Released to the public as part of the Department of Energy's Open Energy Data Initiative, the National Solar Radiation Database (NSRDB) is a serially complete collection of hourly and half-hourly values of the three most common measurements of solar radiation – global horizontal, direct normal, and diffuse horizontal irradiance — and meteorological data. These data have been collected at a sufficient number of locations and temporal and spatial scales to accurately represent regional solar radiation climates.

The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations for 1998-2023. The NSRDB is updated annually and provides foundational information to support U.S. Department of Energy programs, research, industry and the general public. The NSRDB provides time-series data at 30-minute resolution of resource averaged over surface cells of 0.038 degrees in both latitude and longitude, or nominally 4 km in size. Additionally time series data at 5 minutes for the US and 10 minutes for North, Central and South America at 2 km resolution are produced from the next generation of GOES satellites and made available from 2019. The solar radiation values represent the resource available to solar energy systems. The data was created using cloud properties which are generated using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms developed by the University of Wisconsin. Fast all-sky radiation model for solar applications (FARMS) in conjunction with the cloud properties, and aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary source are used to estimate solar irradiance (GHI, DNI, and DHI). The Global Horizontal Irradiance (GHI) is computed for clear skies using the REST2 model. For cloud scenes identified by the cloud mask, FARMS is used to compute GHI and FARMS DNI is used to compute the Direct Normal Irradiance (DNI). The PATMOS-X model uses radiance images in visible and infrared channels from the Geostationary Operational Environmental Satellite (GOES) series of geostationary weather satellites. Ancillary variables needed to run REST2 and FARMS (e.g., aerosol optical depth, precipitable water vapor, and albedo) are derived from NASA's Modern Era-Retrospective Analysis (MERRA-2) dataset. Temperature and wind speed data are also derived from MERRA-2 and provided for use in NREL's System Advisor Model (SAM) to compute PV generation.

The National Renewable Energy Laboratory's (NREL) Photovoltaic (PV) Rooftop Database (PVRDB) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for 128 metropolitan regions in the United States. The PVRDB data are organized by city and year of lidar collection. Five geospatial layers are available for each city and year: 1) the raster extent of the lidar collection, 2) buildings identified from the lidar data, 3) suitable developable planes for each building, 4) aspect values of the developable planes, and 5) the technical potential estimates of the developable planes.

The National Solar Radiation Database (NSRDB) was produced by the National Renewable Energy Laboratory under the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy. The NSRDB update is a collection of hourly values of the three most common measurements of solar radiation (i.e., global horizontal, direct normal, and diffuse horizontal) over a period of time adequate to establish means and extremes and at a sufficient number or locations to represent regional solar radiation climates. Nearly all of the solar data in the NSRDB are modeled, and only 40 sites have measured solar data - none of them with a complete period of record. Because of the data-filling methods used to accomplish the goal of serial completeness, NSRDB meteorological data are not suitable for climatological work. The meteorological fields in the NSRDB should be used only as ancillary data for solar deployment and sizing applications. Filled/interpolated meteorological data should not be used for climatic applications. (All such data are flagged.) The serially complete hourly data provided in the NSRDB update are provided in two output formats: 1) ground-based solar and meteorological dataset, and 2) 10 km gridded output produced by the SUNY model. The 1991-2010 NSRDB is an update of the 1991-2005 NSRDB released in 2006 and archived at NCDC. The updated NSRDB dataset an hourly ground-based data set of solar and meteorological fields for 1454 stations. The primary provider for ground-based data is NCDC, which are stored as site-year files in comma-separated value (CSV) American Standard Code for Information Interchange (ASCII) format. Station identification numbers use the six-digit United States Air Force (USAF) station ID numbering scheme. The measured solar radiation data came from multiple sources, including: Atmospheric Radiation Measurement Program, Department of Energy Florida Solar Energy Center, State of Florida Integrated Surface Irradiance Study and Surface Radiation Budget Measurement Networks, National Oceanic and Atmospheric Administration Air Resources Laboratory and Earth System Research Laboratory Global Monitoring Division Measurement and Instrumentation Data Center, National Renewable Energy Laboratory University of Oregon Solar Radiation Monitoring Laboratory Network University of Texas Solar Energy Laboratory. All meteorological data were provided by the National Climatic Data Center from its Integrated Surface Hourly Database (ISD) product. The NSRDB Statistics Files hold summary statistics for all Class I and Class II stations. The Daily Statistics provide monthly and annual averages of solar radiation and several meteorological parameters for both annual and a 20 year roll-up. The Hourly Statistics provide average diurnal profiles by hour for each station year for each solar parameter. The Persistence Statistics provide multiple levels of persistence for up to 30 days for each station for each solar parameter. These Summary Statistics files are documented in the NSRDB User's Manual.

