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.

Documentation

https://nsrdb.nrel.gov/

Update Frequency

Annually

License

Creative Commons Attribution 3.0 United States License

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 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.

description: These data were originally downloaded from the National Renewable Energy Laboratory (NREL) web site http://www.nrel.gov/gis/data_solar.html in units of kilowatt-hours per square meter per day and were converted to Langleys per day. 1 Langley per day = 1 calorie per square centimeter per day. or 1 Langley per day = 0.01163 kilowatt-hour per square meter per day. NREL has several different values of solar radiation available, the "global horizontal" data is what is represented by this service. "Global horizontal" means on a surface perpendicular to the radius -- i.e. a horizontal plate, wherever on the Earth you are measuring (or using) it. Please note NREL's disclaimer: http://www.nrel.gov/disclaimer.html; abstract: These data were originally downloaded from the National Renewable Energy Laboratory (NREL) web site http://www.nrel.gov/gis/data_solar.html in units of kilowatt-hours per square meter per day and were converted to Langleys per day. 1 Langley per day = 1 calorie per square centimeter per day. or 1 Langley per day = 0.01163 kilowatt-hour per square meter per day. NREL has several different values of solar radiation available, the "global horizontal" data is what is represented by this service. "Global horizontal" means on a surface perpendicular to the radius -- i.e. a horizontal plate, wherever on the Earth you are measuring (or using) it. Please note NREL's disclaimer: http://www.nrel.gov/disclaimer.html

This data provides annual average daily total solar resource averaged over surface cells of 0.038 degrees in both latitude and longitude, or nominally 4 km in size. 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. 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 direct normal irradiance (DNI) and global horizontal irradiance (GHI). The DNI and GHI are computed for clear skies using the REST2 model. For cloud scenes identified by the cloud mask, the FARMS is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data are averaged from hourly model output over 19 years (1998-2016). The PATMOS-X model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, daily snow cover data from the NSIDC and mixing ratio, temperature and pressure profiles from the Modern Era-Retrospective Analysis (MERRA-2) dataset. The REST2 model uses hourly aerosol optical depth from MERRA-2 to calculate GHI and DNI; water vapor and other inputs for REST 2 are obtained from the MERRA-2. This dataset was derived from the NSRDB and may be used with the following citation: Sengupta, M., Xie, Y., Lopez, A., Habte, A., Maclaurin, G., & Shelby, J. (2018). The national solar radiation data base (NSRDB). Renewable and Sustainable Energy Reviews, 89, 51-60.

GIS data for India's direct normal irradiance (DNI) and global horizontal irradiance. Provides 10-kilometer (km) solar resource maps and data for India. The 10-km hourly solar resource data were developed using weather satellite (METEOSAT) measurements incorporated into a site-time specific solar modeling approach developed at the U.S. State University of New York at Albany. The data is made publicly available in geographic information system (GIS) format (shape files etc). The new maps and data were released in June 2013. The new data expands the time period of analysis from 2002-2007 to 2002-2011 and incorporates enhanced aerosols information to improve direct normal irradiance (DNI). These products were developed by the U.S. National Renewable Energy Laboratory (NREL) in cooperation with India's Ministry of New and Renewable Energy, through funding from the U.S. Department of Energy and U.S. Department of State.

This data was collected for Tonita et al., “Vertical bifacial photovoltaic system model validation: study with field data, various orientations, and latitudes,” for validation of optical models for vertically-oriented photovoltaics under high albedo. Ground irradiance data for vertical PV arrays modeling in agrivoltaics is also provided. The dataset is provided for further use or study as open source. For any questions on the dataset, email silvana.ovaitt@nrel.gov.

description: 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.; abstract: 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

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.

