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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

MODIS Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (MODIS)

The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) is responsible for the distribution of the Level 1 data, and the higher levels of all Ocean and Atmosphere products (Land products are distributed through the Land Processes (LP) DAAC DAAC, and the Snow and Ice products are distributed though the National Snow and Ice Data Center (NSIDC) DAAC). Ocean products include sea surface temperature (SST), concentrations of chlorophyll, pigment and coccolithophores, fluorescence, absorptions, and primary productivity. Atmosphere products include aerosols, atmospheric water vapor, clouds and cloud masks, and atmospheric profiles from 20 layers. While most MODIS data products are archived in the Hierarchical Data Format-Earth Observing System (HDF-EOS 2.7) format, the ocean binned products and primary productivity products (Level 4) are in the native HDF4 format. MODIS Level 1 and 2 data are of the Swath type and are packaged in files representing five minutes of Files for Level 3 and 4 are global products at daily, weekly, monthly or yearly resolutions. Apart from the ocean binned and Level 4 products, these are in Grid type, and the maps are in the Cylindrical Equidistant projection with rectangular grid. Terra viewing (scenes of approximately 2000 by 2330 km). MODIS data have several levels of maturity. Most products are released with a provisional level of maturity and only announced as validated after rigorous testing by the MODIS Science Teams. MODIS/Terra Level 1, and all MODIS/Terra 11 micron SST products are announced as validated. At the time of this publication, the MODIS Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of MODIS/Terra Ocean products. MODIS/Aqua Level 1 and cloud mask products are released with provisional maturity.

Source record↗
NASA NTRS2004

Aura Atmospheric Data Products and Their Availability from NASA Goddard Earth Sciences DAAC

NASA's EOS-Aura spacecraft was launched successfully on July 15, 2004. The four instruments onboard the spacecraft are the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), the Tropospheric Emission Spectrometer (TES), and the High Resolution Dynamics Limb Sounder (HBDLS). The Aura instruments are designed to gather earth sciences measurements across the ultraviolet, visible, infra-red, thermal and microwave regions of the electromagnetic spectrum. Aura will provide over 70 distinct standard atmospheric data products for use in ozone layer and surface UV-B monitoring, air quality forecast, and atmospheric chemistry and climate change studies (http://eosaura.gsfc.nasa.gov/). These products include earth-atmosphere radiances and solar spectral irradiances; total column, tropospheric, and profiles of ozone and other trace gases, surface W-B flux; clouds and aerosol characteristics; and temperature, geopotential height, and water vapor profiles. The MLS, OMI, and HIRDLS data products will be archived at the NASA Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC), while data from TES will be archived at NASA Langley Research Center DAAC. Some of the standard products which have gone through quick preliminary checks are already archived at the GES DAAC (http://daac.nsfc.nasa.gov/) and are available to the Aura science team and data validation team members for data validation; and to the application and visualization software developers, for testing their application modules. Once data are corrected for obvious calibration problems and partially validated using in-situ observations, they would be made available to the broader user community. This presentation will provide details of the whole suite of Aura atmospheric data products, and the time line of the availability of the rest of the preliminary products and of the partially validated provisional products. Software and took available for data access, visualization, and data mining will also be discussed.

Ahmad, S.↗
NASA NTRS2000

Airborne Measurements of Nitric Oxide, Nitrogen Dioxide, Ozone, and Total Reactive Nitrogen During the NASA Global Tropospheric Experiment

