National Solar Radiation Database

National Solar Radiation Database
Name	National Solar Radiation Database
Country	United States
Maintained by	National Renewable Energy Laboratory
First released	1991
Latest version	NSRDB 1991–2020 (2023 update)
Data types	Solar irradiance, meteorological variables, modeled clear-sky and satellite-derived estimates
Access	Public download and API

National Solar Radiation Database provides a comprehensive archive of solar irradiance and meteorological data for the United States used in renewable energy analysis, climate research, and engineering. Developed and hosted by the National Renewable Energy Laboratory in collaboration with the National Oceanic and Atmospheric Administration, the database synthesizes observations and modeled products to support institutions such as the Department of Energy, utilities like Pacific Gas and Electric Company, research centers including the Solar Energy Technologies Office and academic programs at Massachusetts Institute of Technology and Stanford University.

History and development

The database traces origins to efforts by the Solar Energy Research Institute and early work at Sandia National Laboratories in the 1970s and 1980s to compile solar resource assessments for projects like Solar One and Solar Two. Formal establishment occurred with the National Solar Radiation Data Base (1991) initiative coordinated by the National Renewable Energy Laboratory and supported by the U.S. Department of Energy and National Oceanic and Atmospheric Administration. Major updates integrated satellite-era methods influenced by programs at NASA (e.g., GOES) and international collaborations with institutions such as the European Centre for Medium-Range Weather Forecasts and World Meteorological Organization. Subsequent version releases (2005, 2012, 2018, 2023) incorporated advances from Geostationary Operational Environmental Satellite algorithms, the MODIS instrument, and enhanced surface measurement networks like the Baselining Solar Monitoring Network and the Surface Radiation Budget community.

Data content and methodology

The NSRDB combines ground-based measurements from networks operated by National Oceanic and Atmospheric Administration, Atmospheric Radiation Measurement sites, and regional utilities with satellite-derived retrievals based on GOES, Himawari, and MODIS radiance inputs. Variables include global horizontal irradiance, direct normal irradiance, diffuse horizontal irradiance, wavelength-resolved irradiance, air temperature, wind speed, and dew point—used by model frameworks such as the REST2 clear-sky model and statistical gap-filling methods informed by Machine Learning research at Lawrence Berkeley National Laboratory and Argonne National Laboratory. Data processing pipelines employ geostationary satellite calibration techniques derived from NOAA STAR and radiative transfer coding from the LibRadtran project, with metadata standards aligned to Federal Geographic Data Committee practices.

Coverage and spatial resolution

Coverage spans the United States including the Contiguous United States, Alaska, Hawaii, and selected territories with temporal records from hourly to sub-hourly cadences over multi-decade periods (e.g., 1991–2020). Spatial resolution varies by release and product type: gridded products are commonly provided at 4-km or 1-km resolution leveraging geostationary satellite footprints similar to those used by EUMETSAT and the Joint Polar Satellite System, while point-specific modeled time series correspond to locations of measurement sites such as the NOAA Cooperative Observer Program stations and university testbeds at National Renewable Energy Laboratory's Solar Radiation Research Laboratory.

Access, formats, and tools

Users retrieve data through a public Application Programming Interface maintained by the National Renewable Energy Laboratory, bulk FTP archives, and web portals compatible with GIS clients like ArcGIS and QGIS. File formats include CSV, NetCDF, and API JSON that integrate with modeling platforms such as SAM (System Advisor Model), PVWatts, and simulation tools developed at NREL and Sandia National Laboratories. Community tools and libraries for Python and MATLAB—originating from open-source projects hosted by organizations including GitHub and tutorials from National Renewable Energy Laboratory staff—facilitate ingestion into workflows used by engineers at firms like First Solar and researchers at University of California, Berkeley.

Applications and impact

The database underpins feasibility studies for utility-scale projects by developers such as NextEra Energy and system designers at SunPower Corporation, supports yield forecasting for grid operators including California Independent System Operator and PJM Interconnection, and informs policy analyses by the U.S. Energy Information Administration and International Renewable Energy Agency. NSRDB products enable climate trend studies cited in publications from Nature, Proceedings of the National Academy of Sciences, and Journal of Applied Meteorology and Climatology, and have been used in economic assessments for incentives like state-level renewable portfolio standards administered by agencies such as the California Energy Commission.

Limitations and quality control

Limitations stem from satellite retrieval uncertainties in complex terrain (e.g., Rocky Mountains, Appalachian Mountains), challenges resolving urban microclimates in metropolitan regions like New York City and Los Angeles, and biases during snow-covered conditions in Alaska and Colorado. Quality control procedures integrate outlier detection, cross-validation with ground-truth from AERONET and SURFRAD sites, and versioning protocols informed by standards from the National Institute of Standards and Technology and the Federal Geospatial Data Committee. Users are advised to consult metadata and uncertainty layers provided with each release and to complement modeled estimates with local measurements from laboratory networks at Sandia National Laboratories or university solar test facilities.

Category:Solar energy Category:Climate data