Improving the National Solar Radiation Data Base using PSM V4

The National Solar Radiation Database (NSRDB) provides comprehensive global solar resource data at a high temporal and spatial resolution. The NSRDB employs satellite-based solar modeling to retrieve cloud properties and subsequently compute solar radiation. The other input parameters—including aerosol optical properties, precipitable water vapor, surface albedo, temperature, and pressure—are also employed by the model. The NSRDB data were recently updated using physical solar model (PSM) version 4, which includes an improved gap-filling algorithm, based on machine-learning techniques, for the missing cloud properties, corrections of solar position calculations, an enhanced algorithm for computing land-surface albedo over snow or ice surfaces, and a physics-based model for computing DNI. The updated PSM was used to generate solar radiation data for 2021-2023, including global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance (DHI). This model was also employed to reprocess all previous NSRDB data from 1998-2020. The NSRDB was validated using high-quality measurements from surface sites, including NOAA’s the Surface Radiation Budget (SURFRAD). According to data for 2019-2023, the NSRDB processed by the latest PSM has mean bias error (MBE) within 5% and 8%, respectively, for GHI and DNI. This study provides users with the latest NSRDB information and outlines plans for ongoing development and updates.

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Publication Details

Published
2025-06-08
DOI
https://doi.org/10.1109/pvsc59419.2025.11133215
Citations
1
Primary Topic
Solar Radiation and Photovoltaics
Type
article
Field-Weighted Citation Impact
2.48

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Improving the National Solar Radiation Data Base using PSM V4

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article

Improving the National Solar Radiation Data Base using PSM V4

Brandon Benton, Manajit Sengupta, Michael P. Foster, Jaemo Yang, Aron Habte, Yu Xie, Andrew K. Heidinger, Paul Edwards
article en
1 citations

Abstract

The National Solar Radiation Database (NSRDB) provides comprehensive global solar resource data at a high temporal and spatial resolution. The NSRDB employs satellite-based solar modeling to retrieve cloud properties and subsequently compute solar radiation. The other input parameters—including aerosol optical properties, precipitable water vapor, surface albedo, temperature, and pressure—are also employed by the model. The NSRDB data were recently updated using physical solar model (PSM) version 4, which includes an improved gap-filling algorithm, based on machine-learning techniques, for the missing cloud properties, corrections of solar position calculations, an enhanced algorithm for computing land-surface albedo over snow or ice surfaces, and a physics-based model for computing DNI. The updated PSM was used to generate solar radiation data for 2021-2023, including global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance (DHI). This model was also employed to reprocess all previous NSRDB data from 1998-2020. The NSRDB was validated using high-quality measurements from surface sites, including NOAA’s the Surface Radiation Budget (SURFRAD). According to data for 2019-2023, the NSRDB processed by the latest PSM has mean bias error (MBE) within 5% and 8%, respectively, for GHI and DNI. This study provides users with the latest NSRDB information and outlines plans for ongoing development and updates.

National Laboratory of the Rockies (US), National Oceanic and Atmospheric Administration (US), University of Wisconsin–Madison (US), NOAA Oceanic and Atmospheric Research (US)
U.S. Department of Energy, National Renewable Energy Laboratory
Affordable and clean energy
Openalex Percentile: Top 9%
Solar Radiation and Photovoltaics
2.48
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