Fabrication of the University of Michigan Multichannel Chemiluminescence Instrument (UMMCI) was completed in early 1996 and the instrument participated in test flights on the NASA P3B at Wallops Island prior to integration and deployment for the PEM- Tropics A Mission. The UMMCI consists of 4 channels for simultaneous measurements of ozone and NO with the option for measurements of NO2 and NOy (total reactive nitrogen) when converters are placed upstream of the NO channels. Each NO channel consists of a zeroing volume and reaction vessel, while the ozone channel consists of an ozone catalyst (or scrubber) trap that is not in line with the reaction vessel. The detectors in all for channels are Hamamatsu photomultiplier tubes, which are followed by pulse amplifier discriminators on the NO channels and an electrometer on the ozone channel. Schematics of the Detector Module and NOx/03 Probe Insert and Diagrams of the Control and Data System, the Power and Ground System, the Gas Flow System, and the Calibration System Flow are attached. Intercomparisons were conducted with G. Gregory, NASA/Langley, during the test flights (following prior calibration of the ozone generator/calibrators at the Wallops Long-Path Absorption facility). Initial test results appeared to be reasonable, and instrument characterization studies proceeded for the ozone channel and the 3 NO channels until deployment for integration for the PEM-Tropics Mission. Ozone data was obtained for Flights #4, and 6-2 1, and finalized data was submitted to the PEM-Tropics Data Archive and to the Science Team during the April 1997 Data Workshop. Although it initially appeared that the instrument sensitivity varied, subsequent tests showed that this was the fault of a leak in the ozone calibrator. In fact; the instrument sensitivity has not been observed to vary in a large number of tests over the years since the PEM-Tropics mission. We have, therefore, a very high degree of confidence in the O3 data that we submitted. NO data was obtained for all flights except the mission out of Christmas Island and the subsequent return to Hawaii, during which time the NO channels were contaminated with back-flushing pure NO from the O3 channel. The NO channels were found to suffer from a varying artifact (7 - 22 pptv) which made the instrument's results unreliable for the marine boundary layer portions of the missions (where conditions were extremely clean with NO typically < 2 pptv and O3 only 8 ppbv). Nonetheless, the NO values were an upper limit and were quite useful in identifying pollution layers and outflow from the Latin American Continent. NO data was submitted to the archive for all flights during which data was obtained. Ozone data from the P3B was among the results presented in several peer-reviewed publications. Notably, the ozone data supported the first published finding of evidence for the occurrence of aerosol nucleation in the marine boundary layer. As well, the ozone data was utilized in a treatment of the wavenumber spectra of winds, temperature and trace gases and to demonstrate the occurrence of layering as observed by the P3B during PEM-Tropics A . O3 and NO data were used in an assessment of the impact of southern hemispheric biomass burning, and in the role of NOx and O3 in HOx photochemistry during the PEM Tropics A mission. These data, along with other species measured during PEM-Tropics A, have also been employed in the generation of climatologies for tropospheric ozone and its precursors by the PI's research group.

Carroll, Mary Anne↗
NASA NTRS2013

TPSAS-NF1676L-16802-DND

The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is responsible for the ingest, archive, and distribution of NASA Earth Science data in the areas of radiation budget, clouds, aerosols, and tropospheric chemistry. Currently, the ASDC supports more than 44 projects and has over 1,700 archived data sets, which increase daily. The ASDC’s implementation mission with iRODS is to establish a consolidated, shared services capability that will provide higher quality, more cost effective and efficient services, and greater access to our current science community users and future diverse customers.

Tiffany Mathews↗
NASA NTRSDate not supplied

TPSAS-NF1676L-16824-DND

The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is responsible for the ingest, archive, and distribution of NASA Earth Science data in the areas of radiation budget, clouds, aerosols, and tropospheric chemistry. Currently, the ASDC supports more than 44 projects and has over 1,700 archived data sets, which increase daily. The ASDC?s implementation mission with iRODS is to establish a consolidated, shared services capability that will provide higher quality, more cost effective and efficient services, and greater access to our current science community users and future diverse customers.

Tiffany Mathews↗
NASA NTRS2004

Tools and Data Services from the GSFC Earth Sciences DAAC for Aura Science Data Users

In these times of rapidly increasing amounts of archived data, tools and data services that manipulate data and uncover nuggets of information that potentially lead to scientific discovery are becoming more and more essential. The Goddard Space Flight Center (GSFC) Earth Sciences (GES) Distributed Active Archive Center (DAAC) has made great strides in facilitating science and applications research by, in consultation with its users, developing innovative tools and data services. That is, as data users become more sophisticated in their research and more savvy with information extraction methodologies, the GES DAAC has been responsive to this evolution. This presentation addresses the tools and data services available and under study at the GES DAAC, applied to the Earth sciences atmospheric data. Now, with the data from NASA's latest Atmospheric Chemistry mission, Aura, being readied for public release, GES DAAC tools, proven successful for past atmospheric science missions such as MODIS, AIRS, TRMM, TOMS, and UARS, provide an excellent basis for similar tools updated for the data from the Aura instruments. GES DAAC resident Aura data sets are from the Microwave Limb Sounder (MLS), Ozone Monitoring Instrument (OMI), and High Resolution Dynamics Limb Sounder (HIRDLS). Data obtained by these instruments afford researchers the opportunity to acquire accurate and continuous visualization and analysis, customized for Aura data, will facilitate the use and increase the usefulness of the new data. The Aura data, together with other heritage data at the GES DAAC, can potentially provide a long time series of data. GES DAAC tools will be discussed, as well as the GES DAAC Near Archive Data Mining (NADM) environment, the GIOVANNI on-line analysis tool, and rich data search and order services. Information can be found at: http://daac.gsfc.nasa.gov/upperatm/aura/. Additional information is contained in the original extended abstract.

