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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

The connection between forest degradation and urban energy demand in sub-Saharan Africa: a characterization based on high-resolution remote sensing data

Charcoal is a key energy source for urban households in sub-Saharan Africa and charcoal production is the main cause of forest degradation across the region. We used multitemporal high-resolution remote sensing optical imagery to quantify the extent and intensity of forest degradation associated with charcoal production and its impact on forest carbon stocks for the main supplying area of an African capital. This analysis documents the advance of forest degradation and quantifies its aboveground biomass removals over a seven-year period, registering that, between 2013 and 2016, the average annual area under charcoal production was 103 sq.km and the annual aboveground biomass removals reached 1081 000 (SD = 2461) Mg. Kiln densities in the study area rose to 2 kilns-ha, with an average of 90.7 Mg ha^(−1) of extracted aboveground biomass. Charcoal production was responsible for the degradation of 55.5% of the mopane woodlands in the study area between 2013 and 2019. We estimated post-disturbance recovery times using an ecosystem model calibrated for the study area. The simulations showed that recovery times could require up to 150 years for current aboveground biomass extraction rates. The results of the remote sensing analysis and the simulations of the ecosystem model corroborate the unsustainability of the present patterns of charcoal production. The detailed characterization of the spatial and temporal patterns of charcoal production was combined with household survey information to quantify the impact of the urban energy demand of the Maputo urban area on forest carbon stocks. The analysis shows that Maputo charcoal demand was responsible for the annual degradation of up to 175.3 sq.km and that the contribution of the study area to this demand fluctuated between 75% and 33% over the study period. The extent, advance pace and distance from urban centers documented in this study support the idea that forest degradation from charcoal production cannot merely be considered a peri-urban process. The intensity of the aboveground biomass (AGB) removals and its contribution to forest carbon stocks changes is significant at the national and regional levels.

F Sedano↗
NASA NTRS1992

Probing the circumstellar environments of very young low-mass stars using water masers

The VLA is used to search nearby very young low-mass stars for water maser emission. The sample consists of 26 low-luminosity IRAS sources embedded in dense molecular cores, a class of sources suspected to be newly forming low-mass stars on the order of a few hundred thousand years old. Three sources were detected. High spatial resolution maps show the region of maser emission is generally confined to an area smaller than about 0.5 arcsec near the star, and the velocities of individual components span intervals ranging from 20 to 40 km/s. It is inferred from the fact that the maser velocities are too large to be due to gravitational motions in at least two of the sources that the masers are associated with the winds from the young low-mass stars. A comparison of the high spatial resolution maser data to lower-resolution CO data shows no evidence for higher collimation close to the star; the stellar wind cavity appears to have similar collimation at 10 exp 15 cm as at 10 exp 7 to 10 exp 18 cm.

Terebey, S.↗
NASA NTRS1994

Rice cultivation and methane emission: Documentation of distributed geographic data sets

High-resolution global data bases on the geographic and seasonal distribution of rice cultivation and associated methane emission, compiled by Matthews et al., were archived for public use. In addition to the primary data sets identifying location, seasonality, and methane emission from rice cultivation, a series of supporting data sets is included, allowing users not only to replicate the work of Matthews et al. but to investigate alternative cultivation and emission scenarios. The suite of databases provided, at 1 latitude by 1 longitude resolution for the globe, includes (1) locations of rice cultivation, (2) monthly arrays of actively growing rice areas, (3) countries and political subdivisions, and (4) monthly arrays of methane emission from rice cultivation. Ancillary data include (1) a listing, by country, of harvested rice areas and seasonal distribution of crop cycles and (2) country names and codes. Summary tables of zonal/monthly distributions of actively growing rice areas and of methane emissions are presented. Users should consult original publications for complete discussion of the data bases. This short paper is designed only to document formats of the distributed information and briefly describe the contents of the data sets and their initial application to evaluating the role of rice cultivation in the methane budget.

