_R2022.0 ENVISAT MERIS Global Binned Particulate Organic Carbon (POC) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672042-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3b_RRS_2022.0 ENVISAT MERIS Level-3 Global Binned Remote-Sensing Reflectance (RRS) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778899-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3b_RRS_R2022.0 ENVISAT MERIS Global Binned Remote-Sensing Reflectance (RRS) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672043-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3m_CHL_2022.0 ENVISAT MERIS Level-3 Global Mapped Chlorophyll (CHL) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778904-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_CHL_R2022.0 ENVISAT MERIS Global Mapped Chlorophyll (CHL) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672044-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_CYANTC_5.0 ENVISAT MERIS Global Mapped CyAN Project, True Color (TC) Data, version 5.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561580577-OB_DAAC.umm_json Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data. proprietary MERIS_L3m_CYAN_5.0 ENVISAT MERIS Global Mapped Cyanobacteria Index (CI) Data, version 5.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561580575-OB_DAAC.umm_json Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data. proprietary +MERIS_L3m_FLH_2022.0 ENVISAT MERIS Level-3 Global Mapped Fluorescence Line Height (FLH) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778906-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_ILW_4 ENVISAT MERIS Regional Mapped Inland Waters (ILW) Data, version 4 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2954423744-OB_DAAC.umm_json The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site. proprietary +MERIS_L3m_IOP_2022.0 ENVISAT MERIS Level-3 Global Mapped Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778909-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_IOP_R2022.0 ENVISAT MERIS Global Mapped Inherent Optical Properties (IOP) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672045-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3m_KD_2022.0 ENVISAT MERIS Level-3 Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778916-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_KD_R2022.0 ENVISAT MERIS Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672046-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3m_PAR_2022.0 ENVISAT MERIS Level-3 Global Mapped Photosynthetically Active Radiation (PAR) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778919-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_PAR_R2022.0 ENVISAT MERIS Global Mapped Photosynthetically Available Radiation (PAR) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672047-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3m_PIC_2022.0 ENVISAT MERIS Level-3 Global Mapped Particulate Inorganic Carbon (PIC) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778924-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_PIC_R2022.0 ENVISAT MERIS Global Mapped Particulate Inorganic Carbon (PIC) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672049-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3m_POC_2022.0 ENVISAT MERIS Level-3 Global Mapped Particulate Organic Carbon (POC) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778927-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_POC_R2022.0 ENVISAT MERIS Global Mapped Particulate Organic Carbon (POC) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672050-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary +MERIS_L3m_RRS_2022.0 ENVISAT MERIS Level-3 Global Mapped Remote-Sensing Reflectance (RRS) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281778928-OB_CLOUD.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L3m_RRS_R2022.0 ENVISAT MERIS Global Mapped Remote-Sensing Reflectance (RRS) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2210672051-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L4b_GSM_R2022.0 ENVISAT MERIS 4B Global Binned Garver-Siegel-Maritorena Model (GSM) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2802700386-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary MERIS_L4m_GSM_R2022.0 ENVISAT MERIS 4M Global Mapped Garver-Siegel-Maritorena Model (GSM) Data, version R2022.0 OB_DAAC STAC Catalog 2002-03-21 2012-05-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2802700390-OB_DAAC.umm_json MERIS (Medium Resolution Imaging Spectrometer) is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by ground command. The instrument scans the Earth's surface by the so called 'push-broom' method. Linear CCD arrays provide spatial sampling in the across-track direction, while the satellite's motion provides scanning in the along-track direction. MERIS is designed so that it can acquire data over the Earth whenever illumination conditions are suitable. The instrument's 68.5-degree field-of-view around nadir covers a swath width of 1150 km. This wide field of view is shared between five identical optical modules arranged in a fan shape configuration. proprietary @@ -11575,8 +11593,8 @@ OMAEROZ_003 OMI/Aura Aerosol product Multi-wavelength Algorithm Zoomed 1-Orbit L OMAERO_003 OMI/Aura Multi-wavelength Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V003 (OMAERO) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966755-GES_DISC.umm_json The Level-2 Aura Ozone Monitoring Instrument (OMI) Aerosol Product (OMAERO) is now available from NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access. This is the second public release of version 003. The data was re-processed in late 2011 using an improved algorithm (processing version 1.2.3.1). After some quick validation the reprocessed data was released to the public in March 2012. The shortname for this Level-2 Aerosol Product is OMAERO_V003. There are two Level-2 Aura OMI aerosol products OMAERUV and OMAERO. The OMAERUV product uses the near-UV algorithm. The OMAERO product is based on the multi-wavelength algorithm and that uses up to 20 wavelength bands between 331 nm and 500 nm. OMAERO retrieval algorithm is developed by the KNMI OMI Team Scientists. Drs. Deborah Stein-Zweers, Martin Sneep and Pepijn Veefkind are now the key investigators of this product. The OMAERO product contains Aerosol Optical Depths, Single Scattering Albedo, and other ancillary and geolocation information. The OMAERO files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERO data product is about 6 Mbytes. proprietary OMAEROe_003 OMI/Aura Multi-wavelength Aerosol Optical Depth and Single Scattering Albedo L3 1 day Best Pixel in 0.25 degree x 0.25 degree V3 (OMAEROe) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136062-GES_DISC.umm_json The OMI science team produces this Level-3 Aura/OMI Global Aerosol Data Products OMAEROe (0.25deg Lat/Lon grids). The OMAEROe product selects best aerosol value from the Level2G good quality data that are reported in each grid, based on the multi-wavelength algorithm that uses up to 20 wavelength bands between 331 nm and 500 nm. The selection criteria is based on the shortest optical path length (secant of solar zenith angle + secant of viewing zenith angle). The OMAEROe files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMAEROe data product is about 7 Mbytes. (The shortname for this Level-3 Global Gridded Aerosol Product is OMAEROe) proprietary OMAERUVG_003 OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo Daily L2 Global Gridded 0.25 degree x 0.25 degree V3 (OMAERUVG) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136097-GES_DISC.umm_json This Level-2G daily global gridded product OMAERUVG is based on the pixel level OMI Level-2 AERUV product OMAERUV. This Level-2G daily global gridded product OMAERUVG is based on the pixel level OMI Level-2 Aerosol product OMAERUV. OMAERUVG data product is a special Level-2 gridded product where pixel level products are binned into 0.25x0.25 degree global grids. It contains the data for all scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved without averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMAERUVG files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits mapped on the Global 0.25x0.25 deg Grids. The maximum file size for the OMAERUVG data product is about 50 Mbytes. proprietary -OMAERUV_003 OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000120-OMINRT.umm_json The OMI/Aura level-2 near UV Aerosol data product 'OMAERUV', recently re-processed using an enhanced algorithm, is now released (April 2012) to the public. The data is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), http://disc.gsfc.nasa.gov/Aura/OMI/omaeruv_v003.shtml NASA Aura satellite sensors are tracking important atmospheric pollutants from space since its launch in July, 2004. The Ozone Monitoring Instrument(OMI), one of the four Aura satellite sensors with its 2600 km viewing swath width provides daily global measurements of four important US Environmental Protection Agency criteria pollutants (Tropospheric ozone, Nitrogen dioxide,Sulfur dioxide and Aerosols from biomass burning and industrial emissions, HCHO, BrO, OClO and surface UV irradiance. