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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Physics-guided machine learning for improved accuracy of the National Solar Radiation Database

The National Solar Radiation Database (NSRDB) provides high-resolution spatiotemporal solar irradiance data for the entire globe. The NSRDB uses a two-step Physical Solar Model (PSM) to compute the effects of clouds and other atmospheric variables on the solar radiation reaching the surface of the Earth. Physical and optical cloud properties are fundamental inputs to the PSM and are derived from the National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellites. This paper describes recent improvements to the NSRDB driven by physics-guided machine learning methods for cloud property retrieval. The impacts of these new methods on the NSRDB irradiance data are validated using an extensive set of ground measurement sites, showing significant improvement for all sites. We report on average, the mean absolute percentage error for global horizontal irradiance and direct normal irradiance show reductions of 2.16 and 3.95 percentage points respectively for all daylight conditions, 5.92 and 17.39 percentage points respectively for cloudy conditions, and 9.00 and 22.59 percentage points respectively for gap-filled cloudy conditions. These new methods will help improve the quality and accuracy of the irradiance and cloud data in the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2021

Evaluation of clear-sky and satellite-derived irradiance data for determining the degradation of photovoltaic system performance

Knowing the degradation in performance of a photovoltaic (PV) system over time is important for estimating the lifetime energy produced and the financial return. A key parameter for normalizing performance and determining degradation is the plane-of-array (POA) irradiance. Because accurate long-term POA measurements are not always readily available, three methods of providing irradiance data for determining the degradation rate of PV systems were evaluated—a method using irradiance data modeled with the Ineichen clear-sky model and monthly Linke turbidity coefficients, a method using the supplemental clear-sky irradiance data from the National Solar Radiation Data Base (NSRDB), and a method using the NSRDB solar irradiance data for both cloudy and clear-sky conditions (all-sky). The irradiance data from the three methods were evaluated using measured irradiance data from 1998 through 2018 for the seven-station SURFRAD network and for 3-, 5-, and 10-year periods that might be used for evaluating PV system performance. Only the two clear-sky methods for the 10-year periods had less uncertainty with respect to determining PV system degradation than the expected median degradation rate for PV systems of -0.5%/year to -0.6%/year. Shorter periods and the all-sky method had larger uncertainties, making their use questionable for determining the degradation rates of PV systems.

14 SOLAR ENERGY↗
DOE OSTI2025

Spatiotemporal Downscaling Model for Solar Irradiance Forecast Using Nearest-Neighbor Random Forest and Gaussian Process

Accurate solar photovoltaic (PV) capacity estimation requires high-resolution, site-specific solar irradiance data to account for localized variability. However, global datasets, such as the National Solar Radiation Database (NSRDB), provide regional averages that fail to capture the fine-scale fluctuations critical for large-scale grid integration. This limitation is particularly relevant in the context of increasing distributed energy resources (DERs) penetration, such as rooftop PV. Additionally, it is critical to the implementation of the U.S. Federal Energy Regulatory Commission (FERC) Order 2222, which facilitates DER participation in U.S. bulk power markets. To address this challenge, this study evaluates Nearest-Neighbor Random Forest (NNRF) and Nearest-Neighbor Gaussian Process (NNGP) models for spatiotemporal downscaling of global solar irradiance data. By leveraging historical irradiance and meteorological data, these models incorporate spatial, temporal, and feature-based correlations to enhance local irradiance predictions. The NNRF model, a machine-learning approach, prioritizes computational efficiency and predictive accuracy, while the NNGP model offers a level of interpretability and prediction uncertainty by numerically quantifying correlations and dependencies in the data. Model validation was conducted using day-ahead predictions. The results showed that the average Goodness of Fit (GoF) of the NNRF model of 90.61% across all eight sites outperformed the GoF of the NNGP of 85.88%. Additionally, the computational speed of NNRF was 2.5 times faster than the NNGP. Finally, the NNGP displayed polynomial scaling while the NNRF scaled linearly with increasing number of nearest neighbors. Additional validation of the model on five sites in Puerto Rico further confirmed the superiority of the NNRF model over the NNGP model. These findings highlight the robustness and computational efficiency of NNRF for large-scale solar irradiance downscaling, making it a strong candidate for improving PV capacity estimation and real-time electricity market integration for DERs.

