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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Potential Effects of Climate Change and Solar Radiation Modification on Renewable Energy Resources

Solar radiation modification (SRM) is a possible deliberate approach to decrease or reflect incoming solar radiation with the goal of reducing global temperatures, which have increased over the last decades due to high atmospheric greenhouse gas concentrations. Stratospheric aerosol injection, specifically, has shown potential for successfully reducing global temperatures in climate model simulations. Despite the growing literature in the areas of climate change and SRM, their combined effects on renewable energy generation, a climate change mitigation strategy, have not been addressed. In this review paper, we synthesize previous literature on the possible effects of climate change and SRM on renewable energy resources (i.e., wind energy, solar energy, biomass energy, and hydropower), review the status of climate change and SRM research, and explore potential effects of SRM on renewable energy primarily in the Continental United States (CONUS), but with global perspectives as well. We discuss the research challenges and impacts of SRM on renewable energy and conclude by discussing the potential implications of SRM for renewables for SRM governance and policy. This work is not advocating for or against SRM. It is highlighting an important potential impact for future decision makers.

Kumler, Andrew [National Renewable Energy Laborato↗
DOE OSTI2025

Solar Radiation Measurements (CRADA Final Report)

Long-term solar radiation measurements are important for understanding solar resource availability and variability for systems design and deployment of cost-effective solar resource technologies. Additionally high-quality traceable solar measurements are required to validate satellite-based solar resource datasets that provide high-resolution long-term data covering the US. The purpose and intent of this agreement is to collect long-term solar radiation and meteorological measurements from the state-of-the-art facility at the University of Arizona to meet the above needs.

14 SOLAR ENERGY↗
DOE OSTI2024

Bias Correction and Statistical Downscaling of Solar Radiation Using NA-CORDEX and the NSRDB

The current state-of-art for estimating long-term PV production uses long-term estimates of solar radiation variables, such as global horizontal irradiance (GHI), from previous years. This data is used in models such as the System Advisor Model (SAM) or PYSyst to predict annual production for a PV plant. This information is then used to estimate the production over the next 20 years (a typical plant lifetime) under the assumption that the variability over the current period is representative of the future. As the PV industry moves to extend plant lifetimes to 50 years the current assumptions of representativeness of weather may not be appropriate. This is especially true as our climate changes rapidly. To assess long-term PV production, future projections for solar radiation based on projected carbon emissions are readily available in regional and global climate models. However, climate model projections contain inherent biases that may need to be corrected for accurate analysis of future projections of climate variables. Several studies have analyzed projections of solar radiation for future years, however the accuracy of the model output compared to current and historic data has not been widely studied. Chen (2021) showed that available climate models do not accurately represent solar radiation in some cases, over-projecting GHI at the surface while under-projecting its obstructions, such as clouds and aerosols. This works aims to (1) increase understanding of the accuracy of solar radiation currently available in global and regional climate models and (2) implement bias correction through linear models based on reanalysis data compared to observed solar radiation. The latter aim will be conducted using available observed solar radiation data and modeled data from several regional climate models (RCMs). The bias correction method will be applied to projections of solar radiation resulting in a more accurate representation of the future of solar production.

climate data↗
DOE OSTI2026

Solar Radiation Research Laboratory (SRRL) Core Project Final Report: Fiscal Years 2022-2024

The Solar Radiation Research Laboratory (SRRL) at the National Laboratory of the Rockies (NLR) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m2) for the United States that is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two calibration facilities that meet International Standards Organization-17025 (ISO-17025) standards and provide unique high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System (BMS) at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop (1) improved methods for the calibration of solar radiometers; (2) new standards through the ISO, the International Electrotechnical Commission (IEC), and the American Standards for Testing of Materials (ASTM) International; (c) solar radiation and meteorological models; and (d) advanced instrumentation and methods for operating solar measurement stations. The SRRL datasets are also critical for the validation of new models and datasets, such as the National Solar Radiation Database (NSRDB). The research and development of solar radiation measurement systems and resource modeling techniques are essential for advancing the scientific basis for producing reliable resource data. Specifically, the spatial, temporal, and spectral (wavelength dependency) characteristics of the solar resource are required in several different time frames for various project phases.

14 SOLAR ENERGY↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model: Preprint

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

DNI↗
DOE OSTI2024

Standard Operating Procedure for Optimal Deployment of Meteorological Instrumentation Within the Solar Radiation Research Laboratory: 2024 Edition

The objective of the National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) is to collect and use high-quality solar radiation data sets for research leading to the widespread adoption of solar technologies. To appropriately populate and track the diverse array of instruments at the NREL-SRRL, NREL has established a Standard Operating Procedure (SOP) for optimal instrument deployment within the SRRL for both the Baseline Measurement System (BMS) and the Research Measurement System (RMS). Using best practices methodologies, the NREL-SRRL maintains a varied and extensive array of solar monitoring equipment to test, evaluate, and characterize the solar sensors used by federal and international agencies as well as the solar industry to determine the solar resource. The SOP provides the industry with guidance for solar resource assessment and is used for procedures in the long-term continuous monitoring of legacy instruments alongside state-of-the-art instruments. Based on the SOP, instruments are annually evaluated for continued deployment. Instruments that do not meet the SOP criteria are decommissioned, and new instruments that meet the criteria are deployed. Streamlining and optimizing the use of this facility ensures that the lab continues to be a world-leading solar calibration and measurement facility. This 2024 edition includes updates to the appendices to reflect the instrument changes from one year to another.