Kempler, S.↗
DOE OSTI2021

Hyper Suprime-Cam Legacy Archive

Abstract We present the launch of the Hyper Suprime-Cam Legacy Archive (HSCLA), a public archive of processed, science-ready data from the Hyper Suprime-Cam (HSC). HSC is an optical wide-field imager installed at the prime focus of the Subaru Telescope and has been in operation since 2014. While ∼1/3 of the total observing time of HSC has been used for the Subaru Strategic Program (SSP), the remainder of the time is used for Principal Investigator (PI)-based programs. We have processed the data from these PI-based programs and make the processed, high-quality data available to the community through HSCLA. The current version of HSCLA includes data taken in the first year of science operation, 2014. We provide both individual and coadd images as well as photometric catalogs. The photometric catalog from the coadd is loaded to the database, which offers a fast access to the large catalog. There are other online tools such as an image browser and an image cutout tool and they will be useful for science analyses. The coadd images reach 24–27th magnitudes at 5σ for point sources and cover approximately 580 square degrees in at least one filter with 150 million objects in total. We perform extensive quality assurance tests and verify that the photometric and astrometric quality of the data is good enough for most scientific explorations. However, the data are not without problems and users are referred to the list of known issues before exploiting the data for science. All the data and documentations can be found at the data release site, 〈https://hscla.mtk.nao.ac.jp/〉.

Tanaka, Masayuki↗
DOE OSTI2024

Machine Learning (ML) Classifier to Assist Metadata Creation

The Atmospheric Radiation Measurement (ARM) Data Center is responsible for the timely collection, archival, and curation of science data products. These products are freely available through an online data repository. Metadata creation is paramount for scientific users to find and access over seven petabytes of atmospheric science data. The hierarchical metadata structure allows users to search for information at both broad and narrow levels. This project aims to leverage 30 years’ worth of manually created metadata to enable machine predictions of broad-term classifications from narrow-term descriptions. These classification predictions would assist metadata coordinators with their term selections. This paper discusses the cleaning and preprocessing of the training data, the pipeline developed to determine the best model for this task, and the creation of an API metadata classifier for ARM measurement metadata. Our results show that the Linear Support Vector Classification (LinearSVC) algorithm, along with the Term Frequency – Inverse Document Frequency (TF-IDF) vectorizer, is well-suited for our multi-class classification task. Lengthier input training data led to better results, and artificial balancing was unnecessary for this particular use case. This predictive classifier enhances efficiency in metadata creation, as well as supports greater consistency and accuracy in metadata tagging.

Collier, Hannah [ORNL] (ORCID:0000000341284292)↗
DOE OSTI2020

Annotated Bibliography of Literature Addressing the Low-Income Energy Affordability in the United States

Oak Ridge National Laboratory (ORNL), with support from the Georgia Institute of Technology, conducted a “meta review” of low-income energy affordability in the United States. The first step of that review involved the creation of an annotated bibliography of literature focused on low-income household energy affordability, needs, and gaps. This bibliography includes abstracts of the published literature discussed in the meta review. This annotated bibliography describes the relatively current literature (published from 2010 to 2019) that examines low-income energy affordability in the United States. As an initial search criterion, literature was compiled from journal publications archived in Web of Science and Scopus databases.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1990

Data distribution satellite system architecture concept

This paper describes a future communications satellite system architecture concept called the Data Distribution Satellite (DDS). The DDS is envisioned as a new system to be used as an adjunct to TDRS/TDAS for distributing new NASA science data throughout the U.S. as well as internationally. The DDS would also provide networking capability for interchange of science database files among science users and NASA archive depositories. Experimenters would be able to access and control their experimental packages remotely, relieving astronaut workload. This paper gives a conceptual system design based on year 1995 technology. Features of the design include use of Ku and Ka-bands, use of fixed spot beams, 2 Gb/s throughput, and on-board demodulation and switching. The satellite dry mass is 1,300 kg and end-of-life power is 4 kW.

Price, Kent M.↗
NASA NTRS1992

State of the Data Union, 1992

This is the first report on the State of the Data Union (SDU) for the NASA Office of Space Science and Applications (OSSA). OSSA responsibilities include the collection, analysis, and permanent archival of data critical to space science research. The nature of how this is done by OSSA is evolving to keep pace with changes in space research. Current and planned missions have evolved to be more complex and multidisciplinary, and are generating much more data and lasting longer than earlier missions. New technologies enable global access to data, transfer of huge volumes of data, and increasingly complex analysis. The SDU provides a snapshot of this dynamic environment, identifying trends in capabilities and requirements. The current space science data environment is described and parameters which capture the pulse of key functions within that environment are presented. Continuous efforts of OSSA to improve the availability and quality of data provided to the scientific community are reported, highlighting efforts such as the Data Management Initiative.