Matthews, Elaine↗
DOE OSTI2023

What's New in the NSRDB

The National Solar Radiation Database (NSRDB) provides solar resource data across the globe at a high temporal and spatial resolution. This data is primarily used in solar energy modeling. The NSRDB is updated annually for the United States and North, Central and South America and the data is currently available from 1998-2021. In 2022 the NSRDB was updated using the latest version of the underlying Physical Solar Model (PSM). This update includes improved surface albedo and gap-filling of cloud properties. The inclusion of these updates reduced the uncertainty in the data compared to previous versions of the NSRDB. The Himawari and Meteosat Indian Ocean Data Coverage (IODC) satellites were added to the Geostationary Operational Environmental Satellite (GOES) and made our coverage global. While standard data from the GOES continues to be served at an hourly 4km x 4km resolution, full resolution data has also been made available to the user. The NSRDB now contains over 200Tb of data with nearly 40Tb being added annually. We provide significant flexibility for data download depending on the amount of data required by the users. In this paper we provide an update on the current status on the NSRDB.

photovoltaic systems↗
NASA NTRS1982

The effect of model resolution and satellite sounding data on GLAS model forecasts

The effect of horizontal model resolution on satellite data impact has been studied for two versions of the GLAS second-order general circulation model: the C-model with a 4-deg latitude by 5-deg longitude resolution and the F-model with a 2.5-deg latitude and 3-deg longitude resolution. It is found that the 48-72 h forecast skill of the GLAS model was significantly improved by the increased resolution. Initial state differences between the SAT and NOSAT cycles using the F-model were on the average smaller than the corresponding differences with the C-model. However, the F-model cycle differences exhibited a smaller scale structure and, in some cases, larger gradients.

Atlas, R.↗
NASA NTRS1993

Comparison of radiation and cloud parameters derived from satellite and aircraft measurements during FIRE 2 cirrus IFO

Meteorological satellite instrument pixel sizes are often much greater than the individual cloud elements in a given scene. Partially cloud-filled pixels can be misinterpreted in many analysis schemes because the techniques usually assume that all of the cloudy pixels are cloud filled. Coincident Landsat and Geostationary Operational Environmental Satellite (GOES) data and degraded-resolution Landsat data were used to study the effects of both sensor resolution and analysis techniques on satellite-derived cloud parameters. While extremely valuable for advancing the understanding of these effects, these previous studies were relatively limited in the number of cloud conditions that were observed and by the limited viewing and illumination conditions. During the First ISCCP Regional Experiment (FIRE) Phase 2 (13 Nov. - 7 Dec. 1991), the NASA ER-2 made several flights over a wide range of cloud fields and backgrounds with several high resolution sensors useful for a variety of purposes including serving as ground truth for satellite-based cloud retrievals. This paper takes a first look at utilizing the ER-2 for validating cloud parameters derived from GOES and NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data.

Heck, Patrick W.↗
DOE OSTI2022

CO2 Sweep Based on Geochemical, and Reservoir Characterization of the Residual Oil Zone of Hess's Seminole San Andres Unit (Final Report)

The study of the ROZ (residual oil zone) versus the MPZ (main pay zone) of the Seminole Field provided a unique insight into the nature of ROZ. This is because we had access to an order of magnitude of core available in other fields. We were also able to use an extensive petrophysical data base with one-foot sampling interval made available by the operator. We also obtained an extensive and unique data base containing the entire production history for the field at full resolution. The data set also includes a unique complete, highly-granular information on volumes of CO2 injection and CO2 production. We created a unique high-resolution model of the reservoir. This is the first such model that has been created. Using this very high-resolution data base we were able to make high resolution, multiphase fluid flow simulations. These fluid flow simulations have enabled our team to evaluate CO2 sweep in the ROZ in comparison with the MPZ.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1989

The origin of the galactic emission in IRAS data

Using the high resolution IRAS data and the radial distribution of gaseous material and those of the interstellar radiation field (ISRF), a model of the Galactic infrared emission was built. The first step consisted of a separation of the diffuse emission in IRAS data from that of the well-defined strong Galactic sources. A well accepted idea is that IR emission comes from dust heated either by the ISRF and/or by internal cloud heating sources. Thus the IR galactic emission was modelled from radial distributions of gas and ISRF and the following three main hypothesis: (1) the dust-to-gas ration is the same in the whole Galaxy; (2) IR emission is proportional to local dust density; and (3) IR emission is also proportional to the local ISRF. The IR emission as modelled was integrated over each line of sight and compared with observed IRAS data. The results show that the IR diffuse component comes from dust associated with H1 and heated by the general ISRF. For the dust embedded in cold H2 component, the heating source is also the general ISRF while the warm component is explained by dust embedded in molecular clouds and heated by high-mass stars born in the close vicinity of the clouds and by disc population ISRF.

