Workflow Step: geo -> analyze -> 01_met_summary

[rburghol]

• Summarizes met data for the given coverage and scenario. Scenario includes the datasource, which is tied to a specific varkey and potentially a property featureid+entity_type combo.
• Draft R script: precip_coverage_summary.R
• Example bash script to call R in workflow 06_plot_stormVolume

Testing/Running

Running in meta_model

scenario=stormVol_daymet # scenario=stormVol_prism

for i in usgs_ws_01613900 usgs_ws_01616100 usgs_ws_01673550; do
  /opt/model/meta_model/run_model raster_met $scenario $i auto geo analyze 01
done

R retrieval via om_vahydro_metric_grid()

library("hydrotools")
basepath='/var/www/R';
source("/var/www/R/config.R") # will need file in same folder/directory

# GET VAHydro 1.0 RIVERSEG l90_Qout DATA
mdf <- data.frame(
  'model_version' = c('met-1.0','met-1.0','met-1.0','met-1.0'),
  'runid' = c('stormVol_prism','stormVol_daymet','stormVol_prism','stormVol_daymet'),
  'metric' = c('precip_annual_max_in','precip_annual_max_in','precip_annual_min_in','precip_annual_min_in'),
  'runlabel' = c('prism_p_max_in','daymet_p_max_in','prism_p_min_in','daymet_p_min_in')
)
met_data <- om_vahydro_metric_grid(
  metric = metric, runids = mdf, bundle="watershed", ftype="usgs_full_drainage",
  base_url = paste(site,'entity-model-prop-level-export',sep="/"),
  ds = ds
)