Asiedu, Shadrack (ORCID:0009000646004826)↗
NASA NTRS1987

Thematic Mapper bandpass solar exoatmospheric irradiances

Based on solar irradiance data published by Neckel and Labs (1984) and Iqbal (1983), the solar exoatmospheric irradiances for Thematic Mapper (TM) bands 1, 2, 3, and 4 have been calculated. Results vary by up to 1 percent from previous published values, which were based on the earlier data of Neckel and Labs. For TM bands 5 and 7, integrated solar exoatmospheric irradiances have also been recalculated using solar irradiance data published by Labs and Neckel (1968), Arvesen et al. (1969), and Iqbal (1983). These irradiances vary by up to 6 percent from previously published results, which were based on data published by Thekaekara (1972).

Markham, B. L.↗
DOE OSTI2020

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m 2 ), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. Furthermore, the algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

14 SOLAR ENERGY↗
NASA NTRS2002

Comparison of Total Solar Irradiance with NASA/NSO Spectromagnetograph Data in Solar Cycles 22 and 23

An earlier study compared NASA/NSO Spectromagnetograph (SPM) data with spacecraft measurements of total solar irradiance (TSI) variations over a 1.5 year period in the declining phase of solar cycle 22. This paper extends the analysis to an eight-year period which also spans the rising and early maximum phases of cycle 23. The conclusions of the earlier work appear to be robust: three factors (sunspots, strong unipolar regions, and strong mixed polarity regions) describe most of the variation in the SPM record, but only the first two are associated with TSI. Additionally, the residuals of a linear multiple regression of TSI against SPM observations over the entire eight-year period show an unexplained, increasing, linear time variation with a rate of about 0.05 W m(exp -2) per year. Separate regressions for the periods before and after 1996 January 01 show no unexplained trends but differ substantially in regression parameters. This behavior may reflect a solar source of TSI variations beyond sunspots and faculae but more plausibly results from uncompensated non-solar effects in one or both of the TSI and SPM data sets.

Jones, Harrison P.↗
NASA NTRS1994

Changes in photochemically significant solar UV spectral irradiance as estimated by the composite Mg II index and scale factors

Quantitative assessment of the impact of solar ultraviolet irradiance variations on stratospheric ozone abundances currently requires the use of proxy indicators. The Mg II core-to-wing index has been developed as an indicator of solar UV activity between 175-400 nm that is independent of most instrument artifacts, and measures solar variability on both rotational and solar cycle time scales. Linear regression fits have been used to merge the individual Mg II index data sets from the Nimbus-7, NOAA-9, and NOAA-11 instruments onto a single reference scale. The change in 27-dayrunning average of the composite Mg II index from solar maximum to solar minimum is approximately 8 percent for solar cycle 21, and approximately 9 percent for solar cycle 22 through January 1992. Scaling factors based on the short-term variations in the Mg II index and solar irradiance data sets have been developed to estimate solar variability at mid-UV and near-UV wavelengths. Near 205 nm, where solar irradiance variations are important for stratospheric photo-chemistry and dynamics, the estimated change in irradiance during solar cycle 22 is approximately 10 percent using the composite Mg II index and scale factors.

Deland, Matthew T.↗
DOE OSTI2024

Simulative Prediction of Solar Illuminance and Application of the Du-Sharples Model in Estimating Adapted Daylighting Metrics for an Urban Environment