Caux, Emanuel↗
DOE OSTI2018

High-Resolution Gamma Spectrometry Data Set for High Burnup Pressurized Water Reactor Used Fuel

Over the past decade, considerable resources have been applied to investigate verification of used nuclear fuel assemblies for international safeguards. The opportunity to expand the available data used to validate these verification techniques was presented in 2016 by the High Burnup Spent Fuel Data Project, which made 25 high-burnup pressurized water reactor used fuel rods available for measurement in the Irradiated Fuels Examination Laboratory at Oak Ridge National Laboratory. With the support of the National Nuclear Security Administration Office of Nonproliferation and Arms Control, a 2017 campaign measured the 25 used fuel rods with a high-resolution gamma spectrometer. A planar high-purity germanium detector was used to provide high-efficiency across an energy range from 60 keV to 3 MeV. Gamma spectra of individual fuel rods were collected in 4.5 mm steps along the entire length of each rod. In addition, spectra were collected on select rods in rotational increments of 30 degrees to provide data on the distribution of fission products along the rod perimeter. The spectra are stored on a controlled-access website for use by others. This paper describes the measurement geometry, used fuel rod characteristics, example spectra, and preliminary analyses performed during the measurement campaign.

Smith, Susan↗
NASA NTRS2004

Processing of High Resolution, Multiparametric Radar Data for the Airborne Dual-Frequency Precipitation Radar APR-2

Following the successful Precipitation Radar (PR) of the Tropical Rainfall Measuring Mission, a new airborne, 14/35 GHz rain profiling radar, known as Airborne Precipitation Radar - 2 (APR-2), has been developed as a prototype for an advanced, dual-frequency spaceborne radar for a future spaceborne precipitation measurement mission. . This airborne instrument is capable of making simultaneous measurements of rainfall parameters, including co-pol and cross-pol rain reflectivities and vertical Doppler velocities, at 14 and 35 GHz. furthermore, it also features several advanced technologies for performance improvement, including real-time data processing, low-sidelobe dual-frequency pulse compression, and dual-frequency scanning antenna. Since August 2001, APR-2 has been deployed on the NASA P3 and DC8 aircrafts in four experiments including CAMEX-4 and the Wakasa Bay Experiment. Raw radar data are first processed to obtain reflectivity, LDR (linear depolarization ratio), and Doppler velocity measurements. The dataset is then processed iteratively to accurately estimate the true aircraft navigation parameters and to classify the surface return. These intermediate products are then used to refine reflectivity and LDR calibrations (by analyzing clear air ocean surface returns), and to correct Doppler measurements for the aircraft motion. Finally, the the melting layer of precipitation is detected and its boundaries and characteristics are identifIed at the APR-2 range resolution of 30m. The resulting 3D dataset will be used for validation of other airborne and spaceborne instruments, development of multiparametric rain/snow retrieval algorithms and melting layer characterization and statistics.

airborne radar↗
NASA NTRS1988

High-spatial-resolution TOVS observations for the FIRE/SRB Wisconsin experiment region from October 14 through November 2, 1986

Maps and concise tables are presented which show TOVS (TIROS Operational Vertical Sounder) HIRS/2 (High Resolution Infrared Sounder) data products, resolution size, and sounding location for the FIRE/SRB (First ISCCP Experiment/Surface Radiation Budget) Wisconsin experiment region from October 14 through November 2, 1986. The data presented are the result of a special analysis of the HIRS/2 sounder from the NOAA-9 and -10 satellites.

Whitlock, Charles H.↗
DOE OSTI2020

Validation of finite-element models using full-field experimental data: Levelling finite-element analysis data through a digital image correlation engine

Full-field data from digital image correlation (DIC) provide rich information for finite-element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions and data filtering. As such, in this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other, and (2) the proposed DIC-levelling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to ‘level’ the FEA data to the DIC data in a regularisation sense. Synthetic ‘experimental’ DIC data were generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errorswere computed, even though therewas no model form error, because the filtering effect of theDIC enginewas neglected. In contrast, the levelling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the levelling approach, it was clearly observed. Finally, the ‘experimental’ DIC datawere purposefully misaligned slightly fromthe FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In conclusion, direct interpolation is insufficient, and the proposed levelling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data have been ‘levelled’ to the DIC data can meaningful, quantitative error maps be computed.

42 ENGINEERING↗
NASA NTRS1984

Cartographic accuracy of Landsat-4 MSS and TM image data

Investigations of the cartographic quality of Landsat-4 MSS and TM image data in CCT-p formats have produced rectification accuracies (rmse/xy/ values) of + or - 2/3 to + or - 1 data pixel for both whole and subscene areas using polynomials of the first through third degree. In order to achieve these accuracies with MSS data, 15 or more Ground Control Points (GCPs) are required, whereas with the TM data sets as few as 5-10 GCPs will suffice. Factors which limit the cartographic rectification accuracies of the Landsat-4 data include: (1) spatial resolution of the data; (2) map and digitizing errors; and (3) terrain relief. Of these factors, data resolution is the most significant, limiting the location of GCPs to about + or - 0.5 pixel. Horizontal displacements due to terrain relief can be minimized by selecting GCPs at or near midrange elevations. Overall, the representative rmse(xy) values of + or - 25 and + or - 55 m for TM and MSS data sets are within U.S. National Map Accuracy Standards for cartographic products of 1:100,000 and 1:200,000 scale, respectively.

