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Plots Directory

This directory contains all visualizations generated by the gridMET bias correction and CONUS-AgWeather analysis scripts (~1.0 GB total).

Data Availability

The plots are available from Zenodo:

DOI

Download Plots.zip and extract its contents into the Plots/ directory at the repository root.

Directory Structure

Plots/
├── Boxplots/                         # Bias boxplots by time period (~2.5 MB)
├── Climate/                          # Climate zone correlation plots (~20 MB)
├── CONUS-AgWeather_v1_ETo_Stats/     # ETo QC analysis statistics (~2.2 MB)
├── CONUS-AgWeather_v1_Var_Stats/     # Variable QC analysis statistics (~9.2 MB)
├── Correlation_Plots_All/            # All-station correlation matrices (~2.6 MB)
├── Crop_Bias_Distributions/          # Crop-type bias distributions (~10 MB)
├── East_vs_West/                     # East/West regional comparisons (~8.3 MB)
├── GridMET_Plots/                    # GridMET validation plots (~121 MB)
├── OpenET_accuracy/                  # OpenET vs flux tower accuracy (~1.3 MB)
├── Site_Analysis_GridMET/            # Site-level GridMET analysis (~80 MB)
├── Site_Analysis_OpenET/             # Site-level OpenET analysis (~762 MB)
├── Station_Climate/                  # Climate-grouped station plots (~18 MB)
└── station_map_conus_agweather.png   # Station location map (~16 MB)

Plot Directories and Generating Scripts

Directory Generating Script Description
Boxplots/ scripts/boxplots_stats.py Bias boxplots grouped by region and climate zone, with summary statistics CSVs
Climate/ corr_analysis_gridmet.py Köppen climate-stratified Pearson correlation matrices
CONUS-AgWeather_v1_ETo_Stats/ scripts/conus_agweather_eto_analysis.py Pre/post-QC ETo analysis plots and statistics
CONUS-AgWeather_v1_Var_Stats/ scripts/conus_agweather_var_analysis.py Pre/post-QC variable (Rs, Rso) comparison plots
Correlation_Plots_All/ corr_analysis_gridmet.py All-station correlation matrices between ET and other variables
Crop_Bias_Distributions/ corr_analysis_gridmet.py Bias distributions grouped by CDL crop type
East_vs_West/ corr_analysis_gridmet.py Regional correlation matrices (East vs West of 100th meridian)
GridMET_Plots/ corr_analysis_gridmet.py GridMET bias comparison scatter plots
OpenET_accuracy/ scripts/OpenET_flux_grouped_scatter_plots.py, scripts/monthly_climos.py, scripts/monthly_error_delta_bias_heatmaps.py, scripts/monthly_ET_vs_ETo_error_scatter.py OpenET vs flux tower accuracy plots
Site_Analysis_GridMET/ scripts/site_analysis_gridmet.py Site-level GridMET vs station ET scatter plots with metrics
Site_Analysis_OpenET/ scripts/site_analysis_openet.py Site-level OpenET model scatter plots with metrics
Station_Climate/ scripts/station_climate_plots.py Station variable distributions by Köppen climate zone
station_map_conus_agweather.png scripts/gen_map.py CONUS station location map with observation counts

Detailed Plot Descriptions

Boxplots/

Script: gridmetbias/scripts/boxplots_stats.py

Bias ratio boxplots organized by time period subdirectories (e.g., Annual/, Summer (JJA)/).

Contents:

  • {variable}_Bias_Boxplots_{time_period}.png - Boxplots showing:
    • All sites combined
    • East vs. West of 100th meridian
    • By lumped Köppen climate zone
  • {variable}_Bias_Stats_{time_period}.csv - Summary statistics (n stations, n days, min, max, median, Q1, Q3, mean, std)

Variables: ETo, ETr, ea, u2, srad, tmin, tmax

Climate/

Script: gridmetbias/corr_analysis_gridmet.py → biaslibs.plot_bias_corr_matrix_climate()

Pearson correlation heatmaps between monthly ET bias ratios and other variable bias ratios, stratified by Köppen climate zones.