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NASA NTRS1995

Upper Atmosphere Research Satellite Validation Workshop III: Temperature and Constituents Validation

The Upper Atmosphere Research Satellite (UARS) was launched in September 1991. Since that time data have been retrieved continuously from the various instruments on the UARS spacecraft. These data have been processed by the respective instrument science teams and subsequently archived in the UARS Central Data Handling Facility (CDHF) at the NASA Goddard Space Flight Center, Greenbelt, Maryland. This report contains the proceedings from one of the three workshops held to evaluate the progress in validating UARS constituents and temperature data and to document the quality of that data. The first workshop was held in Oxford, England, in March 1992, five and one-half months after UARS launch. The second workshop was held in Boulder, Colorado in October 1992. Since launch, the various data have undergone numerous revisions. In many instances these revisions are a result of data problems identified during the validation workshops. Thus, the formal validation effort is a continually ongoing process.

Grose, William L.↗
NASA NTRS1995

Link Winds: A visual data analysis system and its application to the atmospheric ozone depletion problem

The Linked Windows Interactive Data System (LinkWinds) is a prototype visual data exploration system resulting from a NASA Jet Propulsion Laboratory (JPL) program of research into the application of graphical methods for rapidly accessing, displaying, and analyzing large multi variate multidisciplinary data sets. Running under UNIX it is an integrated multi-application executing environment using a data-linking paradigm to dynamically interconnect and control multiple windows containing a variety of displays and manipulators. This paradigm, resulting in a system similar to a graphical spreadsheet, is not only a powerful method for organizing large amounts of data for analysis, but leads to a highly intuitive, easy-to-learn user interface. It provides great flexibility in rapidly interacting with large masses of complex data to detect trends, correlations, and anomalies. The system, containing an expanding suite of non-domain-specific applications, provides for the ingestion of a variety of data base formats and hard -copy output of all displays. Remote networked workstations running LinkWinds may be interconnected, providing a multiuser science environment (MUSE) for collaborative data exploration by a distributed science team. The system is being developed in close collaboration with investigators in a variety of science disciplines using both archived and real-time data. It is currently being used to support the Microwave Limb Sounder (MLS) in orbit aboard the Upper Atmosphere Research Satellite (UARS). This paper describes the application of LinkWinds to this data to rapidly detect features, such as the ozone hole configuration, and to analyze correlations between chemical constituents of the atmosphere.

Jacobson, Allan S.↗
NASA NTRS2012

Content Platforms Meet Data Storage, Retrieval Needs

Earth is under a constant barrage of information from space. Whether from satellites orbiting our planet, spacecraft circling Mars, or probes streaking toward the far reaches of the Solar System, NASA collects massive amounts of data from its spacefaring missions each day. NASA s Earth Observing System (EOS) satellites, for example, provide daily imagery and measurements of Earth s atmosphere, oceans, vegetation, and more. The Earth Observing System Data and Information System (EOSDIS) collects all of that science data and processes, archives, and distributes it to researchers around the globe; EOSDIS recently reached a total archive volume of 4.5 petabytes. Try to store that amount of information in your standard, four-drawer file cabinet, and you would need 90 million to get the job done. To manage the flood of information, NASA has explored technologies to efficiently collect, archive, and provide access to EOS data for scientists today and for years to come. One such technology is now providing similar capabilities to businesses and organizations worldwide.

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NASA NTRS2018

Advanced Analytics and Big Earth Data

NASA's Earth Science Data Systems process, archive and distribute petabytes of Earth Observation data to a variety of end users. These end users will face dramatically increased data size in the near future, bringing about new challenges and opportunities in analyzing those data. One area of particular ferment currently is Machine Learning. Many Machine Learning methods are black boxes, limiting direct insight into the data's properties. However, they can be used for a variety of data enhancement purposes, such as parameter retrieval, data fusion and image classification and segmentation. The Earth Observing System Data and Information System is also evolving to host large data volumes in the cloud, enabling data proximal analysis. As part of this effort, an Analytics framework is being developed to support and enhance user analysis of the data. By using standards based services in the framework, diverse user communities can be served, while also allowing inter-system collaboration in the analysis process.

Cloud Computing↗
NASA NTRS2024

Bridging the Gap: Enhancing Prominence and Provenance of NASA Datasets in Research Publications

Attribution of datasets that were used to generate research results described in peer-reviewed publications to the original source of these datasets (which are often archived at NASA Earth Science data centers) has been very challenging. Even though the data citation standard of citing datasets as research artifacts and citing them with Digital Object Identifiers (DOIs) was introduced over a decade ago, most authors do not properly reference the data used in their studies and merely mention them in the text. The lack of proper citations of datasets makes the peer-reviewed publication less transparent, imperils reproducibility, and impedes open science. We offer an open-source publication management methodology and a tool that can help to enhance usage-based data discovery, prominence, and provenance of the data; reproducibility of the research results; and potentially increase the return on investment on NASA-funded research.

open-source↗