The Solar Radiation Research Laboratory (SRRL) was established at the Solar Energy Research Institute (now NREL) in 1981 to provide continuous measurements of the solar resources, outdoor calibrations of pyranometers and pyrheliometers, and to characterize commercially available instrumentation. The SRRL is an outdoor laboratory located on South Table Mountain, a mesa providing excellent solar access throughout the year, overlooking Denver. Beginning with the basic measurements of global horizontal irradiance, direct normal irradiance and diffuse horizontal irradiance at 5-minute intervals, the SRRL Baseline Measurement System now produces more than 130 data elements at 1-min intervals that are available from the Measurement & Instrumentation Data Center Web site. Data sources include global horizontal, direct normal, diffuse horizontal (from shadowband and tracking disk), global on tilted surfaces, reflected solar irradiance, ultraviolet, infrared (upwelling and downwelling), photometric and spectral radiometers, sky imagery, and surface meteorological conditions (temperature, relative humidity, barometric pressure, precipitation, snow cover, wind speed and direction at multiple levels). Data quality control and assessment include daily instrument maintenance (M-F) with automated data quality control based on real-time examinations of redundant instrumentation and internal consistency checks using NREL's SERI-QC methodology. Operators are notified of equipment problems by automatic e-mail messages generated by the data acquisition and processing system. Radiometers are recalibrated at least annually with reference instruments traceable to the World Radiometric Reference (WRR).

The National Solar Radiation Data Base 1961-1990 (NSRDB) is a research product of the U.S. Department of Energy (DOE), National Renewable Energy Laboratory (NREL), Renewable Resource Data Center (RReDC). NSRDB is a serially complete collection of hourly values of the three most common measurements of solar radiation (global horizontal, direct normal, and diffuse horizontal) over a period of time adequate to establish means and extremes, and at a sufficient number of locations to represent regional solar radiation climates. The solar radiation and meteorological elements contained in the database are listed at [http://rredc.nrel.gov/solar/pubs/NSRDB/1-1.html]. Version 1.0 of NSRDB (NSRDB) contains 30 years of solar radiation and supplementary meteorological data from 237 NWS sites in the United States, plus sites in Guam and Puerto Rico.

The updated 1991-2005 NSRD holds solar and meteorological data for 1,454 locations in the United States and its territories as well as a one-tenth-degree gridded data set that contains hourly solar records for 8 years (1998-2005) for the United States (except Alaska above 60 degree latitude) for about 100,000 pixel locations (at a nominal 10-km-by-10-km pixel size). In the updated NSRD, all gaps in station records were filled, and the stations were classified by data quality. The National Climatic Data Center (NCDC) provides primary distribution of the updated NSRDB, but the NREL site holds a solar research version of the NSRDB with additional solar fields (without meteorological data). About 40 stations in the updated NSRDB include measured solar data, supplied by the following agencies: Atmospheric Radiation Measurement (ARM) Program, DOE; Florida Solar Energy Center, State of Florida; Integrated Surface Irradiance Study (ISIS) and Surface Radiation Budget Measurement (SURFRAD) Networks, NOAA/ARL, NOAA/ESRL/Global Monitoring Division; Measurement and Instrumentation Data Center, NREL; University of Oregon Solar Radiation Monitoring Laboratory Network; and University of Texas Solar Energy Laboratory.

A significant difference between the 1961-1990 and 1991-2005 NSRDBs involves data storage. In the original, measured data were merged with modeled data such that a seamless data set of solar radiation values was produced. (The model essentially filled gaps in the measured data.) The update includes fields for both, which allows users the flexibility to choose modeled or, if available, measured data for an application.

Average of the hourly Global Horizontal Irradiance (GHI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE"). The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.

Abstract: Monthly and annual average solar resource potential for Hawaii.

Purpose: Provide information on the solar resource potential for Hawaii. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented due south at an angle from horizontal equal to the latitude of the collector location.