14 SOLAR ENERGY↗
DOE OSTI2025

Standard Operating Procedure for Optimal Deployment of Meteorological Instrumentation Within the Solar Radiation Research Laboratory: 2025 Edition

The objective of the National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) is to collect and use high-quality solar radiation data sets for research leading to the widespread adoption of solar technologies. To appropriately populate and track the diverse array of instruments at the NREL-SRRL, NREL has established a Standard Operating Procedure (SOP) for optimal instrument deployment within the SRRL for both the Baseline Measurement System (BMS) and the Research Measurement System (RMS). Using best practices methodologies, the NREL-SRRL maintains a varied and extensive array of solar monitoring equipment to test, evaluate, and characterize the solar sensors used by federal and international agencies as well as the solar industry to determine the solar resource. The SOP provides the industry with guidance for solar resource assessment and is used for procedures in the long-term continuous monitoring of legacy instruments alongside state-of-the-art instruments. Based on the SOP, instruments are annually evaluated for continued deployment. Instruments that do not meet the SOP criteria are decommissioned, and new instruments that meet the criteria are deployed. Streamlining and optimizing the use of this facility ensures that the lab continues to be a world-leading solar calibration and measurement facility. This 2025 edition includes updates to the appendices to describe the current instrumentation of the NREL-SRRL.

14 SOLAR ENERGY↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

Xie, Yu↗
DOE OSTI2025

The National Solar Radiation Database Final Report: Fiscal Years 2022-2024

The National Solar Radiation Database (NSRDB) is the leading public source of high-resolution solar resource data in the United States, with more than 400,000 users annually. This database represents the state of the art in the satellite-based estimation of solar resource information and uses a unique physics-based modeling approach that enables improvements in accuracy with the deployment of the next-generation geostationary satellites. Making the highest-quality, state-of-the-art, regularly updated datasets available on a timely basis for users reduces costs of solar deployment by providing accurate information for siting studies and system output prediction and thereby reduces project financing costs and risks.

14 SOLAR ENERGY↗
DOE OSTI2025

Assessing the performance of solar radiation management geoengineering simulations

Offsetting the global warming caused by anthropogenic increases in atmospheric greenhouse gases by deliberate injection of aerosols into the stratosphere is the most studied of solar radiation management geoengineering schemes. The long-term success or failure of such schemes in achieving their stated goals is assessed by comparing simulated geoengineered temperature, precipitation and tropical cyclones metrics to equivalent fields in the simulated targeted climate simulations. Results using available data sets from three single model stabilized climate target experiments and three multimodel climate change reduction experiments are presented and compared against a measure of internal variability. While all but one experimental scheme is successful in achieving their targeted global mean annual surface temperature, their success at regional scales varies significantly and is often larger than the internal variability metric used here.

climate model evaluation↗
DOE OSTI2025

A proposed high-intensity radiometer calibration method using concentrated solar radiation

Accurate calibration of irradiance measurement devices, or radiometers, is essential for ensuring the reliability of measurements in high heat applications such as concentrating solar power (CSP), aerospace, defense, and pulsed power systems. Despite the critical need, existing calibration standards and service providers are limited to irradiance levels below 100 kW/m 2 and specific radiation sources, which is insufficient for many applications. For instance, CSP technologies, particularly those under the Department of Energy’s Solar Energy Technologies Office (SETO) Gen 3 program, require accurate measurements of broadband irradiance at levels exceeding 2000 kW/m 2 . In even more extreme scenarios, such as re-entry vehicles, heat levels can surpass 10000 kW/m 2 . Current ISO standards, specifically ISO 14934–2 and ISO 14934–3, are constrained to lower irradiance levels and dependent on black body heat sources, limiting their applicability for high-intensity broadband irradiance measurements, particularly in concentrated solar applications. Here, to address this shortfall, the National Solar Thermal Test Facility (NSTTF) at Sandia National Laboratories (SNL) proposes a calibration method and facility capable of characterizing radiometers up to 2750 kW/m 2 using concentrated solar irradiance. Calibrating with concentrated sunlight is important for solar applications as it aligns the calibration process with the solar spectrum. This alignment is crucial for minimizing systematic errors and avoiding the need for additional corrections that may arise when radiometers designed for solar applications are calibrated using black-body or electrical sources. This paper presents the present day NSTTF characterization facility and procedure, detailing the proposed calibration method and uncertainty quantification. The presented method builds upon 1980′s NSTTF methodology and involves both theoretical and empirical methods to establish a robust relationship between gauge voltage output and irradiance intensity, quantifying both measurement and fitting errors. By addressing the limitations of existing standards and extending the characterization range, this work provides an advancement in the field of high-intensity irradiance measurement and instrumentation characterization.

