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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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Development of a Global Solar Activity Data Portal
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Enabling Solar Variability Studies Through Global Solar Activity Data Portal
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Global Solar Activity Data Portal for Long-Term Forecasting
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Using solar wind data to predict daily GPS scintillation occurrence in the African and Asian low‐latitude regions
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The influence of cloud cover on the reliability of satellite-based solar resource data
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Survey of Time Shift Detection Algorithms for Measured PV Data
In this research, three variations of time shift detection algorithms were tested for their ability to detect time shift issues (including daylight savings time and random time shifts) in measured PV data sets. Two algorithms from the Python PVAnalytics package were assessed, and one algorithm from the Solar-Data-Tools package was assessed. Each algorithm's ability to accurately detect and measure time shifts was assessed.
Exploring solar neutrino oscillation parameters with the liquid scintillator counter at Yemilab with a comparison to JUNO
We investigate the sensitivities of the liquid scintillator counter (LSC) at Yemilab and JUNO to solar neutrino oscillation parameters, focusing on θ 12 and Δ m 21 2 . We compare the potential of JUNO with LSC at Yemilab utilizing both reactor and solar data in determining those parameters. We find that the solar neutrino data of LSC at Yemilab is highly sensitive to θ 12 enabling its determination with a higher precision compared to reactor experiments. Our study also reveals that if Δ m 21 2 is larger, with a value close to the best-fit value of KamLAND, JUNO reactor data will have about two times better precision than the reactor LSC at Yemilab. On the other hand, if Δ m 21 2 is smaller and closer to the best-fit value of solar neutrino experiments, the precision of the reactor LSC at Yemilab will be better than JUNO. Published by the American Physical Society 2024
Analysis of regression methods for solar activity forecasting
The paper deals with the potential use of the most recent solar data to project trends in the next few years. Assuming that a mode of solar influence on weather can be identified, advantageous use of that knowledge presumably depends on estimating future solar activity. A frequently used technique for solar cycle predictions is a linear regression procedure along the lines formulated by McNish and Lincoln (1949). The paper presents a sensitivity analysis of the behavior of such regression methods relative to the following aspects: cycle minimum, time into cycle, composition of historical data base, and unnormalized vs. normalized solar cycle data. Comparative solar cycle forecasts for several past cycles are presented as to these aspects of the input data. Implications for the current cycle, No. 21, are also given.
DASL-Data and Activities for Solar Learning
DASL-Data and Activities for Solar Learning Data and Activities for Solar Learning (DASL) provides a classroom learning environment based on a twenty-five year record of solar magnetograms from the National Solar Observatory (NSO) at Kitt Peak, AZ. The data, together with image processing software for Macs or PCs, can be used to learn basic facts about the Sun and astronomy at the middle school level. At the high school level, students can study properties of the Sun's magnetic cycle with classroom exercises emphasizing data and error analysis and can participate in a new scientific study, Research in Active Solar Longitudes (RASL), in collaboration with classrooms throughout the country and scientists at NSO and NASA. We present a half-day course to train teachers in the scientific content of the project and its classroom use. We will provide a compact disc with the data and software and will demonstrate software installation and use, classroom exercises, and participation in RASL with computer projection.
Observed variability of the solar luminosity
Data on solar luminosity variations are compiled in graphs and analyzed, with a focus on the SMM satellite bolometric measurements and other observations made since 1983. Consideration is given to total irradiance measurements in integrated light; emission-line variability in the visible, UV, and IR; mechanisms contributing to the solar variability (sunspots, faculae, rotation, oscillations, granulation, and active networks); the role of the solar magnetic cycle; and other observable parameters indicating variability. Also discussed are the effects of solar variations on the earth climate and the implications of the observations for theoretical models of convective-envelope processes (thermal diffusion near the surface and magnetic pressure in the interior).
The Yohkoh mission for high-energy solar physics
Data on solar flare mechanisms and the sun's corona will be generated by Japan's Yohkoh satellite's X-ray imaging sensors and X-ray and gamma-ray spectrometers. It is noted that the X-ray corona above active regions expands, in some cases almost continually, in contradiction of the widely accepted model of magnetohydrostatic equilibrium in such regions. Flaring X-ray bright points have been discovered to often involve ejecta into an adjacent, much larger and fainter magnetic loop, which brightens along its length at speeds up to 1000 km/sec.
Integrated dynamic analysis simulation of space stations with controllable solar arrays (supplemental data and analyses)
Space station and solar array data and the analyses which were performed in support of the integrated dynamic analysis study. The analysis methods and the formulated digital simulation were developed. Control systems for space station altitude control and solar array orientation control include generic type control systems. These systems have been digitally coded and included in the simulation.
A model of the brightness of moonlight
In this paper, measurements of the sky brightness from the 2800-m level of Mauna Kea are reported. In addition, a model is presented for predicting the moonlight as a function of the moon's phase, the zenith distance of the moon, the zenith distance of the sky position, the angular separation of the moon and sky position, and the local extinction coefficient. The model equations can be quickly calculated on a pocket calculator. A comparison of the model with lunar data and with some Russian solar data shows the accuracy of the predictions to range from 8 percent to 23 percent.
Development of a 95-Year Solar Dataset for Resource Adequacy Studies
Long-term high-resolution solar data provides enhanced understanding of variability of solar generation and enhances our ability to develop strategies for a resilient and reliable electric grid under high deployment of solar energy. Therefore, it is important to develop long-term synthetic datasets that can provide multiple occurrences of various severe weather scenarios that are expected to test the limits of resource adequacy under scenarios contain various energy generation sources. Examples of such scenarios could be long periods of high temperatures when demand for electricity is high or periods where high winds could lead to a shut-down of transmission lines for long periods of time to ensure fire safety. NREL has developed the first version of such a dataset covering a 95-year period covering 2006-2100 at a 4km hourly resolution. This dataset contains all variables necessary to calculate solar generation. During development of this dataset, we focused on creating unbiased, high-resolution solar irradiance through statistical downscaling methods, using Regional Climate Model (RCM) simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) as input. The National Solar Radiation Database (NSRDB) containing over 25 years of observations was used to calibrate the statistical downscaling models. This presentation will outline the primary steps in developing this dataset, including (1) regridding RCM data to a common grid at 20-km resolution, (2) correcting RCM biases with NSRDB, (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar and ancillary data. Additionally, we will present an evaluation of the downscaled data against the NSRDB across various zones in the CONUS. Lastly, we will present a user guide for accessing the datasets.
Using Time Series Data Products to Support ASHRAE’s Historic and Future Climate Data Needs through NASA’s POWER Web Services
To address the data needs for resilience and sustainability of building systems within ASHRAE, the NASA Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data on a long-term, global scale. Solar data from several NASA projects and meteorological data from NASA assimilation models have been reformatted and disseminated to the public via a user friendly web GIS-enabled based data portal (https://power.larc.nasa.gov) in selectable data formats, immediately amenable to key industry wide decision support tools such as EnergyPlus. Time series of potential climate conditions from downscaled climate simulations are being made available for similar statistics and formats. An emphasis is placed upon obtaining and utilizing time series data to conduct analysis of building system performance for current and planning building systems for energy savings and greenhouse gas emissions. This presentation has the learning following learning objectives for the ASHRAE community: 1) Learn how NASA POWER’s web service suite can provide supplementary solar and surface meteorological data parameters, including a discussion of uncertainty. 2) Learn how downscaled climate scenario information can be provided to evaluate potential future requirements. The presentation is part of a forum entitled, "Weather Data for Large-Scale Building Energy Modeling".
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.