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). The Level-2 OMI Aerosol Product OMAERUV from the Aura-OMI is now available from NASAs GSFC Earth Sciences (GES) Data and Information Services Center (DISC) for public access. OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Absorption and Aerosol Extinction Optical Depths, and Single Scattering Albedo at three different wavelengths (354, 388 and 500 nm), Aerosol Index, and other ancillary and geolocation parameters, in the OMI field of view (13x24 km). Another standard OMI aerosol product is OMAERO, that is based on the KNMI multi-wavelength spectral fitting algorithm. OMAERUV files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 6 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A short OMAERUV Readme Document that includes brief algorithm description and currently known data quality issues is provided by the OMAERUV Algorithm lead (see http://disc.gsfc.nasa.gov/Aura/OMI/omaeruv_v003.shtml) For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . OMAERUV Data Groups and Parameters: The OMAERUV data file contains a swath which consists of two groups: Data fields: Total Aerosol Optical Depth (extinction optical depth) and Aerosol Absorption Optical Depths (at 354, 388 and 500 nm), Single Scattering Albedo, UV Aerosol Index, Visible Aerosol Index, and other intermediate and ancillary parameters (e.g. Estimates of Aerosol Total Extinction and Absorption Optical Depths and Single Scattering Albedo at five atmospheric levels, Aerosol Type, Aerosol Layer Height, Normalized Radiance, Lambert equivalent Reflectivity, Surface Albedo, Imaginary Component of Refractive Index) and Data Quality Flags. Geolocation Fields: Latitude, Longitude, Time(TAI93), Seconds, Solar Zenith Angles, Viewing Zenith Angles, Relative Azimuth Angle, Terrain Pressure, Ground Pixel Quality Flags. For the full set of Aura products available from the GES DISC, please see the link below. http://disc.sci.gsfc.nasa.gov/Aura/ Atmospheric Composition data from Aura and other satellite sensors can be ordered from the following sites: http://disc.sci.gsfc.nasa.gov/acdisc/ proprietary OMAERUV_003 OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V003 (OMAERUV) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966768-GES_DISC.umm_json The Aura Ozone Monitoring Instrument level-2 near UV Aerosol data product 'OMAERUV', recently re-processed using an enhanced algorithm, is now released (April 2012) to the public. The data are available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The shortname for this Level-2 near-UV Aerosol Product is OMAERUV_V003. The OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Absorption and Aerosol Extinction Optical Depths, and Single Scattering Albedo at three different wavelengths (354, 388 and 500 nm), Aerosol Index, and other ancillary and geolocation parameters, in the OMI field of view (13x24 km). The OMAERUV files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 6 Mbytes. proprietary +OMAERUV_003 OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000120-OMINRT.umm_json The OMI/Aura level-2 near UV Aerosol data product 'OMAERUV', recently re-processed using an enhanced algorithm, is now released (April 2012) to the public. The data is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), http://disc.gsfc.nasa.gov/Aura/OMI/omaeruv_v003.shtml NASA Aura satellite sensors are tracking important atmospheric pollutants from space since its launch in July, 2004. The Ozone Monitoring Instrument(OMI), one of the four Aura satellite sensors with its 2600 km viewing swath width provides daily global measurements of four important US Environmental Protection Agency criteria pollutants (Tropospheric ozone, Nitrogen dioxide,Sulfur dioxide and Aerosols from biomass burning and industrial emissions, HCHO, BrO, OClO and surface UV irradiance. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). The Level-2 OMI Aerosol Product OMAERUV from the Aura-OMI is now available from NASAs GSFC Earth Sciences (GES) Data and Information Services Center (DISC) for public access. OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Absorption and Aerosol Extinction Optical Depths, and Single Scattering Albedo at three different wavelengths (354, 388 and 500 nm), Aerosol Index, and other ancillary and geolocation parameters, in the OMI field of view (13x24 km). Another standard OMI aerosol product is OMAERO, that is based on the KNMI multi-wavelength spectral fitting algorithm. OMAERUV files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 6 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A short OMAERUV Readme Document that includes brief algorithm description and currently known data quality issues is provided by the OMAERUV Algorithm lead (see http://disc.gsfc.nasa.gov/Aura/OMI/omaeruv_v003.shtml) For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . OMAERUV Data Groups and Parameters: The OMAERUV data file contains a swath which consists of two groups: Data fields: Total Aerosol Optical Depth (extinction optical depth) and Aerosol Absorption Optical Depths (at 354, 388 and 500 nm), Single Scattering Albedo, UV Aerosol Index, Visible Aerosol Index, and other intermediate and ancillary parameters (e.g. Estimates of Aerosol Total Extinction and Absorption Optical Depths and Single Scattering Albedo at five atmospheric levels, Aerosol Type, Aerosol Layer Height, Normalized Radiance, Lambert equivalent Reflectivity, Surface Albedo, Imaginary Component of Refractive Index) and Data Quality Flags. Geolocation Fields: Latitude, Longitude, Time(TAI93), Seconds, Solar Zenith Angles, Viewing Zenith Angles, Relative Azimuth Angle, Terrain Pressure, Ground Pixel Quality Flags. For the full set of Aura products available from the GES DISC, please see the link below. http://disc.sci.gsfc.nasa.gov/Aura/ Atmospheric Composition data from Aura and other satellite sensors can be ordered from the following sites: http://disc.sci.gsfc.nasa.gov/acdisc/ proprietary OMAERUV_004 OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V004 (OMAERUV) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3185856256-GES_DISC.umm_json The Aura Ozone Monitoring Instrument level-2 near UV Aerosol data product OMAERUV (Version 004) is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. The OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Optical Depth, Aerosol Single Scattering Albedo, Absorption Optical Depth, UV Aerosol Index, and Aerosol Optical Depth over clouds at three wavelengths (354, 388, and 500 nm), and other ancillary and geolocation parameters, in the OMI field of view (13x24 km). The OMAERUV files are stored in the version 4.0 Network Common Data Form (NetCDF). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 17 Mbytes. proprietary OMAERUV_CPR_003 OMI/Aura Level 2 Near UV Aerosol Optical Depth and Single Scattering Albedo 200-m swath subset along CloudSat track V003 (OMAERUV_CPR) at GES DISC GES_DISC STAC Catalog 2006-06-01 2017-05-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350969-GES_DISC.umm_json This is a CloudSat-collocated subset of the original OMI product OMAERUV, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications. (The shortname for this CloudSat-collocated OMI Level 2 near-UV aerosol subset is OMAERUV_CPR_003) proprietary OMAERUVd_003 OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo L3 1 day 1.0 degree x 1.0 degree V3 (OMAERUVd) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136096-GES_DISC.umm_json The OMI science team produces this Level-3 daily global gridded product OMAERUVd (1 deg Lat/Lon grids). The OMAERUVd product is produced with all data pixels that fall in a grid box with quality filtered and then averaged, based on the pixel level OMI Level-2 Aerosol data product OMAERUV. The OMAERUV data product is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data. The OMAERUVd data product contains extinction and absorption optical depths at three wavelenghts (355 nm, 388 nm and 500 nm). The OMAERUVd files are stored in version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMAERUVd data product is about 0.2 Mbytes. proprietary @@ -11586,8 +11604,8 @@ OMCLDO2Z_003 OMI/Aura Cloud Pressure and Fraction (O2-O2 Absorption) Zoomed 1-Or OMCLDO2_003 OMI/Aura Cloud Pressure and Fraction (O2-O2 Absorption) 1-Orbit L2 Swath 13x24km V003 (OMCLDO2) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966787-GES_DISC.umm_json The reprocessed OMI/Aura Level-2 cloud data product OMCLDO2 is now available from the NASA GoddardEarth Sciences Data and Information Services Center (GES DISC) for the public access. It is the second release of Version 003 and was reprocessed in late 2011. OMI provides two cloud products based on two different algorithms, the Rotational Raman Scattering method, and O2-O2 absorption method using the DOAS technique. This level-2 global cloud product, with a pixel resolution of 13x24 km2at nadir, is based on the spectral fitting of O2-O2 absorption band at 477 nm using DOAS technique. This product contains cloud pressure, cloud fraction, slant column O2-O2, ozone, ring coefficients, uncertainties in derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The lead scientist for this product is Dr. Pepijn Veefkind. The OMCLDO2 product files are stored in the version 5 Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes) and is roughly 15.096 MB in size. There are approximately 14 orbits per day thus the total data volume is approximately 200 GB/day. proprietary OMCLDO2_CPR_003 OMI/Aura Cloud Pressure and Fraction (O2-O2 Absorption) 200-km swath subset along CloudSat track V003 (OMCLDO2_CPR) at GES DISC GES_DISC STAC Catalog 2006-06-01 2018-03-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350939-GES_DISC.umm_json This the OMI/Aura Cloud Pressure and Fraction (O2-O2 Absorption) subset along CloudSat track, for the purposes of the A-Train mission. The original product uses the DOAS technique method. This level-2 global cloud product at the pixel resolution (13x24 km2 at nadir) is based on the spectral fitting of O2-O2 absorption band at 477 nm using DOAS technique. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track. This product contains cloud pressure, cloud fraction, slant column O2-O2 and O3, ring coefficients, uncertainties in derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications. (The shortname for this Level-2 OMI cloud pressure and fraction (O2-O2 absorption) subset along CloudSat track product is OMCLDO2_CPR) proprietary OMCLDRRG_003 OMI/Aura Effective Cloud Pressure and Fraction (Raman Scattering) Daily L2 Global Gridded 0.25 degree x 0.25 degree V3 (OMCLDRRG) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136100-GES_DISC.umm_json This Level-2G daily global gridded product OMCLDRRG is based on the pixel level OMI Level-2 CLDRR product OMCLDRR. This level-2G global cloud product (OMCLDRRG) provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The algorithm lead for the products OMCLDRR and OMCLDRRG is NASA OMI scientist Dr. Joanna Joinner. OMCLDRRG data product is a special Level-2G Gridded Global Product where pixel level data (OMCLDRR)are binned into 0.25x0.25 degree global grids. It contains the OMCLDRR data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved without Averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMCLDRRG data products are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each daily file contains data from the day lit portion of the orbits (~14 orbits). The average file size for the OMCLDRRG data product is about 75 Mbytes. proprietary -OMCLDRR_003 OMI/Aura Effective Cloud Pressure and Fraction (Raman Scattering) 1-Orbit L2 Swath 13x24 km V003 (OMCLDRR) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966791-GES_DISC.umm_json The reprocessed Aura Ozone Monitoring Instrument (OMI) Version 003 Level 2 Cloud Data Product OMCLDRR is available to the public from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Aura OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product, OMCLDRR, provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner. The OMCLDRR files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes. proprietary OMCLDRR_003 OMI/Aura Cloud Pressure and Fraction (Raman Scattering) 1-Orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000100-OMINRT.umm_json The reprocessed Aura OMI Version 003 Level 2 Cloud Data Product OMCLDRR is made available (in April 2012) to the public from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). http://disc.gsfc.nasa.gov/Aura/OMI/omcldrr_v003.shtml ) Aura OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product (OMCLDRR) provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner. OMCLDRR files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml . A short OMCLDRR Readme Document that includes brief algorithm description and data quality is also provided by the OMCLDRR Algorithm lead. The Ozone Monitoring Instrument (OMI) was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products are archived at the NASA GES DISC. For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/instruments/omi/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMCLDRR data file contains one swath which consists of two groups: Data fields: Two Effective Cloud Fraction and two Cloud Top Pressures that are based on two different clear and cloudy scene reflectivity criteria, Chlorophyll Amount, Effective Reflectivity (394.1 micron), UV Aerosol Index (based on 360 and 388 nm), and many Auxiliary Algorithm Parameter and Quality Flags. Geolocation Fields: Latitude, Longitude, Time, Solar Zenith Angle, Viewing Zenith Angle, Relative Azimuth Angle, Terrain Height, and Ground Pixel Quality Flags. OMI Atmospheric data and documents are available from the following sites: http://disc.gsfc.nasa.gov/Aura/OMI/ http://mirador.gsfc.nasa.gov/ proprietary +OMCLDRR_003 OMI/Aura Effective Cloud Pressure and Fraction (Raman Scattering) 1-Orbit L2 Swath 13x24 km V003 (OMCLDRR) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966791-GES_DISC.umm_json The reprocessed Aura Ozone Monitoring Instrument (OMI) Version 003 Level 2 Cloud Data Product OMCLDRR is available to the public from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Aura OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product, OMCLDRR, provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner. The OMCLDRR files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes. proprietary OMCLDRR_004 OMI/Aura Effective Cloud Pressure and Fraction (Raman Scattering) 1-Orbit L2 Swath 13x24 km V004 (OMCLDRR) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3159637081-GES_DISC.umm_json This is the Aura Ozone Monitoring Instrument (OMI) Version 004 Level 2 Cloud Data Product OMCLDRR. OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product, OMCLDRR, provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner. The OMCLDRR files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes. proprietary OMCLDRR_CPR_003 OMI/Aura Cloud Pressure and Fraction (Raman Scattering) 200-km swath subset along CloudSat track V003 (OMCLDRR_CPR) at GES DISC GES_DISC STAC Catalog 2006-06-01 2018-03-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350980-GES_DISC.umm_json This is the OMI/Aura Cloud Pressure and Fraction (Raman Scattering) subset along CloudSat tracks, for the purposes of the A-Train mission. The original data product uses the Rotational Raman Scattering method. This level-2 global cloud product provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). The goal of this subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications. (The shortname for this Level-2 OMI cloud pressure and fraction subset along CloudSat tracks product is OMCLDRR_CPR) proprietary OMDOAO3G_003 OMI/Aura Ozone (O3) DOAS Total Column Daily L2 Global Gridded 0.25 degree x 0.25 degree V3 (OMDOAO3G) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136103-GES_DISC.umm_json This Level-2G daily global gridded product OMDOAO3G is based on the pixel level OMI Level-2 DOAO3 product OMDOAO3. This Level-2G global total column ozone product is derived from OMDOAO3 which is based on the Differential Absorption Spectroscopy (DOAS) fitting technique that essentially uses the OMI visible radiance values between 331.1 and 336.1 nm. In addition to the total ozone column this product also contains some auxiliary derived and ancillary input parameters, e.g. ozone slant column density, ozone ghost column density, etc. The short name for this Level-2 OMI ozone product is OMDOAO3G and the lead algorithm scientist for this product and for OMDOAO3 (the data source of OMDOAO3G) is Dr. Pepijn Veefkind from KNMI. The OMDOAO3G product files are stored in the version 5 Hierarchical Data Format (HDF-EOS5). Each daily file contains data from the day lit portion of the orbits (approximately 14 orbits) and is roughly 80 MB in size. proprietary @@ -11669,12 +11687,12 @@ OMSO2_003 OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13x24 km OMSO2_CPR_003 OMI/Aura Level 2 Sulphur Dioxide (SO2) Trace Gas Column Data 1-Orbit Subset and Collocated Swath along CloudSat V003 (OMSO2_CPR) at GES DISC GES_DISC STAC Catalog 2006-06-01 2018-03-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350970-GES_DISC.umm_json "This is a CloudSat-collocated subset of the original product OMSO2, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. Even though collocated with CloudSat, this subset can serve many other A-Train applications. (The shortname for this CloudSat-collocated subset of the original product OMSO2 Product is OMSO2_CPR_V003) This document describes the original OMI SO2 product (OMSO2) produced from global mode UV measurements of the Ozone Monitoring Instrument (OMI). OMI was launched on July 15, 2004 on the EOS Aura satellite, which is in a sun-synchronous ascending polar orbit with 1:45pm local equator crossing time. The data collection started on August 17, 2004 (orbit 482) and continues to this day with only minor data gaps. The minimum SO2 mass detectable by OMI is about two orders of magnitude smaller than the detection threshold of the legacy Total Ozone Mapping Spectrometer (TOMS) SO2 data (1978-2005) [Krueger et al 1995]. This is due to smaller OMI footprint and the use of wavelengths better optimized for separating O3 from SO2. The product file, called a data granule, covers the sunlit portion of the orbit with an approximately 2600 km wide swath containing 60 pixels per viewing line. During normal operations, 14 or 15 granules are produced daily, providing fully contiguous coverage of the globe. Currently, OMSO2 products are not produced when OMI goes into the ""zoom mode"" for one day every 452 orbits (~32 days). For each OMI pixel we provide 4 different estimates of the column density of SO2 in Dobson Units (1DU=2.69x10^16 molecules/cm2) obtained by making different assumptions about the vertical distribution of the SO2. However, it is important to note that in most cases the precise vertical distribution of SO2 is unimportant. The users can use either the SO2 plume height, or the center of mass altitude (CMA) derived from SO2 vertical distribution, to interpolate between the 4 values: 1)Planetary Boundary Layer (PBL) SO2 column (ColumnAmountSO2_PBL), corresponding to CMA of 0.9 km. 2)Lower tropospheric SO2 column (ColumnAmountSO2_TRL), corresponding to CMA of 2.5 km. 3)Middle tropospheric SO2 column, (ColumnAmountSO2_TRM), usually produced by volcanic degassing, corresponding to CMA of 7.5 km, 4)Upper tropospheric and Stratospheric SO2 column (ColumnAmountSO2_STL), usually produced by explosive volcanic eruption, corresponding to CMA of 17 km. The accuracy and precision of the derived SO2 columns vary significantly with the SO2 CMA and column amount, observational geometry, and slant column ozone. OMI becomes more sensitive to SO2 above clouds and snow/ice, and less sensitive to SO2 below clouds. Preliminary error estimates are discussed below (see Data Quality Assessment). OMSO2 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMSO2 data product is about 9 Mbytes." proprietary OMSO2e_003 OMI/Aura Sulfur Dioxide (SO2) Total Column Daily L3 1 day Best Pixel in 0.25 degree x 0.25 degree V3 (OMSO2e) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136112-GES_DISC.umm_json "The OMI science team produces this Level-3 Aura/OMI Global OMSO2e Data Products (0.25 degree Latitude/Longitude grids). In this Level-3 daily global SO2 data product, each grid contains only one observation of Total Column Density of SO2 in the Planetary Boundary Layer (PBL), based on an improved Principal Component Analysis (PCA) Algorithm. This single observation is the ""best pixel"", selected from all ""good"" L2 pixels of OMSO2 that overlap this grid and have UTC time between UTC times of 00:00:00 and 23:59:59.999. In addition to the SO2 Vertical column value some ancillary parameters, e.g., cloud fraction, terrain height, scene number, solar and satellite viewing angles, row anomaly flags, and quality flags have been also made available corresponding to the best selected SO2 data pixel in each grid. The OMSO2e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5) using the grid model." proprietary OMTO3G_003 OMI/Aura Ozone (O3) Total Column Daily L2 Global Gridded 0.25 degree x 0.25 degree V3 (OMTO3G) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136114-GES_DISC.umm_json This Level-2G daily global gridded product OMTO3G is based on the pixel level OMI Level-2 Total Ozone Product OMTO3. The OMTO3 product is from the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. The OMTO3G data product is a special Level-2 Global Gridded Product where pixel level data are