The practice of daylighting in indoor spaces can significantly reduce electricity consumption and carbon emissions, improve human productivity, and enhance mood and cognitive perception. This work discussed the recent developments in daylighting science and practice, computed the periodic variations in average diurnal daylight levels for each month, quantified in terms of global horizontal illuminance and diffuse horizontal illuminance, for Kolkata, India, a city with tropical wet and dry climate, with two empirical luminous efficacy models of estimating solar illuminance, and assessed daylighting metrics with the Du-Sharples model. A program was formulated that could compute and generate daylight data with monthly-hourly solar irradiation data and the Du-Sharples model was utilized to predict dirt-corrected daylighting metrics for three glazing transmittance values and five elemental carbon deposition levels on glazing material. The highest monthly average global horizontal illuminance is recorded in April (64.05 klx for Littlefair model and 66.82 klx for Muneer-Kinghorn model) and the highest monthly average diffuse horizontal illuminance is recorded in July (33.23 klx for Littlefair model and 30.63 klx for Muneer-Kinghorn model). Further, the computed yearly average global and diffuse horizontal illuminance levels agree well with a previous study that applied the Perez model. Yearly average horizontal work surface illuminance level remained >1.5 klx for window-towall area ratio >30 %. The approach adopted in this work and the temporal variation charts of computed exterior daylight level data may assist building service engineers, architects, and indoor lighting practitioners in making informed policy decisions at different stages of building planning.

Engineering↗
NASA NTRS1993

Composite Mg II solar activity index for solar cycles 21 and 22

On the basis of version 1.0 of the composite MG II solar activity index data set, it is shown that the change in the 27-day running average of the Mg II index from solar maximum to solar minimum is about 8 percent for solar cycle 21 and about 9 percent for solar cycle 22 through January 1992. Scaling factors based on the short-term variations in the Mg II index and solar irradiance data sets are developed for each instrument to estimate solar variability at mid-UV and near-UV wavelengths. A set of composite scale factors are derived for use with the present composite MG index. Near 205 cm, where solar irradiance variations are important for stratospheric chemistry, the estimated change in irradiance during solar cycle 22 is about 10 +/- 1 percent using the composite Mg II index (version 1.0) and scale factors.

Deland, Matthew T.↗
NASA NTRS1988

Active Cavity Radiometer (ACR)

The objective of the Active Cavity Radiometer (ACR) experiment on the Atmospheric Laboratory for Applications and Science (ATLAS) mission is the measurement of the total solar irradiance with state-of-the-art accuracy and precision. This experiment is part of an ongoing program of space flight observations to study short- and long-term variations in the total solar output of optical energy. Precise observations of solar total irradiance provide information on the solar cycle and other long-term trends in solar output that are of climatological significance as well as short-term solar physics phenomena such as radiation anisotropy, active region structure, missing flux due to sunsports, bolometry of solar flares, global oscillations, coronal holes, and large-scale convective flows. The principal role of the ATLAS ACR observations will be in support of extended solar irradiance experiments on free-flying satellites. Annual in-flight comparison of observations by both ATLAS and free-flying experiments is an important part of sustaining the long-term precision of the climatological solar irradiance data base at the required + or - 0.1 percent level. Another role for ATLAS solar irradiance measurements will be establishment of the radiation scale at the solar total flux level in the International System of Units (SI). Two types of pyrheliometers, the ACR and SOLCON, will be directly intercompared during the ATLAS 1 mission. Addition of other sensors is planned for future reflights. Comparisons of solar observations by different pyrheliometers in the shuttle space environment will provide the most definitive experiment for determining their accuracy in defining the radiation scale at the solar total flux level.

Willson, R. C.↗
NASA NTRS1988

A new method for estimating the turbulent heat flux at the bottom of the daily mixed layer

Temperature data in the mixed layer and net solar irradiance data at the sea surface are used to estimate the vertical turbulent heat flux at the bottom of the daily mixed layer. The method is applied to data obtained in the eastern tropical Pacific, where the daily cycle in the temperature field is confined to the upper 10-25 m. Equatorial turbulence measurements indicate that the turbulent heat flux is much greater during nighttime than daytime.

Imawaki, Shiro↗
DOE OSTI2023

Clear-Sky Probability for the 2023 Annular Solar Eclipse and the 2024 Total Solar Eclipse Using the NREL National Solar Radiation Database

The National Renewable Energy Laboratory (NREL) and collaborators have created a clear-sky probability analysis to help guide viewers to the 2023 annular solar eclipse and the 2024 total solar eclipse. Using cloud and solar data from the NREL National Solar Radiation Database (NSRDB), the analysis provides cloudless-sky probabilities specific to the date, time, and location of each eclipse with a 4-km resolution. Though not intended to be an eclipse weather forecast, the detailed maps can help guide eclipse enthusiasts to likely optimal viewing locations. Additionally, high-resolution data are presented for the centerline of the path of each eclipse, representing the likelihood for cloudless skies and atmospheric clarity. The NSRDB provides industry, academia, and other stakeholders with high-resolution solar irradiance data to support feasibility analyses for photovoltaic and concentrating solar power generation projects.

