ADD: Adding example for bringing BNF data sources together for plotting

act/discovery/asos.py

@@ -18,7 +18,7 @@
     from urllib2 import urlopen
 
 
-def get_asos_data(time_window, lat_range=None, lon_range=None, station=None):
+def get_asos_data(time_window, lat_range=None, lon_range=None, station=None, regions=None):
     """
     Returns all of the station observations from the Iowa Mesonet from either
     a given latitude and longitude window or a given station code.
@@ -34,6 +34,9 @@ def get_asos_data(time_window, lat_range=None, lon_range=None, station=None):
         The longitude window to grab all of the ASOS observations from.
     station: str
         The station ID to grab the ASOS observations from.
+    regions: str
+        Region that the ASOS is in.  For Alabama, it would be AL
+        For more than one region add it to the string with spaces between 'AL MN'
 
     Returns
     -------
@@ -51,33 +54,36 @@ def get_asos_data(time_window, lat_range=None, lon_range=None, station=None):
     """
     # First query the database for all of the JSON info for every station
     # Only add stations whose lat/lon are within the Grid's boundaries
-    regions = """AF AL_ AI_ AQ_ AG_ AR_ AK AL AM_
-        AO_ AS_ AR AW_ AU_ AT_
-        AZ_ BA_ BE_ BB_ BG_ BO_ BR_ BF_
-        BT_ BS_ BI_ BM_ BB_ BY_ BZ_ BJ_ BW_ AZ CA CA_AB
-        CA_BC CD_ CK_ CF_ CG_ CL_ CM_ CO CO_ CN_ CR_ CT
-        CU_ CV_ CY_ CZ_ DE DK_ DJ_ DM_ DO_
-        DZ EE_ ET_ FK_ FM_ FJ_ FI_ FR_ GF_ PF_
-        GA_ GM_ GE_ DE_ GH_ GI_ KY_ GB_ GR_ GL_ GD_
-        GU_ GT_ GN_ GW_ GY_ HT_ HN_ HK_ HU_ IS_ IN_
-        ID_ IR_ IQ_ IE_ IL_ IT_ CI_ JM_ JP_
-        JO_ KZ_ KE_ KI_ KW_ LA_ LV_ LB_ LS_ LR_ LY_
-        LT_ LU_ MK_ MG_ MW_ MY_ MV_ ML_ CA_MB
-        MH_ MR_ MU_ YT_ MX_ MD_ MC_ MA_ MZ_ MM_ NA_ NP_
-        AN_ NL_ CA_NB NC_ CA_NF NF_ NI_
-        NE_ NG_ MP_ KP_ CA_NT NO_ CA_NS CA_NU OM_
-        CA_ON PK_ PA_ PG_ PY_ PE_ PH_ PN_ PL_
-        PT_ CA_PE PR_ QA_ CA_QC RO_ RU_RW_ SH_ KN_
-        LC_ VC_ WS_ ST_ CA_SK SA_ SN_ RS_ SC_
-        SL_ SG_ SK_ SI_ SB_ SO_ ZA_ KR_ ES_ LK_ SD_ SR_
-        SZ_ SE_ CH_ SY_ TW_ TJ_ TZ_ TH_
-        TG_ TO_ TT_ TU TN_ TR_ TM_ UG_ UA_ AE_ UN_ UY_
-        UZ_ VU_ VE_ VN_ VI_ YE_ CA_YT ZM_ ZW_
-        EC_ EG_ FL GA GQ_ HI HR_ IA ID IL IO_ IN KS
-        KH_ KY KM_ LA MA MD ME
-        MI MN MO MS MT NC ND NE NH NJ NM NV NY OH OK
-        OR PA RI SC SV_ SD TD_ TN TX UT VA VT VG_
-        WA WI WV WY"""
+    if regions is None:
+        regions = """AF AL_ AI_ AQ_ AG_ AR_ AK AL AM_
+            AO_ AS_ AR AW_ AU_ AT_
+            AZ_ BA_ BE_ BB_ BG_ BO_ BR_ BF_
+            BT_ BS_ BI_ BM_ BB_ BY_ BZ_ BJ_ BW_ AZ CA CA_AB
+            CA_BC CD_ CK_ CF_ CG_ CL_ CM_ CO CO_ CN_ CR_ CT
+            CU_ CV_ CY_ CZ_ DE DK_ DJ_ DM_ DO_
+            DZ EE_ ET_ FK_ FM_ FJ_ FI_ FR_ GF_ PF_
+            GA_ GM_ GE_ DE_ GH_ GI_ KY_ GB_ GR_ GL_ GD_
+            GU_ GT_ GN_ GW_ GY_ HT_ HN_ HK_ HU_ IS_ IN_
+            ID_ IR_ IQ_ IE_ IL_ IT_ CI_ JM_ JP_
+            JO_ KZ_ KE_ KI_ KW_ LA_ LV_ LB_ LS_ LR_ LY_
+            LT_ LU_ MK_ MG_ MW_ MY_ MV_ ML_ CA_MB
+            MH_ MR_ MU_ YT_ MX_ MD_ MC_ MA_ MZ_ MM_ NA_ NP_
+            AN_ NL_ CA_NB NC_ CA_NF NF_ NI_
+            NE_ NG_ MP_ KP_ CA_NT NO_ CA_NS CA_NU OM_
+            CA_ON PK_ PA_ PG_ PY_ PE_ PH_ PN_ PL_
+            PT_ CA_PE PR_ QA_ CA_QC RO_ RU_RW_ SH_ KN_
+            LC_ VC_ WS_ ST_ CA_SK SA_ SN_ RS_ SC_
+            SL_ SG_ SK_ SI_ SB_ SO_ ZA_ KR_ ES_ LK_ SD_ SR_
+            SZ_ SE_ CH_ SY_ TW_ TJ_ TZ_ TH_
+            TG_ TO_ TT_ TU TN_ TR_ TM_ UG_ UA_ AE_ UN_ UY_
+            UZ_ VU_ VE_ VN_ VI_ YE_ CA_YT ZM_ ZW_
+            EC_ EG_ FL GA GQ_ HI HR_ IA ID IL IO_ IN KS
+            KH_ KY KM_ LA MA MD ME
+            MI MN MO MS MT NC ND NE NH NJ NM NV NY OH OK
+            OR PA RI SC SV_ SD TD_ TN TX UT VA VT VG_
+            WA WI WV WY"""
+    else:
+        regions = '_ '.join(regions.split(' '))
 