binned into 0.25x0.25 degree global grids. It contains the data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved Without Averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMTO3G data product contains almost all parameters that are contained in the OMTO3. For example, in addition to the total column ozone it also contains UV aerosol index, cloud fraction, cloud pressure, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The OMTO3G files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3G data product is about 150 Mbytes. proprietary -OMTO3_003 OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ . proprietary OMTO3_003 OMI/Aura Ozone(O3) Total Column 1-Orbit L2 Swath 13x24 km V003 (OMTO3) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966818-GES_DISC.umm_json The Aura Ozone Monitoring Instrument (OMI) Level-2 Total Column Ozone Data Product OMTO3 (Version 003) is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. OMI provides two Level-2 (OMTO3 and OMDOAO3) total column ozone products at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms. This level-2 global total column ozone product (OMTO3) is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrievals (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3. The algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia. The OMTO3 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is approximately 35 MB. proprietary +OMTO3_003 OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ . proprietary OMTO3_CPR_003 OMI/Aura Level 2 Ozone (O3) Total Column 1-Orbit Subset and Collocated Swath along CloudSat track 200-km wide at 13x24 km2 resolution GES_DISC STAC Catalog 2006-06-01 2018-03-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350982-GES_DISC.umm_json This is a CloudSat-collocated subset of the original product OMTO3, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications. (The shortname for this CloudSat-collocated OMI Level 2 Total Ozone Column subset is OMTO3_CPR_V003) proprietary OMTO3d_003 OMI/Aura TOMS-Like Ozone, Aerosol Index, Cloud Radiance Fraction L3 1 day 1 degree x 1 degree V3 (OMTO3d) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136070-GES_DISC.umm_json The OMI science team produces this Level-3 daily global TOMS-Like Total Column Ozone gridded product OMTO3d (1 deg Lat/Lon grids). The OMTO3d product is produced by gridding and averaging only good quality level-2 total column ozone orbital swath data (OMTO3, based on the enhanced TOMS version-8 algorithm) on the 1x1 degree global grids. The OMTO3d files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3d data product is about 0.65 Mbytes. proprietary -OMTO3e_003 OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) . proprietary OMTO3e_003 OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 1 day 0.25 degree x 0.25 degree V3 (OMTO3e) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136071-GES_DISC.umm_json The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. The OMTO3e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. proprietary +OMTO3e_003 OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) . proprietary OMUANC_004 Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUANC) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2556143653-GES_DISC.umm_json The Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km (OMUANC) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath. The fields in this product include snow cover, sea ice cover, land cover, terrain height, row anomaly flag, and pixel area. The OMI team also provides a corresponding product for the OMI VIS swath, OMVANC. This product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir. The OMUANC files are in netCDF4 format which is compatible with most netCDF and HDF5 readers and tools. Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official. proprietary OMUFPITMET_003 GEOS-5 FP-IT Assimilation Geo-colocated to OMI/Aura UV-2 1-Orbit L2 Support Swath 13x24km V3 (OMUFPITMET) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1561222825-GES_DISC.umm_json The GEOS-5 FP-IT Assimilation Geo-colocated to OMI/Aura UV-2 1-Orbit L2 Support Swath 13x24km (OMUFPITMET) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath. The fields in this product include surface pressure, vertical temperature profiles, surface and vertical wind profiles, tropopause pressure, boundary layer top pressure, and surface geopotenial. The OMI team also provides a corresponding product for the OMI VIS swath, OMVFPITMET. The product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir. To reduce the size of each orbital file, FP-IT data fields with a vertical dimension of 72 layers have been reduced to 47 layers in OMUFPITMET by combining layers above the troposphere. The OMUFPITMET files are in netCDF4 format which is compatible with most HDF5 readers and tools. Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official. proprietary OMUFPMET_004 GEOS-5 FP-IT 3D Time-Averaged Model-Layer Assimilated Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUFPMET) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2556146042-GES_DISC.umm_json The GEOS-5 FP-IT 3D Time-Averaged Model-Layer Assimilated Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km (OMUFPMET) product provides selected meteorlogical fields from the GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath. The fields in this product include layer pressure thickness, surface pressure, vertical temperature profiles, surface potential, and mid-layer pressure along with geolocation info. The OMI team also provides a corresponding product for the OMI VIS swath, OMVFPMET. The OMI ancillary products were developed to provide supplementary information for use with the OMI collection 4 L1B data sets. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir. The OMUFPMET files are in netCDF4 format which is compatible with most netCDF and HDF5 readers and tools. Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official. proprietary @@ -12862,7 +12880,7 @@ SPL1A_RO_QA_002_2 SMAP_L1A_RADAR_RECEIVE_ONLY_QA_V002 ASF STAC Catalog 2015-02-1 SPL1A_RO_QA_003_3 SMAP_L1A_RADAR_RECEIVE_ONLY_QA_V003 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243124139-ASF.umm_json SMAP Level 1A Radar Receive Only Data Quality Information Version 3 proprietary SPL1BTB_005 SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V005 NSIDC_ECS STAC Catalog 2015-03-31 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C1931655418-NSIDC_ECS.umm_json This Level-1B (L1B) product provides calibrated estimates of time-ordered geolocated brightness temperatures measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band brightness temperatures are referenced to the Earth's surface with undesired and erroneous radiometric sources removed. proprietary SPL1BTB_006 SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V006 NSIDC_ECS STAC Catalog 2015-03-31 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C2776463679-NSIDC_ECS.umm_json This Level-1B (L1B) product provides calibrated estimates of time-ordered geolocated brightness temperatures measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band brightness temperatures are referenced to the Earth's surface with undesired and erroneous radiometric sources removed. proprietary -SPL1BTB_NRT_105 Near Real-time SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V105 NSIDC_ECS STAC Catalog 2024-10-09 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C2257958430-NSIDC_ECS.umm_json "This Near Real-Time (NRT) data set corresponds to the standard SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures (SPL1BTB) product. The data provide calibrated estimates of time-ordered geolocated brightness temperature data measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer, the SMAP L-band radiometer. These Near Real-Time data are available within three hours of satellite observation. The data are created using the latest available ancillary data and spacecraft and antenna attitude data to reduce latency. The SMAP satellite orbits Earth every two to three days, providing half-orbit, ascending and descending, coverage from 86.4°S to 86.4°N in swaths 1000 km across. Data are stored for approximately two to three weeks. Thus, at any given time, users have access to at least fourteen consecutive days of Near Real-Time data through the NSIDC DAAC. Users deciding between the NRT and standard SMAP products should consider the immediacy of their needs versus the quality of the data required. Near real-time data are provided for operational needs whereas standard products meet the quality needs of scientific research. If latency is not a primary concern, users are encouraged to use the standard science product, SPL1BTB (https://doi.org/10.5067/ZHHBN1KQLI20)." proprietary +SPL1BTB_NRT_105 Near Real-time SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V105 NSIDC_ECS STAC Catalog 2024-10-17 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C2257958430-NSIDC_ECS.umm_json "This Near Real-Time (NRT) data set corresponds to the standard SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures (SPL1BTB) product. The data provide calibrated estimates of time-ordered geolocated brightness temperature data measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer, the SMAP L-band radiometer. These Near Real-Time data are available within three hours of satellite observation. The data are created using the latest available ancillary data and spacecraft and antenna attitude data to reduce latency. The SMAP satellite orbits Earth every two to three days, providing half-orbit, ascending and descending, coverage from 86.4°S to 86.4°N in swaths 1000 km across. Data are stored for approximately two to three weeks. Thus, at any given time, users have access to at least fourteen consecutive days of Near Real-Time data through the NSIDC DAAC. Users deciding between the NRT and standard SMAP products should consider the immediacy of their needs versus the quality of the data required. Near real-time data are provided for operational needs whereas standard products meet the quality needs of scientific research. If latency is not a primary concern, users are encouraged to use the standard science product, SPL1BTB (https://doi.org/10.5067/ZHHBN1KQLI20)." proprietary SPL1B_SO_LoRes_001_1 SMAP_L1B_SIGMA_NAUGHT_LOW_RES_V001 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214473308-ASF.umm_json SMAP Level 1B Sigma Naught Low Res Product proprietary SPL1B_SO_LoRes_002_2 SMAP_L1B_SIGMA_NAUGHT_LOW_RES_V002 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243253631-ASF.umm_json SMAP Level 1B Sigma Naught Low Res Product Version 2 proprietary SPL1B_SO_LoRes_003_3 SMAP_L1B_SIGMA_NAUGHT_LOW_RES_V003 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243133445-ASF.umm_json SMAP Level 1B Sigma Naught Low Res Product Version 3 proprietary @@ -12892,7 +12910,7 @@ SPL2SMP_008 SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V008 NSI SPL2SMP_009 SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V009 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463734-NSIDC_ECS.umm_json This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are resampled to an Earth-fixed, global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) [and made available as the SPL1CTB product], and the gridded brightness temperatures are then used to derive gridded soil moisture data. proprietary SPL2SMP_E_005 SMAP Enhanced L2 Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V005 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2136471686-NSIDC_ECS.umm_json This enhanced Level-2 (L2) product contains calibrated, geolocated, brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection [available as the SPl1CTB_E product]. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. These 9-km brightness temperatures are then used to retrieve surface soil moisture posted on the 9-km grid [this SPL2SMP_E product]. proprietary SPL2SMP_E_006 SMAP Enhanced L2 Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V006 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776463773-NSIDC_ECS.umm_json This enhanced Level-2 (L2) product contains calibrated, geolocated, brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection [available as the SPl1CTB_E product]. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. These 9-km brightness temperatures are then used to retrieve surface soil moisture posted on the 9-km grid [this SPL2SMP_E product]. proprietary -SPL2SMP_NRT_107 Near Real-time SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V107 NSIDC_ECS STAC Catalog 2024-10-09 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2312096175-NSIDC_ECS.umm_json "This Near Real-Time (NRT) data set corresponds to the standard SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture (SPL2SMP) product. The data provide estimates of global land surface conditions measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer, the SMAP L-band radiometer. These Near Real-Time data are available within three hours of satellite observation. The data are created using the latest available ancillary data and spacecraft and antenna attitude data to reduce latency. The SMAP satellite orbits Earth every two to three days, providing half-orbit, ascending and descending, coverage from 86.4°S to 86.4°N in swaths 1000 km across. Data are stored for approximately two to three weeks. Thus, at any given time, users have access to at least fourteen consecutive days of Near Real-Time data through the NSIDC DAAC. Users deciding between the NRT and standard SMAP products should consider the immediacy of their needs versus the quality of the data required. Near real-time data are provided for operational needs whereas standard products meet the quality needs of scientific research. If latency is not a primary concern, users are encouraged to use the standard science product SPL2SMP (https://doi.org/10.5067/LPJ8F0TAK6E0)." proprietary +SPL2SMP_NRT_107 Near Real-time SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V107 NSIDC_ECS STAC Catalog 2024-10-17 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2312096175-NSIDC_ECS.umm_json "This Near Real-Time (NRT) data set corresponds to the standard SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture (SPL2SMP) product. The data provide estimates of global land surface conditions measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer, the SMAP L-band radiometer. These Near Real-Time data are available within three hours of satellite observation. The data are created using the latest available ancillary data and spacecraft and antenna attitude data to reduce latency. The SMAP satellite orbits Earth every two to three days, providing half-orbit, ascending and descending, coverage from 86.4°S to 86.4°N in swaths 1000 km across. Data are stored for approximately two to three weeks. Thus, at any given time, users have access to at least fourteen consecutive days of Near Real-Time data through the NSIDC DAAC. Users deciding between the NRT and standard SMAP products should consider the immediacy of their needs versus the quality of the data required. Near real-time data are provided for operational needs whereas standard products meet the quality needs of scientific research. If latency is not a primary concern, users are encouraged to use the standard science product SPL2SMP (https://doi.org/10.5067/LPJ8F0TAK6E0)." proprietary SPL3FTA_003 SMAP L3 Radar Northern Hemisphere Daily 3 km EASE-Grid Freeze/Thaw State V003 NSIDC_ECS STAC Catalog 2015-04-13 2015-07-07 -180, 45, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C1236303849-NSIDC_ECS.umm_json This Level-3 (L3) product provides a daily composite of Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radar from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band backscatter data are used to derive freeze/thaw data, which are then resampled to an Earth-fixed, Northern Hemisphere azimuthal 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary SPL3FTP_003 SMAP L3 Radiometer Global and Northern Hemisphere Daily 36 km EASE-Grid Freeze/Thaw State V003 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C1931660632-NSIDC_ECS.umm_json This Level-3 (L3) product provides a daily composite of landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are used to derive freeze/thaw state and transition data, which are then resampled to both an Earth-fixed, Northern Hemisphere azimuthal 36 km Equal-Area Scalable Earth Grid (EASE-Grid 2.0), and to an Earth-fixed global 36 km EASE-Grid 2.0. proprietary SPL3FTP_004 SMAP L3 Radiometer Global and Northern Hemisphere Daily 36 km EASE-Grid Freeze/Thaw State V004 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463838-NSIDC_ECS.umm_json This Level-3 (L3) product provides a daily composite of landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are used to derive freeze/thaw state and transition data, which are then resampled to both an Earth-fixed, Northern Hemisphere azimuthal 36 km Equal-Area Scalable Earth Grid (EASE-Grid 2.0), and to an Earth-fixed global 36 km EASE-Grid 2.0. proprietary @@ -12954,7 +12972,6 @@ SPURS2_WAVEGLIDER_1.0 SPURS-2 Waveglider data for the E. Tropical Pacific field SPURS2_XBAND_1.0 SPURS-2 shipboard X-band radar backscatter data for the E. Tropical Pacific field campaign POCLOUD STAC Catalog 2017-10-21 2017-11-13 -129.131, 8.927, -122.151, 10.355 https://cmr.earthdata.nasa.gov/search/concepts/C2781659132-POCLOUD.umm_json The SPURS-2 X-band marine navigation radar image dataset was collected from the ship during both the 2016 and 2017 cruises. The dataset consists of screenshots of rain echoes captured directly from the science-use X-band marine navigation radar. Raw data could not be saved. The screenshots show qualitative (uncalibrated) echoes of backscatter from rain. For full details on the screenshots, how they should be used, and what they show about rainfall, please refer to our publication: Thompson, E.J., W.E. Asher, A.T. Jessup, and K. Drushka. 2019. High-Resolution Rain Maps from an X-band Marine Radar and Their Use in Understanding Ocean Freshening. Oceanography 32(2):58–65, https://doi.org/10.5670/oceanog.2019.213 . The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is a NASA-funded oceanographic process study and associated field program that aims to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. proprietary SPURS2_XBAND_IMG_1.0 SPURS-2 shipboard X-band radar backscatter images for the 2016 E. Tropical Pacific field campaign POCLOUD STAC Catalog 2016-08-31 2016-09-22 -129.131, 8.927, -122.151, 10.355 https://cmr.earthdata.nasa.gov/search/concepts/C2931233351-POCLOUD.umm_json The SPURS-2 X-band marine navigation radar image dataset was collected from the ship during both the 2016 and 2017 cruises. The dataset consists of screenshots of rain echoes captured directly from the science-use X-band marine navigation radar. Raw data could not be saved. The screenshots show qualitative (uncalibrated) echoes of backscatter from rain. For full details on the screenshots, how they should be used, and what they show about rainfall, please refer to our publication: Thompson, E.J., W.E. Asher, A.T. Jessup, and K. Drushka. 