Search NASA⌕ Search

SEARCH · Search NASA

Results for “Meteorologic data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

An interactive Barnes objective map analysis scheme for use with satellite and conventional data

The Barnes (1973) objective map analysis scheme is employed to develop an interactive analysis package for assessing the impact of satellite-derived data on analyses of conventional meteorological data sets. The method permits modification of the values of input parameters in the objective analysis within objectively determined, internally set limits. The effects of the manipulations are rapidly displayed, and methods are included for assimilating the spatially clustered characteristics of satellite data and the various horizontal resolutions of the data types. Data sets from the SESAME rawinsonde wind data with uniform spatial distribution, with the same data set plus satellite cloud motion data, and a data set from the atmospheric sounder radiometer on the GOES satellite were analyzed as examples. The scheme is demonstrated to recover details after two iterations through the data.

Koch, S. E.↗
NASA NTRS1990

Lidar observations of ozone changes induced by subpolar air mass motion over Table Mountain, California (34.4 deg N)

Between October 15 and November 8, 1988, the Goddard Space Flight Center mobile stratospheric lidar was in place at the (JPL) Table Mountain Facility (located at 34.4 deg N, 117.7 deg W) for the purpose of intercomparing with the JPL lidar permanently stationed at the observatory. During the course of the intercomparison both lidar systems detected a significant change in the vertical profile of ozone lasting for several days. An analysis of meteorological data available from the National Meteorological Center has shown this change to be dynamical in origin due to the transport of subpolar air over Table Mountain.

Mcgee, Thomas J.↗
DOE OSTI2025

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

RivGen Acoustic Measurements, Igiugig, AK

Drifting hydrophone measurements obtained around the Ocean Renewable Power Company RivGen turbine near the village of Igiugig, Alaska in August, 2014. Each data set contains hydrophone voltage (as well as gain and sensitivity), position on the river (LAT, LONG, and proximity to turbine [xt, yt]), drift velocity, and contextual meteorological data.

16 TIDAL AND WAVE POWER↗
NASA NTRS2011

Rapid Transpacific Transport in Autumn Observed by the A-Train Satellites

Transpacific transport of dust and pollutants is well documented for spring, but less so for other seasons. Here we investigate rapid transpacific transport in autumn utilizing the A-train satellites. In three episodes studied as examples, SO2 plumes over East Asia were detected by the Ozone Monitoring Instrument aboard the Aura satellite, and found to reach North America in 5-6 days. They were likely derived from anthropogenic sources, given that identical transport patterns of CO, a tracer for incomplete combustion, were simultaneously observed by the Aqua satellite. Trajectory analysis and meteorological data were employed to explore the meteorological circumstances surrounding these events: like many of their counterparts in spring, all three plumes were lifted to the free troposphere in warm conveyor belt associated with mid-latitude wave cyclones, and their migration to downwind region was regulated by the meteorology over the East Pacific. These cases provide further evidence that a fraction of S02 could escape wet scavenging, and be transported at much greater efficiency than NOx (NO + N02). An analysis of the S02 and CO data from September to November during 2005-2008 found 16 S02 long-range transport episodes, out of 62 Asian outflow events. While the counts are sensitive to the choice of criteria, they suggest that the long-range transport of Asian sulfur species occurs quite frequently, and could exert strong impacts on large downstream areas. This study also highlights the importance of transpacific transport in autumn, which has thus far been rarely studied and deserves more attention from the community.

Li. Can↗
NASA NTRS1994

SeaWiFS technical report series. Volume 19: Case studies for SeaWiFS calibration and validation, part 2