     networks = ['AWOS']
     metadata_list = {}

act/io/conf/noaapsl_SurfaceMet.yaml

@@ -543,3 +543,86 @@ mnt:
       long_name: Hail
       units: mm
       _type: float32
+
+ctd:
+  info:
+    name: Courtland, AL
+    lat:
+      value: 34.66
+      long_name: North latitude
+      units: degree_N
+      standard_name: latitude
+    lon:
+      value: 87.35
+      long_name: West longitude
+      units: degree_W
+      standard_name: longitude
+    alt:
+      value: 187.
+      long_name: Altitude above mean sea level
+      units: m
+      standard_name: altitude
+  operational_date_range1:
+    _date_range: ['2021-09-15 18:12:00', '3000-01-01 00:00:00']
+    Datalogger_ID:
+      _delete: True
+    Year:
+      _delete: True
+    J_day:
+      _delete: True
+    HoursMinutes:
+      _delete: True
+    Pressure:
+      long_name: Atmospheric Presure
+      units: mb
+      standard_name: air_pressure
+      _type: float32
+    Temperature:
+      long_name: Atmospheric Temperature
+      units: degC
+      standard_name: air_temperature
+      _type: float32
+    Relative_Humidity:
+      long_name: Atmospheric Relative_Humidity
+      units: percent
+      standard_name: relative_humidity
+      _type: float32
+    Wind_Speed_Scalar:
+      long_name: Scalar Wind Speed
+      units: m/s
+      _type: float32
+    Wind_Speed_Vector:
+      long_name: Vector Wind Speed
+      units: m/s
+      standard_name: wind_speed
+      _type: float32
+    Wind_Direction:
+      long_name: Wind Direction
+      units: degree
+      standard_name: wind_from_direction
+      _type: float32
+    Wind_Direction_STD:
+      long_name: Wind Direction Standard Deviation
+      units: degree
+      standard_name: wind_from_direction
+      cell_method: "time: standard_deviation"
+      _type: float32
+    Battery_Voltage:
+      long_name: Logger Battery Voltage
+      units: V
+      _type: float32
+    Solar_Radiation:
+      long_name: Solar Radiation
+      units: 'W/m^2'
+    Net_Radiation:
+      long_name: Net Radiation
+      units: 'W/m^2'
+    Precipitation:
+      long_name: Precipitation
+      units: mm
+      _type: float32
+    Wind_Speed_Max:
+      long_name: Maximum Wind Speed
+      units: m/s
+      standard_name: wind_speed_of_gust
+      _type: float32