2019. High-Resolution Rain Maps from an X-band Marine Radar and Their Use in Understanding Ocean Freshening. Oceanography 32(2):58–65, https://doi.org/10.5670/oceanog.2019.213 . The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is a NASA-funded oceanographic process study and associated field program that aims to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. proprietary SPURS2_XBT_1.0 SPURS-2 research vessel Expendable Bathythermograph (XBT) profile data for E. Tropical Pacific R/V Revelle cruises POCLOUD STAC Catalog 2016-08-14 2017-11-15 -157.88, 5.06, -118.32, 21.26 https://cmr.earthdata.nasa.gov/search/concepts/C2491772372-POCLOUD.umm_json The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is NASA-funded oceanographic process study and associated field program that aim to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. The project involves two field campaigns and a series of cruises in regions of the Atlantic and Pacific Oceans exhibiting salinity extremes. SPURS employs a suite of state-of-the-art in-situ sampling technologies that, combined with remotely sensed salinity fields from the Aquarius/SAC-D, SMAP and SMOS satellites, provide a detailed characterization of salinity structure over a continuum of spatio-temporal scales. The SPURS-2 campaign involved two month-long cruises by the R/V Revelle in August 2016 and October 2017 combined with complementary sampling on a more continuous basis over this period by the schooner Lady Amber. Focused around a central mooring located near 10N,125W, the objective of SPURS-2 was to study the dynamics of the rainfall-dominated surface ocean at the western edge of the eastern Pacific fresh pool subject to high seasonal variability and strong zonal flows associated with the North Equatorial Current and Countercurrent. Expendable bathythermograph (XBT) casts were undertaken at stations during both of the SPURS-2 R/V Revelle cruises. Launched off the side of the ship, XBT probes provide vertical profile measurements of the water column at fixed locations. There were a total of 25 and 11 XBT deployments made during the first and second R/V Revelle cruises respectively. There is one XBT data file per cruise, each containing the temperature profile data from all instrument deployments undertaken during that cruise. proprietary -SRB_REL3.0_SW_3HRLY_MONTHLY_UTC_NC_1 Surface Radiation Budget (SRB) Release 3.0 Shortwave 3 hourly monthly UTC data in netcdf format LARC_ASDC STAC Catalog 1983-07-01 2007-12-31 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2184128386-LARC_ASDC.umm_json The data set contains monthly average/3-hourly (also calleddiurnally-resolved monthly average or just 'diurnal' for brevity) global fieldsof 11 shortwave (SW) surface radiative parameters derived with the Shortwavealgorithm of the NASA World Climate Research Programme /Global Energy andWater-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project.The data is generated using the Pinker/Laszlo shortwave algorithm (R.T. Pinkerand I. Laszlo, 1992: Modeling Surface Solar Irradiance for SatelliteApplications on a Global Scale, J. Appl. Met., 31, 194-211).These parameters were derived originally on a 3-hourly temporal resolution(i.e., a global instantaneous gridded field every 3 hours), at UT hours 00, 03,06, 09, 12, 15, 18, and 21 for every day of the month. The 3-hourly values wereused to compute monthly averages separately for each of the 8 UT hours. Thecurrent version of the data is identified as Release 3.0. proprietary SRDB_V5_1827_5 A Global Database of Soil Respiration Data, Version 5.0 ORNL_CLOUD STAC Catalog 1961-01-01 2017-12-31 -163.71, -78.02, 175.9, 81.8 https://cmr.earthdata.nasa.gov/search/concepts/C2216864433-ORNL_CLOUD.umm_json The Soil Respiration Database (SRDB) is a near-universal compendium of published soil respiration (Rs) data. The database encompasses published studies that report at least one of the following data measured in the field (not laboratory): annual soil respiration, mean seasonal soil respiration, a seasonal or annual partitioning of soil respiration into its source fluxes, soil respiration temperature response (Q10), or soil respiration at 10 degrees C. The SRDB's orientation is to seasonal and annual fluxes, not shorter-term or chamber-specific measurements, and the database is dominated by temperate, well-drained forest measurement locations. Version 5 (V5) is the compilation of 2,266 published studies with measurements taken between 1961-2017. V5 features more soil respiration data published in Russian and Chinese scientific literature for better global spatio-temporal coverage and improved global climate-space representation. The database is also restructured to have better interoperability with other datasets related to carbon-cycle science. proprietary SRE4_SAB_gammaclones_1 Clone library using primers for gammaproteobacteria from an SAB treatment in the SRE4 experiment AU_AADC STAC Catalog 2002-12-01 2002-12-31 110, -66, 110, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214313841-AU_AADC.umm_json A clone library was created from DNA extracted from an SAB-treated sample from the SRE4 in situ biodegradation experiment. The clone libary was created using one universal primer and one primer designed to be specific for the gammaproteobacteria. Sequences of approximately 600 bp were obtained. The samples used in this experiment were collected from O'Brien Bay, near Casey Station in the Windmill Islands. Gammaproteobacteria clone library Clone library created from SRE4 T2 SAB sample using primers 10F (GAG TTT GAT CCT GGC TCA G ) and GAMR (GGT AAG GTT CTT CGC GTT GCA T). Clones sequenced on a CEQ8000 Genetic Analysis system (Beckman-Coulter) and alignments were done in BioEdit v 5.0.9. Text file SRE4gammaclonesalign is a text version of BioEdit file SRE4gammaclones. This work was completed as part of ASAC project 2672 (ASAC_2672). proprietary SRE4_desulfobaculaDGGE_1 Band pattern data from Desulfobacula-group specific DGGE for the SRE4 experiment AU_AADC STAC Catalog 2001-10-25 2003-03-30 110, -67, 111, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214313816-AU_AADC.umm_json Samples are from the SRE4 experiment - an in situ experiment to determine fate and effects of different types of oils in the Antarctic marine environment. For details see: Powell S.M., Snape I., Bowman J.P., Thompson B.A.W., Stark J.S., McCammon S.A., Riddle M.J. 2005. A comparison of the short term effects of diesel fuel and lubricant oils on Antarctic benthic microbial communities. Journal of Experimental Marine Biology and Ecology 322:53-65. Samples were analysed by denaturing gradient gel electrophoresis (DGGE) with primers specific for the Desulfobacula group. Samples A,B,C,D,E,F,G,H,I are all initial samples collected different days Samples beginning T0 are predeployment samples, the next number refers to the batch. Samples beginning T2 are 1 year samples with: C = control S = SAB L = lubricant U = used lubricant B = biodegradable lubricant PCR conditions were as follows: Primers: 764F: ACAATGGTAAATGAGGGCA 1392RC: CGCCCGCCGCGCCCCGCGCCCGGCCCGCCGCCCCCGCCCCACGGGCGG TGTGTAC 50 ul (micro litre) reactions with Advantage II taq (Clontech) following manufacturer's recommendations with 20 pmol (pico mol) each primer and 20 ng (nano gram) template DNA. Cycling: 94C 5 minutes 10 cycles of: 94C 1 minutes 65C 1 minutes (-1C per cycle) 72C 2 minutes 20 cycles of: 94C 1 minutes 55C 1 minutes 72C 2 minutes 72C 30 minutes DGGE carried out using the D-Code system (BioRad). Gel: 8% acrylamide 30 - 65% denaturant with 2 cm stacking gel (15% acrylamide) 1 x TAE, 60 degrees C, 70V 16 hours The gels were pre-run for 20 minutes then half reaction volume was loaded and the lanes flushed out after 15 minutes. Gels were stained with SYBRGold. Images were captured using Storm Phosphorimager and ImageQuant v5.2 software(.gel files). Samples were only compared within a gel. Band pattern results are in the file desulfodgge.xls. For each comparison made there is a separate sheet in this file (see below). The first column in each sheet is the band position (or band name) and the remaining columns are samples with the first row being the sample name. '0' '1' indicate the band was 'absent' or 'present'. Comparison Image files (.gel and .tif) results sheets Background variation 140704f; 140704b 140704f and 140704b predeployment batches 180604f; 180406b 180604f and 180604b effect of setup 150704 150704 immediate effect of oil 250604f; 250604b 250604f and 250604b 1 year samples (T2) 040804f; 040804b 040804f and 040804b This work was completed as part of ASAC projects 1228 and 2201 (ASAC_1228, ASAC_2201). proprietary @@ -13574,24 +13591,15 @@ TOMS_ozone_824_1 SAFARI 2000 TOMS Tropospheric Ozone Data, Southern Africa Subse TOPEX_ALTSDR_A TOPEX ALTIMETER SENSOR DATA RECORD POCLOUD STAC Catalog 1992-09-25 2005-10-04 -180, -66, 180, 66 https://cmr.earthdata.nasa.gov/search/concepts/C2617176787-POCLOUD.umm_json The Sensory Data Record (SDR) is similar to the GDR product except that it also contains waveforms, which are required for retracking. This is an expert level product. If you do not need the waveforms then the GDR should suit your needs. proprietary TOPEX_POSEIDON_GDR_F_F TOPEX/POSEIDON Geophysical Data Record Version F POCLOUD STAC Catalog 1992-10-13 2005-10-04 -180, -66, 180, 66 https://cmr.earthdata.nasa.gov/search/concepts/C2599212091-POCLOUD.umm_json The TOPEX/POSEIDON Geophysical Data Record (GDR) contains global coverage altimeter data. The objective of the TOPEX/POSEIDON mission, launched in August 1992, is to determine ocean topography with a sea surface height measurement precision of 3 cm and a sealevel measurement accuracy of 13 cm. The dataset contains measurements from two altimeters, a NASA dual frequency (Ku and C band) instrument similar to the Geosat altimeter, and a French space agency (CNES) instrument which is a proof-of-concept solid-state altimeter (Ku band). It also contains Sea Surface Height (SSH), significant wave height, ionospheric correction, tides and other geophysical corrections. It is emphasized that this product is considered research data because of the form and content of the data. The data consist entirely of files comprising headers and data records which contain over a hundred parameters for each second. It is swath data and there are no images. Analysis software is the responsibility of the user. Calculation of sea surface height anomalies from the altimeter range and environmental corrections is the responsibility of the user. The data are arranged in 10 day cycles that are separated into 254 passes, each about 56 minutes. proprietary TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 In Situ Aerosol Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2736753162-LARC_ASDC.umm_json TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1 is the in situ collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data from the Multiple-Angle Spectrometer Probe (MASP), 2D-C Aerosol Probe, and FSSP Aerosol Size distributions are featured in this data product. Data collection is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 In Situ Aerosol Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2736753162-LARC_ASDC.umm_json TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1 is the in situ collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data from the Multiple-Angle Spectrometer Probe (MASP), 2D-C Aerosol Probe, and FSSP Aerosol Size distributions are featured in this data product. Data collection is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Remotely Sensed Differential Absorption Lidar (DIAL) Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 89.993 https://cmr.earthdata.nasa.gov/search/concepts/C2736747109-LARC_ASDC.umm_json TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1 is the remotely sensed Differential Absorption Lidar (DIAL) data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Remotely Sensed Differential Absorption Lidar (DIAL) Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 89.993 https://cmr.earthdata.nasa.gov/search/concepts/C2736747109-LARC_ASDC.umm_json TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1 is the remotely sensed Differential Absorption Lidar (DIAL) data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_AircraftRemoteSensing_DC8_Lidar_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Remotely Sensed Lidar Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -10.68, -180, 89.993 https://cmr.earthdata.nasa.gov/search/concepts/C2736752301-LARC_ASDC.umm_json TOTE-VOTE_AircraftRemoteSensing_DC8_Lidar_Data_1 is the remotely sensed Raman Lidar data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Methane and water vapor data are featured in this dataset. Data collection is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_AircraftRemoteSensing_DC8_Lidar_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Remotely Sensed Lidar Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -10.68, -180, 89.993 https://cmr.earthdata.nasa.gov/search/concepts/C2736752301-LARC_ASDC.umm_json TOTE-VOTE_AircraftRemoteSensing_DC8_Lidar_Data_1 is the remotely sensed Raman Lidar data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Methane and water vapor data are featured in this dataset. Data collection is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_Analysis_DC8_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Analysis Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 89.993 https://cmr.earthdata.nasa.gov/search/concepts/C2736731936-LARC_ASDC.umm_json TOTE-VOTE_Analysis_DC8_Data_1 is the modeled meteorological data along the flight path for the DC-8 aircraft collected during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection for this product is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_Analysis_DC8_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Analysis Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 89.993 https://cmr.earthdata.nasa.gov/search/concepts/C2736731936-LARC_ASDC.umm_json TOTE-VOTE_Analysis_DC8_Data_1 is the modeled meteorological data along the flight path for the DC-8 aircraft collected during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection for this product is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_Ground_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Ground Site Lidar Data LARC_ASDC STAC Catalog 1995-12-01 1996-02-19 -155.7, 19.5, -117.6, 34.4 https://cmr.earthdata.nasa.gov/search/concepts/C2736718104-LARC_ASDC.umm_json TOTE-VOTE_Ground_Data_1 is the ground site data collected as part of the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data featured in the product includes data from the NASA GSFC Stratospheric Ozone Lidar Trailer Experiment (STROZ-LITE) at Mauna Loa, and the JPL Table Mountain Facility, Mauna Loa Lidar. Data collection for this product is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_Ground_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Ground Site Lidar Data LARC_ASDC STAC Catalog 1995-12-01 1996-02-19 -155.7, 19.5, -117.6, 34.4 https://cmr.earthdata.nasa.gov/search/concepts/C2736718104-LARC_ASDC.umm_json TOTE-VOTE_Ground_Data_1 is the ground site data collected as part of the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data featured in the product includes data from the NASA GSFC Stratospheric Ozone Lidar Trailer Experiment (STROZ-LITE) at Mauna Loa, and the JPL Table Mountain Facility, Mauna Loa Lidar. Data collection for this product is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_MetNav_AircraftInSitu_DC8_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) In Situ DC-8 Meteorology and Navigation Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2736742916-LARC_ASDC.umm_json TOTE-VOTE_MetNav_AircraftInSitu_DC8_Data_1 features the in situ meteorology and navigation data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) Campaign. Instruments included in this dataset include the Microwave Temperature Profiler (MTP), DC-8 Data Acquisition and Distribution System (DADS) and Diode Laser Hygrometer (DLH). Data collection is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_Miscellaneous_DC8_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Ancillary Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 89.993 https://cmr.earthdata.nasa.gov/search/concepts/C2736739081-LARC_ASDC.umm_json TOTE-VOTE_Analysis_DC8_Data_1 is the ancillary datasets from the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. This dataset contains postscript files of datasets to support DC-8 aircraft measurements. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_Miscellaneous_DC8_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 Ancillary Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 89.993 https://cmr.earthdata.nasa.gov/search/concepts/C2736739081-LARC_ASDC.umm_json TOTE-VOTE_Analysis_DC8_Data_1 is the ancillary datasets from the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. This dataset contains postscript files of datasets to support DC-8 aircraft measurements. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_Satellite_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Supplementary Satellite Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-19 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2736712587-LARC_ASDC.umm_json TOTE-VOTE_Satellite_Data_1 is the supplementary satellite data for the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data in this product includes GOES-7 infrared imagery and GOES-9 water vapor imagery. Data collection for this product is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_Satellite_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Supplementary Satellite Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-19 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2736712587-LARC_ASDC.umm_json TOTE-VOTE_Satellite_Data_1 is the supplementary satellite data for the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data in this product includes GOES-7 infrared imagery and GOES-9 water vapor imagery. Data collection for this product is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_Sondes_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Sonde Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-19 179.22, -54.5, -180, 82.5 https://cmr.earthdata.nasa.gov/search/concepts/C2736723318-LARC_ASDC.umm_json TOTE-VOTE_Sondes_Data_1 is the radiosonde data collected during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection for this product is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_Sondes_Data_1 Tropical Ozone Transport Experiment - Vortex Ozone Transport Experiment (TOTE-VOTE) Sonde Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-19 179.22, -54.5, -180, 82.5 https://cmr.earthdata.nasa.gov/search/concepts/C2736723318-LARC_ASDC.umm_json TOTE-VOTE_Sondes_Data_1 is the radiosonde data collected during the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection for this product is complete. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTE-VOTE_TraceGas_AircraftInSitu_DC8_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 In Situ Trace Gas Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2736766511-LARC_ASDC.umm_json TOTE-VOTE_TraceGas_AircraftInSitu_DC8_Data_1 is the in situ trace gas data collected onboard the DC-8 aircraft as part of the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collected by the DACOM, LICOR, and chemiluminescence are featured in this product. Data collection is completed. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary -TOTE-VOTE_TraceGas_AircraftInSitu_DC8_Data_1 Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) DC-8 In Situ Trace Gas Data LARC_ASDC STAC Catalog 1995-12-03 1996-02-20 180, -23.1, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2736766511-LARC_ASDC.umm_json TOTE-VOTE_TraceGas_AircraftInSitu_DC8_Data_1 is the in situ trace gas data collected onboard the DC-8 aircraft as part of the Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collected by the DACOM, LICOR, and chemiluminescence are featured in this product. Data collection is completed. The Tropical Ozone Transport Experiment – Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts. Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP’s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature. proprietary TOTO_0 Tongue of the Ocean (TOTO) experiment OB_DAAC STAC Catalog 1998-04-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360685-OB_DAAC.umm_json Tongue of the Ocean (TOTO) experiment data was collected around the Bahamas and West Florida Shelf. proprietary TOVSA5ND_01 TOVS GLA 5 DAY GRIDS from NOAA-12 V01 (TOVSA5ND) at GES DISC GES_DISC STAC Catalog 1991-07-04 1994-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1274625652-GES_DISC.umm_json This dataset (TOVSA5ND) contains the TIROS Operational Vertical Sounder (TOVS) level 3 geophysical parameters derived using data from NOAA-12 and the physical retrieval method of Susskind et al. (1984) and processed by the Satellite Data Utilization Office of the Goddard Laboratory for Atmospheres at NASA/GSFC. This method, which is hydrodynamic model- and a priori data-dependent, is designated as the so-called Path A scheme by the TOVS Pathfinder Science Working Group. The 20 channel High resolution Infrared Radiation Sounder 2 (HIRS2) and the 4 channel Microwave Sounding Unit (MSU) aboard the NOAA-xx series of Polar Orbiting Satellites are used to produce global fields of the 3-dimensional temperature-moisture structure of the atmosphere. In addition to profiles of temperature and moisture, the HIRS2/MSU data are used to derive important quantities such as land and sea surface temperature, outgoing longwave radiation, cloud fraction, cloudtop height, total ozone overburden and precipitation estimates. The Path A system steps through an interactive forecast-retrieval-analysis cycle. In each 6 hour synoptic