Gardon gauge↗
DOE OSTI2025

CROCUS Low Cost All-in-One Weather Station AMB-001 Data Argonne National Laboratory Prairie Site

The Ambient Weather WS-2902D (AMB) is a low cost weather station that has become very useful for filling data gaps in harder to deploy locations. These low cost weather stations collect 13 second data, which is averaged to a five minute data output available to users through an API key. The data files contain measurements for precipitation, temperature, wind chill/heat index, relative humidity, dew point, UV index, solar radiation, wind speed, wind direction, wind gust, and with an external particulate matter 2.5 (PM 2.5) sensor. Having all of these measurements in one condense system allows for fast deploying and dense network capabilities. Three of the AMB weather stations were deployed at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The instruments are denoted by their three digit identifier (CMS-AMB-xxx) format. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (CMS-AMB-001), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or ACT-DOE.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CROCUS Low Cost All-in-One Weather Station AMB-004 Data Argonne National Laboratory Prairie Site

The Ambient Weather WS-2902D (AMB) is a low cost weather station that has become very useful for filling data gaps in harder to deploy locations. These low cost weather stations collect 13 second data, which is averaged to a five minute data output available to users through an Application Programming Interface (API) key. The data files contain measurements for precipitation, temperature, wind chill/heat index, relative humidity, dew point, UV index, solar radiation, wind speed, wind direction, wind gust, and with an external particulate matter 2.5 (PM 2.5) sensor. Having all of these measurements in one condense system allows for fast deploying and dense network capabilities. Three of the AMB weather stations were deployed at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The instruments are denoted by their three digit identifier (CMS-AMB-xxx) format. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (CMS-AMB-004), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or ACT-DOE.

EARTH SCIENCE > ATMOSPHERE > AEROSOLS > PARTICULAT↗
DOE OSTI2024

The influence of cloud cover on the reliability of satellite-based solar resource data

Satellite-based solar resource data are often developed and validated by using binary cloudiness categories: clear sky or overcast cloudy sky. To investigate the reliability of solar resource data in partially cloudy conditions, we estimate cloud fraction using two distinct algorithms: a physical retrieval model using surface observed global horizontal irradiance (GHI) and direct normal irradiance (DNI) and a temporal average of cloud mask data estimated by the observed DNI. Our analysis reveals a significant presence of scattered clouds, broken clouds, and mismatches between satellite- and surface-based cloud data at 17 surface sites across the contiguous United States, though confidently clear and cloudy conditions collectively account for more than 70 % of the data. Solar radiation is computed using the National Solar Radiation Database (NSRDB) algorithm and validated using surface observations. Here, our findings suggest that, in the presence of scattered clouds, NSRDB data for clear-sky conditions can be subject to significant overestimation. In cloudy-sky conditions classified by satellite data, DNI computed by the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) can be underestimated when limited clouds are detected by surface observations. The bias observed in several cloudiness categories indicates that the NSRDB is exceptionally accurate in confidently clear conditions. However, clear-sky conditions with scattered clouds and mismatched cloud data contribute significantly to the overall uncertainties in the NSRDB. Therefore, future improvements in solar resource data should involve development and implementation of satellite-derived cloud fraction and should consider a novel radiative transfer model accounting for amplified cloud reflection. The evaluation within cloudiness categories also provides a physical rationale for the superior performance of FARMS-DNI compared to the Direct Insolation Simulation Code (DISC) in both cloudy-sky and all-sky conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Five Years of Dissolved Oxygen, Temperature, Salinity, Depth, Weather Data from a Transitioning Wetland at Beaver Creek, Washington, USA

Groundwater dissolved oxygen (DO) variability in coastal system remains poorly understood despite its importance for biogeochemical cycling and ecosystem modeling. Here we investigate the temporal variability in groundwater DO and its hydro-climatic drivers across hourly to seasonal timescales in a transitioning wetland at Beaver Creek, Washington, USA. The site is transitioning from a freshwater forest to a brackish tidal wetland following removal of a barrier in 2014 that prevented tides from accessing the freshwater creek. By utilizing novel optical dissolved oxygen instrumentation (Opti O2, LLC) we obtained continuous, high-frequency (5-minute), in-situ measurements of DO from the flood-plain from June 26th, 2019 through September 30th, 2024. This 63 month dataset is comprised of groundwater dissolved oxygen, temperature, water level and salinity timeseries from the floodplain. This dataset also includes rainfall, air pressure, air temperature, and solar radiation data collected with a co-located Campbell ClimaVUE50 weather sensor. All data is contained within a single csv (2019-06-26 to 2024-09-30 Beaver Creek DO, saln, BGS, temp, weather.csv) that can easily be viewed either using software such as Excel or using any text editor.

54 ENVIRONMENTAL SCIENCES↗