examples/discovery/plot_asos_temp.py

@@ -11,8 +11,7 @@
 import act
 
 time_window = [datetime(2020, 2, 4, 2, 0), datetime(2020, 2, 10, 10, 0)]
-station = 'KORD'
-my_asoses = act.discovery.get_asos_data(time_window, station='ORD')
+my_asoses = act.discovery.get_asos_data(time_window, station='ORD', regions='IL')
 
 display = act.plotting.TimeSeriesDisplay(my_asoses['ORD'], subplot_shape=(2,), figsize=(15, 10))
 display.plot('temp', subplot_index=(0,))

examples/workflows/plot_amf3_comparisons.py

@@ -0,0 +1,118 @@
+"""
+Consolidation of Data Sources
+-----------------------------
+
+This example shows how to use ACT to combine multiple
+datasets to support ARM's AMF3.
+
+"""
+
+import act
+from datetime import datetime
+import matplotlib.pyplot as plt
+import numpy as np
+import os
+
+# Get Surface Meteorology data from the ASOS stations
+station = '1M4'
+time_window = [datetime(2024, 10, 19), datetime(2024, 10, 24)]
+ds_asos = act.discovery.get_asos_data(time_window, station=station, regions='AL')[station]
+ds_asos = ds_asos.where(~np.isnan(ds_asos.tmpf), drop=True)
+ds_asos['tmpf'].attrs['units'] = 'degF'
+ds_asos.utils.change_units(variables='tmpf', desired_unit='degC', verbose=True)
+
+# Pull EPA data from AirNow
+# You need an account and token from https://docs.airnowapi.org/ first
+airnow_token = os.getenv('AIRNOW_API')
+if airnow_token is not None and len(airnow_token) > 0:
+    latlon = '-87.453,34.179,-86.477,34.787'
+    ds_airnow = act.discovery.get_airnow_bounded_obs(
+        airnow_token, '2024-10-19T00', '2024-10-24T23', latlon, 'OZONE,PM25', data_type='B'
+    )
+    ds_airnow = act.utils.convert_2d_to_1d(ds_airnow, parse='sites')
+    sites = ds_airnow['sites'].values
+    airnow = True
+
+# Get NOAA PSL Data from Courtland
+results = act.discovery.download_noaa_psl_data(
+    site='ctd', instrument='Temp/RH', startdate='20241019', enddate='20241024'
+)
+ds_noaa = act.io.read_psl_surface_met(results)
+
+# Place your username and token here
+username = os.getenv('ARM_USERNAME')
+token = os.getenv('ARM_PASSWORD')
+
+# Download ARM data for the MET, OZONE, and SMPS
+if username is not None and token is not None and len(username) > 1:
+    # Example to show how easy it is to download ARM data if a username/token are set
+    results = act.discovery.download_arm_data(
+        username, token, 'bnfmetM1.b1', '2024-10-19', '2024-10-24'
+    )
+    ds_arm = act.io.arm.read_arm_netcdf(results)
+
+    results = act.discovery.download_arm_data(
+        username, token, 'bnfaoso3M1.b1', '2024-10-19', '2024-10-24'
+    )
+    ds_o3 = act.io.arm.read_arm_netcdf(results, cleanup_qc=True)
+    ds_o3.qcfilter.datafilter('o3', rm_assessments=['Suspect', 'Bad'], del_qc_var=False)
+
+    results = act.discovery.download_arm_data(