Supplemental Information: This data provides monthly average and annual average daily total solar resource averaged over surface cells of approximatley 40 km by 40 km in size. This data was developed from the Climatological Solar Radiation (CSR) Model. The CSR model was developed by the National Renewable Energy Laboratory for the U.S. Department of Energy. Specific information about this model can be found in Maxwell, George and Wilcox (1998) and George and Maxwell (1999). This model uses information on cloud cover, atmostpheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. The cloud cover data used as input to the CSR model are an 7-year histogram (1985-1991) of monthly average cloud fraction provided for grid cells of approximately 40km x 40km in size. Thus, the spatial resolution of the CSR model output is defined by this database. The data are obtained from the National Climatic Data Center in Ashville, North Carolina, and were developed from the U.S. Air Force Real Time Nephanalysis (RTNEPH) program. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. The procedures for converting the collector at latitude tilt are described in Marion and Wilcox (1994). Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalible at a 40km resolution. As a result, it is believed that the modeled values are accurate to approximately 10% of a true measured value within the grid cell. Due to terrain effects and other micoclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. Units are in watt hours.

Other Citation Details:

George, R, and E. Maxwell, 1999: "High-Resolution Maps of Solar Collector Performance Using A Climatological Solar Radiation Model", Proceedings of the 1999 Annual Conference, American Solar Energy Society, Portland, ME.

Maxwell, E, R. George and S. Wilcox, "A Climatological Solar Radiation Model", Proceedings of the 1998 Annual Conference, American Solar Energy Society, Albuquerque NM.

Marion, William and Stephen Wilcox, 1994: "Solar Radiation Data Manual for Flat-plate and Concentrating Collectors". NREL/TP-463-5607, National Renewable Energy Laboratory, 1617 Cole Boulevard, Golden, CO 80401.

License Info

DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

A machine readable collection of documented solar siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled based on a locality-by-locality review zoning ordinances after completing an initial review of scholarly legal articles. The citations for each ordinance are included in the Solar Ordinances spreadsheet resource below.

NREL has updated a database of publicly available resources related to community solar in the U.S., including journal articles, reports, fact sheets, slides, videos, datasets, webinars, and other formats. This effort aims to compile resources that would benefit all partners interested in investigating the market status, data analysis, regulation, stakeholder engagement, and the best practices of community solar development.

This database represents a list of community solar projects identified through various sources as of Spring 2018. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the souces e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to Eric O'Shaughnessy at eric.oshaughnessy@nrel.gov.

The National Solar Radiation Database (NSRDB) was produced by the National Renewable Energy Laboratory under the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy. The 1991-2010 NSRDB is an update of the 1991-2005 NSRDB released in 2006 and archived at NCDC. The serially complete hourly data provided in the NSRDB update are provided in two output formats: 1) ground-based solar and meteorological dataset, and 2) 10 km gridded output produced by the SUNY model. The 10 km gridded output is from the State University of New York/Albany (SUNY) satellite radiation model developed by Richard Perez and Clean Power Research. Data in the NSRDB are a slightly modified version of the SolarAnywhere dataset distributed by Clear Power Research. The modifications are detailed in the NSRDB User's Manual. The model uses hourly radiance images estimated from Geostationary Operational Environmental Satellite (GOES) imagery, daily snow cover data, and monthly averages of atmospheric water vapor, trace gases, and the amount of aerosols in the atmosphere to calculate the hourly total irradiance (sun and sky) falling on a horizontal surface. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. In simple terms, this satellite model uses the inverse relationship between reflected irradiance (that reflected by clouds and atmosphere back to space and the satellite sensor) and ground irradiance (that transmitted through the atmosphere to the Earth's surface). The high-resolution 10-km gridded data set from the SUNY model provides a consistency in modeled output data for its period of record for the years 1998 to 2009, the period for which necessary GOES imagery was available for the project. The SUNY model produces estimates of global and direct irradiance at hourly intervals on the 10-km grid for 49 states, excluding Alaska, where the geostationary satellites cannot resolve cloud cover with necessary detail. Although GOES images provide up to 1-km resolution, in the SUNY model, these data are down-sampled to 10-km resolution (0.1 degree x 0.1 degree). This resolution is adequate for most solar radiation resource applications and represents a practical trade-off between resolution and processing and data storage considerations. The model uses both GOES-East and GOES-West satellites for complete spatial coverage of the United States.

CDFW BIOS GIS Dataset, Contact: NREL National Renewable Energy Laboratory, Description: Polygon of Solar Radiation Potential created from modeled raster data by the National Renewable Energy Lab (NREL). This data provides monthly average and annual average daily total solar resource averaged over surface cells of 0.1 degrees in both latitude and longitude, or about 10 km in size. This model uses a modified Bird model to calculate clear sky direct normal (DNI). This is then adjusted as a function of the ratio of clear sky global horizontal (GHI) and the model predicted GHI.