Welch, R.↗
NASA NTRS1994

Science with High Spatial Resolution Far-Infrared Data

The goal of this workshop was to discuss new science and techniques relevant to high spatial resolution processing of far-infrared data, with particular focus on high resolution processing of IRAS data. Users of the maximum correlation method, maximum entropy, and other resolution enhancement algorithms applicable to far-infrared data gathered at the Infrared Processing and Analysis Center (IPAC) for two days in June 1993 to compare techniques and discuss new results. During a special session on the third day, interested astronomers were introduced to IRAS HIRES processing, which is IPAC's implementation of the maximum correlation method to the IRAS data. Topics discussed during the workshop included: (1) image reconstruction; (2) random noise; (3) imagery; (4) interacting galaxies; (5) spiral galaxies; (6) galactic dust and elliptical galaxies; (7) star formation in Seyfert galaxies; (8) wavelet analysis; and (9) supernova remnants.

Terebey, Susan↗
DOE OSTI2025

Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis Data and Application to Ukraine

With a potentially increasing share of the electricity grid relying on wind to provide generating capacity and energy, there is an expanding global need for historically accurate, spatiotemporally continuous, high-resolution wind data. Conventional downscaling methods for generating these data based on numerical weather prediction have a high computational burden and require extensive tuning for historical accuracy. In this work, we present a novel deep learning-based spatiotemporal downscaling method using generative adversarial networks (GANs) for generating historically accurate high-resolution wind resource data from the European Centre for Medium-Range Weather Forecasting Reanalysis version 5 data (ERA5). In contrast to previous approaches, which used coarsened high-resolution data as low-resolution training data, we use true low-resolution simulation outputs. We show that by training a GAN model with ERA5 as the low-resolution input and Wind Integration National Dataset Toolkit (WTK) data as the high-resolution target, we achieved results comparable in historical accuracy and spatiotemporal variability to conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. We applied this approach to downscale 30 km, hourly ERA5 data to 2 km, 5 min wind data for January 2000 through December 2023 at multiple hub heights over Ukraine, Moldova, and part of Romania. With WTK coverage limited to North America from 2007–2013, this is a significant spatiotemporal generalization. The geographic extent centered on Ukraine was motivated by stakeholders and energy-planning needs to rebuild the Ukrainian power grid in a decentralized manner. This 24-year data record is the first member of the super-resolution for renewable energy resource data with wind from the reanalysis data dataset (Sup3rWind).

17 WIND ENERGY↗
DOE OSTI2024

Ultrahigh-resolution mass spectrometry data associated with the manuscript “A functional microbiome catalog crowdsourced from North American rivers"

This data package is associated with the publication “A functional microbiome catalog crowdsourced from North American rivers” submitted to Nature (Borton et al., 2024); (https://www.biorxiv.org/content/10.1101/2023.07.22.550117v1). Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial determinants governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb is a publicly available resource that paves the way for watershed predictive modeling and microbiome-based management practices. This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. We identified the most cosmopolitan microbiome members, while also revealing local drivers of strain endemism across ecological dimensions. We provide the first evidence that microbial functional trait expression followed the tenets of the River Continuum Concept, suggesting the structure and function of river microbiomes is predictable. The Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data were one of many different data types used in establishing the ecological dimensions along which different microbes were detected .This data package only contains the processed FTICR-MS data associated with this manuscript; all other data is accessible via Zenodo (https://zenodo.org/records/8173287), GitHub (https://github.com/jmikayla1991/Genome-Resolved-Open-Watersheds-database-GROWdb), KBase (https://doi.org/10.25982/109073.30/1895615), and NCBI via Bioproject PRJNA946291.This dataset consists of (1) a file-level metadata (flmd) file; (2) a data dictionary (dd) file; (3) a readme; (4) three Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) processed data files (a ‘data’ file containing peak-by-sample observations, a ‘mol’ file containing peak metadata, and a transformation profile containing transformation-by-sample observations). All files are .csv or .pdf.

54 ENVIRONMENTAL SCIENCES↗