period, a 2nd order General Circulation Model (Takacs et al., 1994) is used to generate the 6 hour forecast fields of temperature and humidity. These global fields are used as the first guess for all soundings occuring within a 6 hour time window centered upon the forecast time. These retrievals are then assimilated with all available insitu measurements (such as radiosonde and ship reports) in the 6 hour interval using an Optimal Interpolation (OI) analysis scheme developed by the Data Assimilation Office of the Goddard Laboratory for Atmospheres. This analysis is then used to specify the initial conditions for the next 6 hour forecast, thus completing the cycle. The retrieval algorithm itself is a physical method based on the iterative relaxation technique originally proposed by Chahine (1968). The basic approach consists of modifying the temperature profile from the previous iteration by an amount proportional to the difference between the observed brightness temperatures and the brightness temperatures computed from the trial parameters using the full radiative transfer equation applied at the observed satellite zenith angle. For the case of the temperature profile, the updated layer mean temperatures are given as a linear combination of multichannel brightness temperature differences with the coefficients given by the channel weighting functions. Constraints are imposed upon the solution in order to ensure stability and convergence of the iterative process. For more details see Susskind et al (1984). There are level 3 data product files for five TOVS satellites, each of which is in the HDF format and each representative of a different averaging time period. All files contain the same number of geophysical parameter arrays stored as HDF Scientific Data Sets (SDSs). The time periods include daily, 5 day (pentad) and monthly, with the AM and PM portions of the orbits treated separately. All data are mapped to a 1 degree longitude by 1 degree latitude global grid. This collection contains 5-day averages. proprietary TOVSA5NF_01 TOVS GLA 5 DAY GRIDS from NOAA-9 V01 (TOVSA5NF) at GES DISC GES_DISC STAC Catalog 1984-12-31 1987-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1274625637-GES_DISC.umm_json This dataset (TOVSA5NF) contains the TIROS Operational Vertical Sounder (TOVS) level 3 geophysical parameters derived using data from NOAA-9 and the physical retrieval method of Susskind et al. (1984) and processed by the Satellite Data Utilization Office of the Goddard Laboratory for Atmospheres at NASA/GSFC. This method, which is hydrodynamic model- and a priori data-dependent, is designated as the so-called Path A scheme by the TOVS Pathfinder Science Working Group. The 20 channel High resolution Infrared Radiation Sounder 2 (HIRS2) and the 4 channel Microwave Sounding Unit (MSU) aboard the NOAA-xx series of Polar Orbiting Satellites are used to produce global fields of the 3-dimensional temperature-moisture structure of the atmosphere. In addition to profiles of temperature and moisture, the HIRS2/MSU data are used to derive important quantities such as land and sea surface temperature, outgoing longwave radiation, cloud fraction, cloudtop height, total ozone overburden and precipitation estimates. The Path A system steps through an interactive forecast-retrieval-analysis cycle. In each 6 hour synoptic period, 2nd order General Circulation Model (Takacs et al., 1994) is used to generate the 6 hour forecast fields of temperature and humidity. These global fields are used as the first guess for all soundings occuring within a 6 hour time window centered upon the forecast time. These retrievals are then assimilated with all available insitu measurements (such as radiosonde and ship reports) in the 6 hour interval using an Optimal Interpolation (OI) analysis scheme developed by the Data Assimilation Office of the Goddard Laboratory for Atmospheres. This analysis is then used to specify the initial conditions for the next 6 hour forecast, thus completing the cycle. The retrieval algorithm itself is a physical method based on the iterative relaxation technique originally proposed by Chahine (1968). The basic approach consists of modifying the temperature profile from the previous iteration by an amount proportional to the difference between the observed brightness temperatures and the brightness temperatures computed from the trial parameters using the full radiative transfer equation applied at the observed satellite zenith angle. For the case of the temperature profile, the updated layer mean temperatures are given as a linear combination of multichannel brightness temperature differences with the coefficients given by the channel weighting functions. Constraints are imposed upon the solution in order to ensure stability and convergence of the iterative process. For more details see Susskind et al (1984). There are level 3 data product files for five TOVS satellites, each of which is in the HDF format and each representative of a different averaging time period. This collection contains a 5 day average. proprietary @@ -13746,6 +13754,7 @@ TROPICS07BRTTL1B_0.2 TROPICS07 L1B Orbital Geolocated Native-Resolution Brightn TROPICS07URADL2A_0.2 TROPICS07 L2A Unified Resolution Brightness Temperatures V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3104589838-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS07 satellite, as the Provisional version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPOMAER_1 TROPOMI/Sentinel-5P Near UV Aerosol Optical Depth and Single Scattering Albedo L2 1-Orbit Snapshot 7.5 km x 3 km GES_DISC STAC Catalog 2018-04-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2152047233-GES_DISC.umm_json As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this projects describes a multi-decadal Fundamental Climate Data Record (FCDR) of calibrated radiances as well as an Earth System Data Record (ESDR) of aerosol properties over the continents derived from a 32-year record of satellite near-UV observations by three sensors. The Corpenicus Sentinel-5P TROPOMI Near UV (version 1) Aerosol Optical Depth and Single Scattering Albedo data product consists of aerosol absorption optical depth, aerosol total optical depth, aerosol layer height, aerosol UV index, and aerosol single scattering albedo at approximately 7.5kmx3km. This product also contains ancillary data for ocean corrected surface albedo and terrain pressure. Data since July 19, 2022 (orbit 24688) has been processed with the most recent calibrated L1B radiance data (version 2.0.1). Data prior to July 19, 2022, data was processed with version 2.0.0 L1B radiances. Soon, the entire record will be reprocessed using version 2.0.1 L1B data. Any upgrades will be posted here. These Level-2 data are stored in the NetCDF-4 format and are available from the Goddard Earth Sciences (GES) Data and Information Services Center (DISC). proprietary TROPOMI_MINDS_NO2_1.1 TROPOMI/S5P NO2 Tropospheric, Stratospheric and Total Columns MINDS 1-Orbit L2 Swath 5.5 km x 3.5 km V1.1 (TROPOMI_MINDS_NO2) at GES DISC GES_DISC STAC Catalog 2018-05-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2263977000-GES_DISC.umm_json As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled “Multi-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)” will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2011), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats. proprietary +TROPOMI_SIF_Arctic_Ocean_2378_1 Monthly SIF Estimates from TROPOMI over the Arctic Ocean, 2004-2020 ORNL_CLOUD STAC Catalog 2004-01-01 2020-12-31 -180, 50, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3282002388-ORNL_CLOUD.umm_json This dataset provides solar-induced chlorophyll fluorescence (SIF) estimates over the Arctic Ocean at a 0.05-degree resolution for each month from January 2004 through December 2020. Red SIF data from TROPOspheric Monitoring Instrument (TROPOMI) (2018 to 2021) were extended over the study period using a random forest machine learning model trained using TROPOMI SIF climatological records. These data are useful for monitoring the physiological responses of phytoplankton to ongoing climate change over this ocean region. The data are provided in cloud optimized GeoTIFF format. proprietary TRPSCRAERNH42H2D_1 TROPESS Chemical Reanalysis Surface Aerosol NH4 2-Hourly 2-dimensional Product V1 (TRPSCRAERNH42H2D) at GES DISC GES_DISC STAC Catalog 2005-01-01 2021-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2816184404-GES_DISC.umm_json The TROPESS Chemical Reanalysis Surface Aerosol NH4 2-Hourly 2-dimensional Product contains surface concentrations of ammonium aerosols. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors. The data files are written in the netCDF version 4 file format, and each file contains a year of data at 2-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki. proprietary TRPSCRAERNH46H3D_1 TROPESS Chemical Reanalysis Aerosol NH4 6-Hourly 3-dimensional Product V1 (TRPSCRAERNH46H3D) at GES DISC GES_DISC STAC Catalog 2005-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2837624881-GES_DISC.umm_json The TROPESS Chemical Reanalysis Surface Aerosol NH4 6-Hourly 3-dimensional Product contains vertical concentrations of ammonium aerosols. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors. The data files are written in the netCDF version 4 file format, and each file contains a year of data at 6-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees at 27 pressure levels between 1000 and 60 hPa. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki. proprietary TRPSCRAERNH4M3D_1 TROPESS Chemical Reanalysis Aerosol NH4 Monthly 3-dimensional Product V1 (TRPSCRAERNH4M3D) at GES DISC GES_DISC STAC Catalog 2005-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2837624954-GES_DISC.umm_json The TROPESS Chemical Reanalysis Surface Aerosol NH4 Monthly 3-dimensional Product contains vertical concentrations of ammonium aerosols. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors. The data files are written in the netCDF version 4 file format, and each file contains a year of data at monthly resolution, and a spatial resolution of 1.125 x 1.125 degrees at 27 pressure levels between 1000 and 60 hPa. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki. proprietary