Aug 3, 2022

WRF-Solar AOD550 & Clear-Sky Irradiance Forecasts & Verifying Observations over CONUS


ERROR
Cookies must be enabled.

Version: 1.0

This dataset is fully described in and is a companion of Lee et al. (2022):

Lee, J. A., P. A. Jiménez, J. Dudhia, and Y.-M. Saint-Drenan, 2023: Impacts of the aerosol representation in WRF-Solar clear-sky irradiance forecasts over CONUS. J. Appl. Meteor. Climatol., 62, 227–250, https://doi.org/10.1175/JAMC-D-22-0059.1.

Aerosol optical depth (AOD) is a primary source of solar irradiance forecast error in clear-sky conditions. Improving the accuracy of AOD in NWP models like WRF will thus reduce error in both direct normal irradiance (DNI) and global horizontal irradiance (GHI), which should improve solar power forecast errors, at least in cloud-free conditions. In this study clear-sky GHI and DNI was analyzed from four configurations of the WRF-Solar model with different aerosol representations: 1) The default Tegen climatology; 2) Imposing AOD forecasts from the GEOS-5 model; 3) Imposing AOD forecasts from the Copernicus Atmosphere Monitoring Service (CAMS) model; and 4) The Thompson-Eidhammer aerosol-aware water/ice-friendly aerosol climatology. Over eight months of these 15-min output forecasts are compared against high-quality irradiance observations at NOAA SURFRAD and Solar Radiation (SOLRAD) stations located across CONUS. In general, WRF-Solar with GEOS-5 AOD had the lowest errors in clear-sky DNI, while WRF-Solar with CAMS AOD had the highest errors, higher even than the two aerosol climatologies, which is consistent with validation of the four AOD550 datasets against AERONET stations. For clear-sky GHI, the statistics differed little between the four models, as expected due to the lesser sensitivity of GHI to aerosol loading. Hourly-average clear-sky DNI and GHI was also analyzed, and additionally compared with CAMS model output directly. CAMS irradiance performed competitively with the best WRF-Solar configuration (with GEOS-5 AOD). The markedly different performance of CAMS versus WRF-Solar with CAMS AOD indicates that CAMS is apparently less sensitive to AOD550 than WRF-Solar is.

wrf_aeronet_aod550_by_cycle_20191119-20200730.nc:
NetCDF, 317 MB
WRF-Solar AOD550 spatially interpolated to AERONET stations and AERONET observed AOD550. Organized in arrays sorted by model cycle time (once daily at 09 UTC from 20191119 to 20200730) and model lead time (every 15 min to 45 h). The four WRF-Solar experiments correspond to the four from Lee et al. (2022).

wrf_surfrad_solrad_inst_dni_ghi_by_cycle_20191119-20200730.nc:
NetCDF, 102 MB
WRF-Solar clear-sky DNI and clear-sky GHI interpolated to SURFRAD & SOLRAD stations, and SURFRAD & SOLRAD observed clear-sky DNI and clear-sky GHI. Organized in arrays sorted by model cycle time (once daily at 09 UTC from 20191119 to 20200730) and model lead time (every 15 min to 45 h). The four WRF-Solar experiments correspond to the four from Lee et al. (2022).

wrf_surfrad_solrad_hrly_dni_ghi_by_cycle_20191119-20200730.nc:
NetCDF, 26 MB
WRF-Solar clear-sky DNI and clear-sky GHI interpolated to SURFRAD & SOLRAD stations, and SURFRAD & SOLRAD observed clear-sky DNI and clear-sky GHI. All values are averaged to time-ending 1-hourly averages. Organized in arrays sorted by model cycle time (once daily at 09 UTC from 20191119 to 20200730) and model lead time (every 1 h to 45 h). The four WRF-Solar experiments correspond to the four from Lee et al. (2022).

cams_surfrad_solrad_hrly_dni_ghi_by_cycle_20191119-20200730.nc:
NetCDF, 26 MB
CAMS clear-sky DNI and clear-sky GHI interpolated to SURFRAD & SOLRAD stations, and SURFRAD & SOLRAD observed clear-sky DNI and clear-sky GHI. All values are averaged to time-ending 1-hourly averages. Organized in arrays sorted by model cycle time (once daily at 00 UTC from 20191119 to 20200730) and model lead time (every 1 h to 54 h).

DOI
https://doi.org/10.5065/v94m-y402
Download Data and Documentation
4 Files, 451.41 MB Total Size

Individual Files - View, select, and download individual files from this Dataset.

Zip File - Download a ZIP file containing all files.

Python script - Download all files via Python 3, preferred for all operating systems.

Wget shell script - Download all files using Wget, preferred for Linux.

Curl shell script - Download all files via Curl, preferred for MacOS.

Temporal Range
2019-11-19 to 2020-07-30
Temporal Resolution
1.0 hour
15.0 minute
Related Links
AERONET SOLRAD SURFRAD WRF-Solar
GCMD Science Keywords
  • Atmosphere > Aerosols > Aerosol Optical Depth/Thickness
  • Atmosphere > Atmospheric Radiation > Solar Irradiance
  • Models > Weather Research/Forecast Models
GCMD Platform Types
  • Other > Models > Wrf > Weather Research And Forecasting (Wrf) Model
File Media Types
  • application/x-hdf
Support Contact
Jared Lee
UCAR/NCAR - Research Applications Laboratory
jaredlee@ucar.edu

Data Curator
GDEX Curator
UCAR/NCAR - GDEX
gdex@ucar.edu

Credit
The authors gratefully acknowledge direct funding for this work from NASA under Grant No. 80NSSC18K0330.
Legal Constraints
Creative Commons Attribution 4.0 International License.
Access Constraints
None
Full Metadata
DIF XML
ISO19139 XML
OAI DC
JSON-LD
Version History
1.0

Latitude Range
25.7° N to 49.7° N
Longitude Range
123.2° W to 63.5° W
Authors
Lee, Jared A.
Jiménez, Pedro A.
Dudhia, Jimy
Saint-Drenan, Yves-Marie
Publisher
UCAR/NCAR - GDEX

Suggested Citation
Lee, Jared A., Jiménez, Pedro A., Dudhia, Jimy, Saint-Drenan, Yves-Marie. (2022). WRF-Solar AOD550 & Clear-Sky Irradiance Forecasts & Verifying Observations over CONUS. Version 1.0. UCAR/NCAR - GDEX. https://doi.org/10.5065/v94m-y402. Accessed 25 Nov 2024.
Downloads
196
Download Volume
3.21 GB Total