14 SOLAR ENERGY↗
NASA NTRS1986

The Mg 280-nm doublet as a monitor of changes in solar ultraviolet irradiance

Solar irradiance data gathered with the Nimbus 7 spacecraft from 1978-1985 are compared with atmospheric MG 289-nm doublet emission line data to evaluate the possibility of using the rotational line data to calculate the total solar UV input. The satellite instrumentation is described, including the calibration equipment and procedures. The spacecraft records solar irradiance once per day and the remainder of the time records irradiance scattered by the atmosphere. The measured irradiances are converted to equivalent brightness temperatures, which can be interpolated for specific layers of the atmosphere. Sample daily data are provided to illustrate the correlation between variations in the Mg-II core radiation and the soalr UV irradiance. Techniques are defined for correcting for periodic variations in instrument performance to quantify long-term solar UV radiance variations. Using the atmospheric Mg-II doublet radiation for measuring soalr UV irradiance is concluded of value for characterizing the effects of solar radiation on the atmosphere.

Heath, D. F.↗
NASA NTRS1997

Long-term variations in total solar and UV irradiances

The variations of total solar and UV irradiances during solar cycles 21 and 22 are compared. The total solar irradiance data used were obtained by the SMM/active cavity radiometer irradiance monitoring (ACRIM) 1, upper atmosphere research satellite (UARS)/ACRIM 2 and ERBS experiments. The space-based irradiance observations are compared to the Mount Wilson Magnetic Plage and Photometric Sunspot Index, which is derived from the area and position of sunspots published by the NOAA World Data Center Solar Geophysical Data Catalog. It is found that the variations in solar UV irradiance were similar during the maximum and minimum of solar cycles 21 and 22. The possible reasons for the differences in the irradiance values during the minima of the two solar cylces are discussed.

Pap, J. M.↗
NASA NTRS1984

Status of Solar Measurements and Data Reduction for Erb-nimbus 7

The status of the Total Solar Irradiance data obtained using the cavity radiometer aboard the Earth Radiation Budget experiment of the Nimbus 7 satellite is described. The ERB experiment has a number of sensors which measure the radiative fluxes (both shortwave and infrared) leaving the Earth as well as the solar channels. The complexity of the processing of the Earth-flux data, both wide and narrow angle has necessitated a reprocessing effort which produces the final data. Since the solar data is embedded in the same data stream and tape product as the Earth-flux data, it was not generally available in a format convenient for analysis as a separate product. Values for the final data product only are presented and a few remarks concerning the basic features of the data. There is no scientific conclusions presented here other than those directly related to the measurement results. A set of tabulated values is appended.

Hickey, J. R.↗
DOE OSTI2025

Deliverable 6.7-Final Technical Report: Development Summary and Evaluation of the Solar Uncertainty Integrator (SUNI) Software

The Data Quality and Uncertainty Integration Project was a three-year effort to address stakeholder needs for assessing solar radiation resource data quality based on existing tools for estimating radiometer measurement uncertainties and assessing post-measurement data quality. The annual research objectives for the project addressed a logical progression of effort needed to achieve the ultimate project goal of developing the Solar Uncertainty Integrator (SUNI) software. This final technical report summarizes the development process for achieving these key research objectives and addresses the outreach and code development efforts in the final year of the project to develop a new solar irradiance data uncertainty integration software package.

14 SOLAR ENERGY↗
DOE OSTI2026

Assessing Uncertainty in Solar Measurements: Key Findings From NLR's SUNI Application Across 89 Stations

The Solar Uncertainty Integrator (SUNI) study was developed by the National Laboratory of the Rockies (NLR's) to provide a standardized "bulk uncertainty processing" method for solar irradiance data, which are essential for the successful deployment of solar energy systems. This poster provides an overview of key findings from NLR's SUNI application across 89 stations.

14 SOLAR ENERGY↗