Subdirectories:

  • All_pval_True/ - Shows all correlations
  • All_pval_False/ - Shows only statistically significant correlations (p < 0.05)

CONUS-AgWeather_v1_ETo_Stats/

Script: gridmetbias/scripts/conus_agweather_eto_analysis.py

Analysis of CONUS-AgWeather ETo data before and after quality control.

Contents:

  • QC factor distributions (daily and annual)
  • Station-level ETo comparison plots
  • Summary statistics by climate zone

CONUS-AgWeather_v1_Var_Stats/

Script: gridmetbias/scripts/conus_agweather_var_analysis.py

Analysis of solar radiation (Rs, Rso) and other variables pre/post-QC.

Contents:

  • Three-panel comparison plots:
    • (a) Original Rs and Rso
    • (b) Corrected Rs and Rso
    • (c) Percent change between corrected and original

Correlation_Plots_All/

Script: gridmetbias/corr_analysis_gridmet.py → biaslibs.plot_bias_corr_matrix_all()

Correlation matrices for all stations combined, showing relationships between monthly ET bias ratios and other meteorological variable bias ratios.

Crop_Bias_Distributions/

Script: gridmetbias/corr_analysis_gridmet.py → biaslibs.plot_irr_crop_bias_distributions()

Bias distributions grouped by USDA Cropland Data Layer (CDL) crop types:

  • Corn, Cotton, Soybeans, Wheat, Alfalfa, Other

East_vs_West/

Script: gridmetbias/corr_analysis_gridmet.py → biaslibs.plot_bias_corr_matrix_lon()

Regional comparison plots split at the 100th meridian.

Subdirectories:

  • All_pval_True/ - All correlations shown
  • All_pval_False/ - Significant correlations only (p < 0.05)

Contents: {ET}_{VAR}_{Region}_corr.png files

GridMET_Plots/

Script: gridmetbias/corr_analysis_gridmet.py → biaslibs.gridmet_bias_comp_analysis()

GridMET bias comparison visualizations.

Subdirectories:

  • All/ - All stations combined
    • GridMET_Daily_All_Station_Data.csv - Daily gridMET data for all stations
    • GridMET_Monthly_All_Station_Data.csv - Monthly aggregated data
  • Individual site directories with scatter plots

OpenET_accuracy/

Scripts: gridmetbias/scripts/OpenET_flux_grouped_scatter_plots.py, scripts/monthly_climos.py, scripts/monthly_error_delta_bias_heatmaps.py, scripts/monthly_ET_vs_ETo_error_scatter.py

OpenET model accuracy assessment against flux tower ET.

Contents:

  • Figure6_croplands_monthly_openet_vs_flux.jpg - Croplands monthly OpenET vs flux scatter plots (OpenET_flux_grouped_scatter_plots.py)
  • Figure7_croplands_monthly_climatology.jpg - Monthly ET climatology comparison (monthly_climos.py)
  • Figure8_absolute_error_reduction_heatmaps.jpg - Error reduction heatmaps by land cover and model (monthly_error_delta_bias_heatmaps.py)
  • Figure9_error_reduction_scatter_by_landcover.jpg - Error reduction scatter by land cover (monthly_ET_vs_ETo_error_scatter.py)

OpenET Models: EEMETRIC, SSEBOP, SIMS, ensemble_mean

Land Cover Types: Croplands, Evergreen Forests, Grasslands, Mixed Forests, Shrublands, Wetland/Riparian

Site_Analysis_GridMET/

Script: gridmetbias/scripts/site_analysis_gridmet.py

Site-level scatter plots comparing gridMET reference ET against station ET.

Contents:

  • {SITE_ID}/ - Individual site directories with scatter plots
  • All/ - All sites combined
  • All_cropland_sites_gridmet_metrics.csv - Metrics summary (R², MAE, MBE)

Plot panels: Corrected vs Uncorrected gridMET comparisons

Site_Analysis_OpenET/

Script: gridmetbias/scripts/site_analysis_openet.py

Site-level scatter plots for all OpenET models.