This document provides brief reports, or case studies, on a number of investigations and data set development activities sponsored by the Calibration and Validation Team (CVT) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. Chapter 1 is a comparison with the atmospheric correction of Coastal Zone Color Scanner (CZCS) data using two independent radiative transfer formulations. Chapter 2 is a study on lunar reflectance at the SeaWiFS wavelengths which was useful in establishing the SeaWiFS lunar gain. Chapter 3 reports the results of the first ground-based solar calibration of the SeaWiFS instrument. The experiment was repeated in the fall of 1993 after the instrument was modified to reduce stray light; the results from the second experiment will be provided in the next case studies volume. Chapter 4 is a laboratory experiment using trap detectors which may be useful tools in the calibration round-robin program. Chapter 5 is the original data format evaluation study conducted in 1992 which outlines the technical criteria used in considering three candidate formats, the hierarchical data format (HDF), the common data format (CDF), and the network CDF (netCDF). Chapter 6 summarizes the meteorological data sets accumulated during the first three years of CZCS operation which are being used for initial testing of the operational SeaWiFS algorithms and systems and would be used during a second global processing of the CZCS data set. Chapter 7 describes how near-real time surface meteorological and total ozone data required for the atmospheric correction algorithm will be retrieved and processed. Finally, Chapter 8 is a comparison of surface wind products from various operational meteorological centers and field observations. Surface winds are used in the atmospheric correction scheme to estimate glint and foam radiances.

Hooker, Stanford B.↗
NASA NTRS1985

Contribution of stratospheric winds to annual and semiannual fluctuations in atmospheric angular momentum and the length of day

It is pointed out that modern data sets pertaining to the motions of the solid earth and the atmosphere have begun to achieve an accuracy sufficient to justify renewed interest in the classic problem of explaining variations in the rotation rate of the earth. The possibility exists that deficiencies in the current meteorological data sets account for most of the discrepancies in the annual and semiannual earth-atmosphere momentum budgets. On the basis of composite stratospheric wind analyses produced by Belmont et al. (1974), it has been demonstrated that the seasonal components of the stratosphere's momentum could contribute significantly to a reduction of the seasonal discrepancies thought to exist in the earth-atmosphere momentum budget. The present investigation is further concerned with this subject. A newly available stratospheric wind data set is utilized in conjunction with concurrent U.S. National Meteorological Center data and data of the European Centre for Medium Range Weather Forecasts.

Rosen, R. D.↗
DOE OSTI2017

Surface Meteorology at Teller Site Stations, Seward Peninsula, Alaska, Ongoing from 2016

Meteorological data are currently being collected at two locations at the Teller Site, Seward Peninsula. This December 6, 2017 release includes data for: Teller Creek Station near TL_BSV (TELLER BOTTOM METEOROLOGICAL STATION) Station is located in the lower watershed in a tussock / willow transition zone and co-located with continuous snow depth measurements and subsurface measurements. Teller Creek Station near TL_IS_5 (TELLER TOP METEOROLOGICAL STATION) Station is located in the upper watershed and co-located with continuous snow depth measurements and subsurface measurements. Two types of data products are provided for these stations: First, meteorological and site characterization data grouped by sensor/measurement type (e.g., radiation or soil pit temperature and moisture). These are *.csv files. Second, a Data Visualization tool is provided for quick visualization of measurements over time at a station. Download the *_Visualizer.zip file, extract, and click on the 'index.html' file. Data values are the same in both products. Dataset DOI: 10.5440/1437633; https://doi.org/10.5440/1437633

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Prediction of Climate-Specific Degradation Rate for Photovoltaic Encapsulant Discoloration

Encapsulant discoloration is a well-known field degradation mode of crystalline-silicon photovoltaic modules, particularly in the hot climate zones. The discoloration rate is influenced by several weathering factors, such as UV light, module temperature, and humidity, as well as the permeability of oxygen into the module. Here, a rate dependence model employing the modified Arrhenius equations to predict the degradation rate for encapsulant discoloration in different climates is presented. Two modeling approaches are introduced, which utilize the field and accelerated UV testing degradation data in conjunction with the field meteorological data to determine the acceleration factor for encapsulant browning. A novel method of accelerated UV stress testing at three simultaneous module temperatures in a single environmental chamber test run is implemented to estimate the activation energy for browning. The test was performed on three field-retrieved modules to capture the wear-out failure mechanism. The degradation in short-circuit current Isc rather than maximum power is used as a decisive parameter for the discoloration analysis. Furthermore, the developed model has been used to predict the Isc degradation rate for the Arizona field characterized by a hot and dry climate and is validated against the field-measured value. It has also been applied to other climate types, e.g., the cold and dry climate of New York.

