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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Precipitation measurements from space - Workshop summary 28 April-1 May 1981, Greenbelt, MD

The goals and methods for global precipitation measurements from space are examined. Records currently exist only for visible and IR scans of cloud properties, and are applied from GEO for detecting diurnal variations in precipitation. Microwave radiometry is noted to be a suitable method for supplementing the visible and IR data for measuring stratiform oceanic precipitation, and when used at up to 3 microns can detect areas, if not amounts, of precipitation from GEO. Applications of radar altimeters are proposed in terms of modifications to the Seasat-type 2.2 cm radar, the use of surface target attentuation radar, of frequency agile rain radar, or of adaptive pointing radar. Soil moisture sensing is available with passive microwave radiometry in the 20-50 cm bands, or active sensing in the 5-8 cm bands. The utilization of GARP ground truth data is explored, along with statistical methods for treating the data samples.

Atlas, D.↗
NASA NTRS2008

The NASA NEESPI Data Portal to Support Studies of Climate and Environmental Changes in Non-Boreal Europe

NASA NEESPI (Northern Eurasia Earth Science Partnership Initiative) data portal is a NASA funded project that focuses on collecting satellite remote sensing data, providing tools, information, and services in support of NEESPI scientific objectives (Leptoukh, et al., 2007). The data can be accessed online through anonymous ftp, through an advanced data searching and ordering system Mirador that uses keywords to find data quickly in a Google-like interface, and through the Goddard Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni). The portal provides preprocessed data from different satellite sensors and numerical models to the same spatial and temporal resolution and the same projection so that the data can be used easily to perform inter-comparison or relationship studies. In addition, it provides parameter and spatially subsetted data for regional studies. Studies of regional carbon, hydrology, aerosols in non-boreal Europe and their interactions with global climate are very challenging research topics. The NASA NEESPI data portal makes many satellite data available for such studies, including information on land cover types, fire, vegetation index, aerosols, land surface temperature, soil moisture, precipitation, snow/ice, and other parameters. This paper will introduce the features and products available in the system, focusing on the online data 1 tool, Giovanni NEESPI. An example that explores different data through Giovanni NEESPI in temperate region of non-boreal Europe will be presented.

Shen, Suhung↗
NASA NTRS2015

Exploring NASA GES DISC Data with Interoperable Services

Overview of NASA GES DISC (NASA Goddard Earth Science Data and Information Services Center) data with interoperable services: Open-standard and Interoperable Services Improve data discoverability, accessibility, and usability with metadata, catalogue and portal standards Achieve data, information and knowledge sharing across applications with standardized interfaces and protocols Open Geospatial Consortium (OGC) Data Services and Specifications Web Coverage Service (WCS) -- data Web Map Service (WMS) -- pictures of data Web Map Tile Service (WMTS) --- pictures of data tiles Styled Layer Descriptors (SLD) --- rendered styles.

Giovanni↗
NASA NTRSDate not supplied

Explore Earth Commercial Smallsat Data Acquisition (CSDA) Program

The European Space Agency (ESA), our international partner in the ESA-NASA Earth Science & Observation Joint Program Planning Group (JPPG), is hosting the VH-RODA (Very High-resolution Radar and Optical Data Assessment Workshop) at ESA/ European Space Research Institute (ERSIN) in Frascati, Italy from November 7-10, 2022. The objective of the VH-RODA workshop is to provide an open forum (for the new space, commercial and institutional space sectors) for presenting and discussing about the current status and future developments related to Earth Observation (EO) data quality, calibration and validation of space-borne very high-resolution Synthetic Aperture Radar (SAR) and Optical sensors and data products, with a dedicated focus on commercial EO data providers and related Calibration/Validation activities, synergies between optical and SAR communities, presentation of standards and best practices for data quality. Additionally, the ESA-NASA Joint Program Planning Group (JPPG) Third Party Mission component will meet to further develop non-binding practices on evaluation, identify common guard rails for comparison of data, and coordinate future schedules to leverage shared knowledge. I serve as the Project Manager for the NASA’s Commercial Smallsat Data Acquisition (CSDA) Program and will participate in the VHRODA workshop on behalf of the program.

Commercial Remote Sensing↗
NASA NTRS2021

SEE Test Results for SAMA5D3

ARM processors power a class of high-performance, lower power system on a chip devices. In the absence of radiation effects, these devices are highly desirable for space use. The processor core architecture for ARM devices is licensed to provide computing on multiple hardware platforms. The A5 processor is in a unique pioneering space for providing detailed radiation response data to explore the baseline performance of these devices. These data can help set options for ARM processors and possibly impact design choices for the next generation of ARM fault tolerance capabilities. The SAMA5D3 was tested to establish general SEE performance for a relatively simple implementation of the ARM A5 core. This testing observed SRAM sensitivity starting at an LET of about 3 MeV-cm2/mg, with a saturated cross section of about 2x10-8cm2/bit, and this was determined by both active write and read of the caches, in addition to the use of a debugger to provide test results. Crash/SEFI data was collected using both Linux and bare metal C-code. The onset LET for crashes was about LET 1.5 MeV-cm2/mg, with saturated cross sections of about 2x10-5 cm2 for bare metal (low utilization), and 2x10-4cm2 for Linux (high utilization) tests.

Daniel, Andrew C.↗
DOE OSTI2019

Renewable Energy Data, Analysis, and Decisions Viewed through a Case Study in Bangladesh: Preprint

Many developing countries around the world have signaled their intention to transition their energy sectors to rely on cleaner sources of electricity generation for a variety of reasons that may include complying with their Nationally Determined Contributions (in support of the Paris Climate Agreement), increasing energy security, or reducing air pollution. Renewable energy resources are increasingly a cost competitive option for new electricity generation; however, nations must consider renewable energy potential if they wish to increase these technologies in their electricity generation mix. Yet, goal setting, policymaking, grid modeling, and investment decisions that will enable renewable energy development all depend on the existence and quality of renewable energy resource data. This paper aims to summarize the relationship between renewable energy data, analysis, and decision making for developing countries seeking to transition their energy sector and to consider Bangladesh as a case study of a country that has worked with development organizations and the National Renewable Energy Laboratory to develop a national inventory of renewable energy resource data to enable critical decision making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

DeepUQ: Assessing the Aleatoric Uncertainties from two Deep Learning Methods

Assessing the quality of aleatoric uncertainty estimates from uncertainty quantification (UQ) deep learning methods is important in scientific contexts, where uncertainty is physically meaningful and important to characterize and interpret exactly. We systematically compare aleatoric uncertainty measured by two UQ techniques, Deep Ensembles (DE) and Deep Evidential Regression (DER). Our method focuses on both zero-dimensional (0D) and two-dimensional (2D) data, to explore how the UQ methods function for different data dimensionalities. We investigate uncertainty injected on the input and output variables and include a method to propagate uncertainty in the case of input uncertainty so that we can compare the predicted aleatoric uncertainty to the known values. We experiment with three levels of noise. The aleatoric uncertainty predicted across all models and experiments scales with the injected noise level. However, the predicted uncertainty is miscalibrated to $\rm{std}(\sigma_{\rm al})$ with the true uncertainty for half of the DE experiments and almost all of the DER experiments. The predicted uncertainty is the least accurate for both UQ methods for the 2D input uncertainty experiment and the high-noise level. While these results do not apply to more complex data, they highlight that further research on post-facto calibration for these methods would be beneficial, particularly for high-noise and high-dimensional settings.

Nevin, Rebecca↗