This dataset provides estimated hourly dynamic line ratings for ~84,000 transmission lines across the contiguous United States from 2007-2013. The calculation methods are described in the presentation linked below, and the associated open-source Python code repository is linked in the Resources section below. Abbreviations used in filenames and descriptions are: - SLR: static line ratings - ALR: ambient-temperature-adjusted line ratings - NLR: ambient-temperature- and day/night-irradiance-adjusted line ratings - CLR: ambient-temperature- and clear-sky-irradiance-adjusted line ratings - ILR: ambient-temperature- and measured-irradiance-adjusted line ratings - DLR: full dynamic line ratings (including air temperature/pressure, wind speed/direction, and measured irradiance) Transmission lines are referenced by their ID in the Homeland Infrastructure Foundation-Level Data (HIFLD) on Transmission Lines (linked in Resources section). Time indices are in UTC. The data files contain ratios between modeled hourly ratings and modeled static ratings. Columns are indexed by HIFLD ID; rows are indexed by hourly timestamps from 2007-2013 (UTC). A data directory is also included in the Resources section. The SLR files contain modeled static ratings (the denominator of the ratios in the files described above) in amps. As described in the presentation linked in the Resources section below, SLR calculations assume an ambient air temperature of 40 C, air pressure of 101 kPa, wind speed of 2 feet per second (0.61 m/s) perpendicular to the conductor, global horizontal irradiance of 1000 W/m^2, and conductor absorptivity and emissivity of 0.8. Conductor assumptions are Linnet for ~69 kV and below, Condor for ~115 kV, Martin for ~230 kV, and Cardinal for ~345 kV and above. Caveats and Limitations Results are sensitive to the weather data used. Validation studies on the WIND Toolkit and NSRDB are available at: - King, J. et al. "Validation of Power Output for the WIND Toolkit", 2014 (https://www.nrel.gov/docs/fy14osti/61714.pdf) - Draxl, C. et al. "Overview and Meteorological Validation of the Wind Integration National Dataset Toolkit", 2015 (https://www.nrel.gov/docs/fy15osti/61740.pdf) - Sengupta, M. et al. "Validation of the National Solar Radiation Database (NSRDB) (2005-2012)", 2015 (https://www.nrel.gov/docs/fy15osti/64981.pdf) - Habte, A. et al. "Evaluation of the National Solar Radiation Database (NSRDB Version 2): 1998-2015", 2017 (https://www.nrel.gov/docs/fy17osti/67722.pdf) More work is required to determine how well ratings calculated from NSRDB and WIND Toolkit data reflect the actual ratings observed by installed sensors (such as sag or tension monitors). In general, ratings calculated from modeled weather data are not a substitute for direct sensor data. Assuming a single representative conductor type (ACSR of a single diameter) for each voltage level is an important simplification; reported line ratings at a given voltage level can vary widely. HIFLD line routes are primarily based on imagery instead of exact construction data and may have errors. We use historical weather data directly; calculated line ratings are thus more indicative of real-time ratings than forecasted ratings

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.

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 data was developed using the State University of New York/Albany satellite radiation model. This model was developed by Dr. Richard Perez and collaborators at the National Renewable Energy Laboratory and other universities for the U.S. Department of Energy. Specific information about this model can be found in Perez, et al. (2002). This model uses hourly radiance images from geostationary weather satellites, 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 insolation (sun and sky) falling on a horizontal surface. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. A modified Bird model is used 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. 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 avalable at a 10km resolution. As a result, it is believed that the modeled values are accurate to approximately 15% of a true measured value within the grid cell. Due to terrain effects and other microclimate 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.

A partnership with the University of Nevada and U.S. Department of Energy's National Renewable Energy Laboratory (NREL) to collect solar data to support future solar power generation in the United States. The measurement station monitors global horizontal, direct normal, and diffuse horizontal irradiance to define the amount of solar energy that hits this particular location. The solar measurement instrumentation is also accompanied by meteorological monitoring equipment to provide scientists with a complete picture of the solar power possibilities.

The CloudCV 10-Second Sky Image and Irradiance Dataset contains sky images and irradiance measurements recorded every 10 seconds during daylight hours for 90 days between September 5th to December 3rd, 2019. The dataset was collected at the National Renewable Energy Laboratory (NREL) Solar Radiation Research Laboratory (SRRL) mesa-top campus in Golden, Colorado, USA. The instruments used include an ELP 180 degree Fisheye Lens Wide Angle USB Camera webcam and a co-located LICOR LI200 pyranometer. Historical datasets containing other measurements from co-located instruments with overlapping time period may be available from the NREL Baseline Measurement System. The purpose of collecting this dataset was to train very short term solar irradiance forecasting models from sequential image data of cloud cover. A more detailed description of the CloudCV sky imager and some preliminary analysis conducted with the dataset can be found in NREL Technical Report NREL/TP-2C00-77999 The code repository contains the sky imager's firmware, as well as analysis code and Jupyter notebooks used to perform a preliminary analysis of the short term cloud cover prediction using a linear advection method based on optical flow. The repository is available on Github under NREL Software Record SWR-24-119.

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 for the lower 48 states of the United States of America.

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.

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.

License Info

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.

Seventeen measurement stations in the south western region of the island of Oahu collected data at 1-second intervals over the course of a year. The sensors are located in a 1-kilometer grid and the information then can be used to predict what PV outputs might be at 1-second intervals for medium-sized and large PV systems. This DOE-funded study by NREL supports the Hawaii Clean Energy Initiative (HCEI), a multifaceted program to substantially increase the use of renewable energy in Hawaii.

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.

Average daily total solar global horizontal irradiance average from 1998 to 2014 from the National Renewable Energy Laboratory (NREL).

A partnership with the University of Nevada and U.S. Department of Energy's National Renewable Energy Laboratory (NREL) to collect solar data to support future solar power generation in the United States. The measurement station monitors global horizontal, direct normal, and diffuse horizontal irradiance to define the amount of solar energy that hits this particular location. The solar measurement instrumentation is also accompanied by meteorological monitoring equipment to provide scientists with a complete picture of the solar power possibilities.

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.