+        username, token, 'bnfaossmpsM1.b1', '2024-10-19', '2024-10-24'
+    )
+    ds_smps = act.io.arm.read_arm_netcdf(results)
+
+    # Set up display and plot all the data
+    display = act.plotting.TimeSeriesDisplay(
+        {'ASOS': ds_asos, 'ARM': ds_arm, 'EPA': ds_airnow, 'NOAA': ds_noaa, 'ARM_O3': ds_o3},
+        figsize=(12, 10),
+        subplot_shape=(3,),
+    )
+    # Plot surface temperature from ASOS, NOAA, and ARM sites
+    title = 'Comparison of ARM MET, NOAA Courtland, and Haleyville ASOS Station'
+    display.plot('tmpf', dsname='ASOS', label='ASOS', subplot_index=(0,))
+    display.plot('Temperature', dsname='NOAA', label='NOAA', subplot_index=(0,))
+    display.plot('temp_mean', dsname='ARM', label='ARM', subplot_index=(0,), set_title=title)
+    display.day_night_background(dsname='ARM', subplot_index=(0,))
+
+    # Plot ARM and EPA Ozone data
+    title = 'Comparison of ARM and EPA Ozone Measurements'
+    display.plot('o3', dsname='ARM_O3', label='ARM', subplot_index=(1,))
+    if airnow:
+        display.plot('OZONE_sites_1', dsname='EPA', label='EPA' + sites[1], subplot_index=(1,))
+        display.plot(
+            'OZONE_sites_2',
+            dsname='EPA',
+            label='EPA' + sites[2],
+            subplot_index=(1,),
+            set_title=title,
+        )
+    display.set_yrng([0, 70], subplot_index=(1,))
+    display.day_night_background(dsname='ARM', subplot_index=(1,))
+
+    # Plot ARM SMPS Concentrations and EPA PM2.5 data on different axes
+    title = 'ARM SMPS Concentrations and EPA PM2.5'
+    if airnow:
+        display.plot('PM2.5_sites_0', dsname='EPA', label='EPA ' + sites[0], subplot_index=(2,))
+        display.plot(
+            'PM2.5_sites_2',
+            dsname='EPA',
+            label='EPA ' + sites[2],
+            subplot_index=(2,),
+            set_title=title,
+        )
+    display.set_yrng([0, 25], subplot_index=(2,))
+    ax2 = display.axes[2].twinx()
+    ax2.plot(ds_smps['time'], ds_smps['total_N_conc'], label='ARM SMPS', color='purple')
+    ax2.set_ylabel('ARM SMPS (' + ds_smps['total_N_conc'].attrs['units'] + ')')
+    ax2.set_ylim([0, 7000])
+    ax2.legend(loc=1)
+    display.day_night_background(dsname='ARM', subplot_index=(2,))
+
+    # Set legends
+    for ax in display.axes:
+        ax.legend(loc=2)
+
+    plt.show()
+else:
+    pass

tests/discovery/test_asos.py

@@ -7,7 +7,7 @@
 
 def test_get_ord():
     time_window = [datetime(2020, 2, 4, 2, 0), datetime(2020, 2, 12, 10, 0)]
-    my_asoses = act.discovery.get_asos_data(time_window, station='ORD')
+    my_asoses = act.discovery.get_asos_data(time_window, station='ORD', regions='IL')
     assert 'ORD' in my_asoses.keys()
     assert np.all(
         np.equal(