Average of the hourly Direct Normal Irradiance (DNI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE"). The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.

Average of the hourly Direct Normal Irradiance (DNI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE"). The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.

Abstract: Monthly and annual average solar resource potential for the lower 48 states of the United States of America.

Purpose: Provide information on the solar resource potential for the United States of America lower 48 states. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented due south at an angle from horizontal equal to the latitude of the collector location.

Supplemental Information: This data provides monthly average and annual average daily total solar resource averaged over surface cells of approximatley 40 km by 40 km in size. This data was developed from the Climatological Solar Radiation (CSR) Model. The CSR model was developed by the National Renewable Energy Laboratory for the U.S. Department of Energy. Specific information about this model can be found in Maxwell, George and Wilcox (1998) and George and Maxwell (1999). This model uses information on cloud cover, atmostpheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. The cloud cover data used as input to the CSR model are an 7-year histogram (1985-1991) of monthly average cloud fraction provided for grid cells of approximately 40km x 40km in size. Thus, the spatial resolution of the CSR model output is defined by this database. The data are obtained from the National Climatic Data Center in Ashville, North Carolina, and were developed from the U.S. Air Force Real Time Nephanalysis (RTNEPH) program. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. The procedures for converting the collector at latitude tilt are described in Marion and Wilcox (1994). Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalible at a 40km resolution. As a result, it is believed that the modeled values are accurate to approximately 10% of a true measured value within the grid cell. Due to terrain effects and other micoclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. Units are in kilowatt hours per meter squared per day.

OtherCitation Details:

George, R, and E. Maxwell, 1999: "High-Resolution Maps of Solar Collector Performance Using A Climatological Solar Radiation Model", Proceedings of the 1999 Annual Conference, American Solar Energy Society, Portland, ME.

Maxwell, E, R. George and S. Wilcox, "A Climatological Solar Radiation Model", Proceedings of the 1998 Annual Conference, American Solar Energy Society, Albuquerque NM.

Marion, William and Stephen Wilcox, 1994: "Solar Radiation Data Manual for Flat-plate and Concentrating Collectors". NREL/TP-463-5607, National Renewable Energy Laboratory, 1617 Cole Boulevard, Golden, CO 80401.

License Info

DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation- global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI)- as well as other meteorological data. The goal of the NCDB is to provide unbiased high temporal and spatial resolution climate data needed for renewable energy modeling. The NCDB is modeled using a statistical downscaling approach with Regional Climate Model (RCM)-based climate projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX; linked below). Daily climate projections simulated by the Canadian Regional Climate Model 4 (CanRCM4) forced by the second-generation Canadian Earth System Model (CanESM2) for two Representative Concentration Pathways (RCP4.5 or moderate emissions scenario and RCP8.5 or highest baseline emission scenario) are selected as inputs to the statistical downscaling models. The National Solar Radiation Database (NSRDB) is used to build and calibrate statistical models.

The purpose of this dataset is to summarize current community solar policies and low-income stipulations by state in the United States. The dataset is updated multiple times per year. The current version is the first file located below. Previous versions of the dataset published before August of 2024 can be found in the dataset below labeled “ARCHIVE_State Policies and Programs for Community Solar_Before 08.24.“ This list has been reviewed, but errors may exist, and the list may not be comprehensive. NREL invites input to update or add to the database. Please submit updates, additions, and corrections to Kaifeng Xu (kaifeng.xu@nrel.gov) & Simon Sandler (simon.sandler@nrel.gov).

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of Dec 2023. In addition, this dataset updated the low-income (LI) and low- and moderate-income (LMI) provisions for both complete and pending projects, based on the most recent program data we collected as of March 2024. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

GIS data for Bhutan's direct normal irradiance (DNI), global horizontal irradiance (GHI), and latitude tilt irradiance. Researchers from NREL and the Atmospheric Sciences Research Center (ASRC) at the State University of New York (SUNY) at Albany developed the estimates of Bhutans solar resource. SUNY researchers generated the estimates of GHI and DNI using images collected at hourly intervals between December 2002 and January 2007 from the European Meteosat 5 and 7 geostationary satellites. NREL used the GHI data to generate estimates of the resource potential at latitude tilt, and to create the solar resource maps. This submission includes GIS resources of the results for this study. This data can be used to help with energy production and infrastructure planning in Bhutan.