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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Water loss through evapotranspiration after precipitation events in bioenergy crops grown in similar climatic conditions

The relationship between precipitation and evapotranspiration (ET) is critical to understanding water cycle related dynamics in ecosystems, including crops. Existing studies of bioenergy crops have primarily focused on annual or seasonal ET rates, with less attention given to the immediate ET response following precipitation events. This study examines the variation in ET rates in the days subsequent to precipitation events across various bioenergy crops—corn, switchgrass, and prairies—utilizing 13 years (2010–2022) of growing season data. Meteorological and eddy covariance flux data were collected from seven eddy covariance flux towers as part of the GLBRC scale-up experiment at the Kellogg Biological Station Long Term Ecological Research sites. The analysis revealed that average ET peaked the day after precipitation and declined linearly over the following days, with a statistically significant relationship (p-value = 0.00027, R2 = 0.96). Neither the type of biofuel vegetation nor the historical land use significantly influenced ET post-precipitation events (p-values = 0.53 and 0.153, respectively). Key predictors of ET following precipitation events include shortwave radiation, season, day of the year, ambient temperature, vapor pressure deficit (VPD), long-wave radiation, precipitation amount, soil moisture, and annual variability. These findings enhance our comprehension of ET responses in bioenergy crop systems, with implications for water management in sustainable agriculture.

09 BIOMASS FUELS↗
NASA NTRS1974

Acoustic sounding in the planetary boundary layer

Three case studies are presented involving data from an acoustic radar. The first two cases examine data collected during the passage of a mesoscale cold-air intrusion, probably thunderstorm outflow, and a synoptic-scale cold front. In these studies the radar data are compared to conventional meteorological data obtained from the WKY tower facility for the purpose of radar data interpretation. It is shown that the acoustic radar echoes reveal the boundary between warm and cold air and other areas of turbulent mixing, regions of strong vertical temperature gradients, and areas of weak or no wind shear. The third case study examines the relationship between the nocturnal radiation inversion and the low-level wind maximum or jet in the light of conclusions presented by Blackadar (1957). The low-level jet is seen forming well above the top of the inversion. Sudden rapid growth of the inversion occurs which brings the top of the inversion to a height equal that of the jet. Coincident with the rapid growth of the inversion is a sudden decrease in the intensity of the acoustic radar echoes in the inversion layer. It is suggested that the decrease in echo intensity reveals a decrease in turbulent mixing in the inversion layer as predicted by Blackadar. It is concluded that the acoustic radar can be a valuable tool for study in the lower atmosphere.

Kelly, E. H.↗
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↗
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 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 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.↗
NASA NTRS1976

EarthSat spring wheat yield system test 1975, appendix 4

A computer system is presented which processes meteorological data from both ground observations and meteorologic satellites to define plant weather aspects on a four time per day basis. Plant growth stages are calculated and soil moisture profiles are defined by the system. The EarthSat system assesses plant stress and prepares forecasts of end-of-year yields. The system was used to forecast spring wheat yields in the upper Great Plains states. Hardware and software documentation is provided.

Source record↗
NASA NTRS1979

LACIE sampling design

The sampling design in LACIE consisted of two major components, one for wheat acreage estimation and one for wheat yield prediction. The acreage design was basically a classical survey for which the sampling unit was a 5- by 6-nautical mile segment; however, there were complications caused by measurement errors and loss of data. Yield was predicted by sampling meteorological data from weather stations within a region and then using those data as input to previously fitted regression equations. Wheat production was not estimated directly, but was computed by multiplying yield and acreage estimates. The allocation of samples to countries is discussed as well as the allocation and selection of segments in strata/substrata.

Feiveson, A. H.↗