Contents:

  • Individual site directories with multi-panel scatter plots
  • Metrics CSVs with R², MAE, MBE for each model

Models: EEMETRIC, SSEBOP, SIMS, GEESEBAL, PTJPL, DISALEXI, ensemble_mean

Station_Climate/

Script: gridmetbias/scripts/station_climate_plots.py

Station variable distributions grouped by Köppen climate classification.

Contents: Two-panel plots for each variable:

  • Left: KDE/histogram for all sites
  • Right: Violin plots by climate zone (Bsk+Bsh, Bwh+Bwk, Cfa, Csa+Csb, Dfa+Dfb)

Variables: ETo, ETr, temperatures, humidity, vapor pressure, solar radiation, wind speed, precipitation

station_map_conus_agweather.png

Script: gridmetbias/scripts/gen_map.py

Three-panel map of weather station locations across CONUS:

  • (a) Days of weather observations
  • (b) Years of weather observations
  • (c) Average annual record completeness (%)

Quick Reference: Script → Output Mapping

Script Output Directories
corr_analysis_gridmet.py Climate/, Correlation_Plots_All/, Crop_Bias_Distributions/, East_vs_West/, GridMET_Plots/
scripts/boxplots_stats.py Boxplots/
scripts/conus_agweather_eto_analysis.py CONUS-AgWeather_v1_ETo_Stats/
scripts/conus_agweather_var_analysis.py CONUS-AgWeather_v1_Var_Stats/
scripts/gen_map.py station_map_conus_agweather.png
scripts/OpenET_flux_grouped_scatter_plots.py OpenET_accuracy/
scripts/monthly_climos.py OpenET_accuracy/
scripts/monthly_error_delta_bias_heatmaps.py OpenET_accuracy/
scripts/monthly_ET_vs_ETo_error_scatter.py OpenET_accuracy/
scripts/site_analysis_gridmet.py Site_Analysis_GridMET/
scripts/site_analysis_openet.py Site_Analysis_OpenET/
scripts/station_climate_plots.py Station_Climate/

Citations

Journal Articles:

Volk, J. M., Dunkerly, C., Majumdar, S., Huntington, J. L., Minor, B. A., Kim, Y., Morton, C. G., ReVelle, P., Kilic, A., Melton, F., Allen, R. G., Pearson, C., Purdy, A. J., & Caldwell, T. G. (2026). Assessing and Correcting Bias in Gridded Reference Evapotranspiration over Agricultural Lands Across the Contiguous United States. Under review in Agricultural Water Management. Preprint: https://doi.org/10.31223/X54F38

Dunkerly, C., Volk, J. M., Majumdar, S., Huntington, J. L., Allen, R. G., Pearson, C., Kim, Y., Morton, C. G., Minor, B. A., ReVelle, P., Kilic, A., Melton, F., Purdy, A. J., & Caldwell, T. G. (2026). A Benchmark Dataset of Agricultural Weather Stations over the Contiguous United States for Evapotranspiration Applications. Under review in Nature Scientific Data. Preprint: https://doi.org/10.31223/X56T9Z.

Data Releases:

Volk, J., Dunkerly, C., Majumdar, S., Huntington, J., Minor, B., Kim, Y., Morton, C., ReVelle, P., Kilic, A., Melton, F., Allen, R., Pearson, C., Purdy, A., & Caldwell, T. (2026). CONUS Gridded Reference Evapotranspiration Bias Correction: Inputs, Station Validation, and Outputs (gridMET/OpenET) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18673484

Dunkerly, C., Volk, J. M., Majumdar, S., Huntington, J. L., Allen, R. G., Pearson, C., Kim, Y., Morton, C. G., Minor, B. A., ReVelle, P., Kilic, A., Melton, F., Purdy, A. J., & Caldwell, T. G. (2026). CONUS-AgWeather, a high-quality benchmark daily agricultural weather station dataset for evapotranspiration applications in the Contiguous United States (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18122157