14 SOLAR ENERGY↗
DOE OSTI2014

Validation of Power Output for the WIND Toolkit

Renewable energy integration studies require wind data sets of high quality with realistic representations of the variability, ramping characteristics, and forecast performance for current wind power plants. The Wind Integration National Data Set (WIND) Toolkit is meant to be an update for and expansion of the original data sets created for the weather years from 2004 through 2006 during the Western Wind and Solar Integration Study and the Eastern Wind Integration Study. The WIND Toolkit expands these data sets to include the entire continental United States, increasing the total number of sites represented, and it includes the weather years from 2007 through 2012. In addition, the WIND Toolkit has a finer resolution for both the temporal and geographic dimensions. Three separate data sets will be created: a meteorological data set, a wind power data set, and a forecast data set. This report describes the validation of the wind power data set.

17 WIND 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)↗
DOE OSTI2016

Observed correlations between aerosol and cloud properties in an Indian Ocean trade cumulus regime

There are many contributing factors which determine the micro- and macrophysical properties of clouds, including atmospheric vertical structure, dominant meteorological conditions, and aerosol concentration, all of which may be coupled to one another. In the quest to determine aerosol effects on clouds, these potential relationships must be understood. Here we describe several observed correlations between aerosol conditions and cloud and atmospheric properties in the Indian Ocean winter monsoon season. In the CARDEX (Cloud, Aerosol, Radiative forcing, Dynamics EXperiment) field campaign conducted in February and March 2012 in the northern Indian Ocean, continuous measurements were made of atmospheric precipitable water vapor (PWV) and the liquid water path (LWP) of trade cumulus clouds, concurrent with measurements of water vapor flux, cloud and aerosol vertical profiles, meteorological data, and surface and total-column aerosol from instrumentation at a ground observatory and on small unmanned aircraft. We present observations which indicate a positive correlation between aerosol and cloud LWP only when considering cases with low atmospheric water vapor (PWV < 40 kg m –2 ), a criterion which acts to filter the data to control for the natural meteorological variability in the region. We then use the aircraft and ground-based measurements to explore possible mechanisms behind this observed aerosol–LWP correlation. The increase in cloud liquid water is found to coincide with a lowering of the cloud base, which is itself attributable to increased boundary layer humidity in polluted conditions. High pollution is found to correlate with both higher temperatures and higher humidity measured throughout the boundary layer. A large-scale analysis, using satellite observations and meteorological reanalysis, corroborates these covariations: high-pollution cases are shown to originate as a highly polluted boundary layer air mass approaching the observatory from a northwesterly direction. The source air mass exhibits both higher temperatures and higher humidity in the polluted cases. While the warmer temperatures may be attributable to aerosol absorption of solar radiation over the subcontinent, the factors responsible for the coincident high humidity are less evident: the high-aerosol conditions are observed to disperse with air mass evolution, along with a weakening of the high-temperature anomaly, while the high-humidity condition is observed to strengthen in magnitude as the polluted air mass moves over the ocean toward the site of the CARDEX observations. In conclusion, potential causal mechanisms of the observed correlations, including meteorological or aerosol-induced factors, are explored, though future research will be needed for a more complete and quantitative understanding of the aerosol–humidity relationship.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

sdt (Solar Data Tools) [SWR-25-130]

Solar Data Tools (sdt) is an open-source Python library for analyzing PV power (and irradiance) time-series data. It was developed to enable analysis of unlabeled PV data, i.e. with no model, no meteorological data, and no performance index required, by taking a statistical signal processing approach in the algorithms used in the package’s main data processing pipeline. Solar Data Tools empowers PV system fleet owners or operators to analyze system performance a hundred times faster even when they only have access to the most basic data stream—power output of the system.

Meyers-Im, Bennet [National Laboratory of the Rock↗
NASA NTRS1972

Meteorological measurements from satellite platforms

Quantitative exploitation of meteorological data from geosynchronous satellites is starting to move from the laboratory to operational practice. Investigations of the data applications portion of the total meteorological satellite system include: (1) tropospheric wind shear and the related severe storm circulations; (2) kinematic properties of the tropical atmosphere as derived from cloud motion vectors; (3) application of a geostationary satellite rake system to measurements of rainfall; and (4) pointing error analysis of geosynchronous satellites.

Suomi, V. E.↗