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At least 1,081 records · Page 60

Evaluation of geophysical parameters measured by the Nimbus-7 microwave radiometer for the TOGA Heat Exchange Project

The data distributed by the National Space Science Data Center on the Geophysical parameters of precipitable water, sea surface temperature, and surface-level wind speed, measured by the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7, are evaluated with in situ measurements between Jan. 1980 and Oct. 1983 over the tropical oceans. In tracking annual cycles and the 1982-83 E1 Nino/Southern Oscillation episode, the radiometer measurements are coherent with sea surface temperatures and surface-level wind speeds measured at equatorial buoys and with precipitable water derived from radiosonde soundings at tropical island stations. However, there are differences between SMMR and in situ measurements. Corrections based on radiosonde and ship data were derived supplementing correction formulae suggested in the databook. This study is the initial evaluation of the data for quantitative description of the 1982-83 E1 Nino/Southern Oscillation episode. It paves the way for determination of the ocean-atmosphere moisture and latent heat exchanges, a priority of the Tropical Ocean and Global Atmosphere (TOGA) Heat Exchange Program.

Liu, W. Timothy↗

Southern Durchmusterung (Schoenfeld 1886): Documentation for the machine-readable version

The machine-readable version of the catalog, as it is currently being distributed from the Astronomical Data Center, is described. The Southern Durchmusterung (SD) was computerized at the Centre de Donnees Astronomiques de Strasbourg and at the Astronomical Data Center at the National Space Science Data Center, NASA/Goddard Space Flight Center. Corrigenda listed in the original SD volume and published by Kuenster and Sticker were incorporated into the machine file. In addition, one star indicated to be missing in a published list, and later verified, is flagged so that it can be omitted from computer plotted charts if desired. Stars deleted in the various errata lists were similarly flagged, while those with revised data are flagged and listed in a separate table. This catalog covers the zones -02 to -23 degrees; zones +89 to -01 degrees (the Bonner Durchmusterung) are included in a separate catalog available in machine-readable form.

Warren, Wayne H., Jr.↗

NSSDC data listing

The purpose here is to identify, in a highly summarized way, data available from the National Space Science Data Center (NSSDC). Most data are maintained as offline data sets gathered from individual instruments carried on spacecraft; these comprise the Satellite Data Listing. Descriptive names, time spans, data form, and quality of these data sets are identified in the listing, which is sorted alphabetically, first by spacecraft name and then by the principal investigator's or team leader's last name. Several data sets not associated with individual spaceflight instruments are identified in separate listings following the Satellite Data Listing. These include composite spacecraft data sets, ground based data, models, and computer routines. NSSDC also offers data via special services and systems in a number of areas, including the Astronomical Data Center, Coordinated Data Analysis Workshops, NASA Climate Data System, Pilot Land Data System, and Crustal Dynamics Data Information System.

Horowitz, Richard↗

Global views of Venus from Magellan

Magellan data for Venus reveal a planet with a great diversity of volcanic and tectonic landforms, with good evidence of continuing volcanism and tectonism. Weathering, mass wasting and wind erosion and deposition have modified the surface only to the extent of a few meters, thereby preserving an excellent record of tectonic and volcanic processes on a terrestrial-size planet. All cycle 1 mosaics, radiometry, and altimeter data will be made available through the Planetary Data System and the National Space Science Data Center.

Arvidson, R. E.↗

Technology Directions for the 21st Century

Data compression is an important tool for reducing the bandwidth of communications systems, and thus for reducing the size, weight, and power of spacecraft systems. For data requiring lossless transmissions, including most science data from spacecraft sensors, small compression factors of two to three may be expected. Little improvement can be expected over time. For data that is suitable for lossy compression, such as video data streams, much higher compression factors can be expected, such as 100 or more. More progress can be expected in this branch of the field, since there is more hidden redundancy and many more ways to exploit that redundancy.

Crimi, Giles↗

Autonomous sciencecraft experiment : NASA New Millennium Program

In 2006, the Air Force TechSat 21 mission will fly the Autonomous Sciencecraft Experiment (ASE). ASE will perform onboard: science analysis, mission re-planning, and robust execution. These technologies will enable TechSat 21 to respond onboard to sciene opportunities by retargeting future science observations and returning only the most important science data. This capability can dramatically increase science return and is central to future mission concepts to monitor dynamic phenomena such as lo volcanoes, the Europa ice crust, and Martian sandstorms.

Autonomous sciencecraft experiment↗

25th Space Simulation Conference. Environmental Testing: The Earth-Space Connection

Topics covered include: Methods of Helium Injection and Removal for Heat Transfer Augmentation; The ESA Large Space Simulator Mechanical Ground Support Equipment for Spacecraft Testing; Temperature Stability and Control Requirements for Thermal Vacuum/Thermal Balance Testing of the Aquarius Radiometer; The Liquid Nitrogen System for Chamber A: A Change from Original Forced Flow Design to a Natural Flow (Thermo Siphon) System; Return to Mercury: A Comparison of Solar Simulation and Flight Data for the MESSENGER Spacecraft; Floating Pressure Conversion and Equipment Upgrades of Two 3.5kw, 20k, Helium Refrigerators; Affect of Air Leakage into a Thermal-Vacuum Chamber on Helium Refrigeration Heat Load; Special ISO Class 6 Cleanroom for the Lunar Reconnaissance Orbiter (LRO) Project; A State-of-the-Art Contamination Effects Research and Test Facility Martian Dust Simulator; Cleanroom Design Practices and Their Influence on Particle Counts; Extra Terrestrial Environmental Chamber Design; Contamination Sources Effects Analysis (CSEA) - A Tool to Balance Cost/Schedule While Managing Facility Availability; SES and Acoustics at GSFC; HST Super Lightweight Interchangeable Carrier (SLIC) Static Test; Virtual Shaker Testing: Simulation Technology Improves Vibration Test Performance; Estimating Shock Spectra: Extensions beyond GEVS; Structural Dynamic Analysis of a Spacecraft Multi-DOF Shaker Table; Direct Field Acoustic Testing; Manufacture of Cryoshroud Surfaces for Space Simulation Chambers; The New LOTIS Test Facility; Thermal Vacuum Control Systems Options for Test Facilities; Extremely High Vacuum Chamber for Low Outgassing Processing at NASA Goddard; Precision Cleaning - Path to Premier; The New Anechoic Shielded Chambers Designed for Space and Commercial Applications at LIT; Extraction of Thermal Performance Values from Samples in the Lunar Dust Adhesion Bell Jar; Thermal (Silicon Diode) Data Acquisition System; Aquarius's Instrument Science Data System (ISDS) Automated to Acquire, Process, Trend Data and Produce Radiometric System Assessment Reports; Exhaustive Thresholds and Resistance Checkpoints; Reconfigurable HIL Testing of Earth Satellites; FPGA Control System for the Automated Test of MicroShutters; Ongoing Capabilities and Developments of Re-Entry Plasma Ground Tests at EADS-ASTRIUM; Operationally Responsive Space Standard Bus Battery Thermal Balance Testing and Heat Dissipation Analysis; Galileo - The Serial-Production AIT Challenge; The Space Systems Environmental Test Facility Database (SSETFD), Website Development Status; Simulated Reentry Heating by Torching; Micro-Vibration Measurements on Thermally Loaded Multi-Layer Insulation Samples in Vacuum; High Temperature Life Testing of 80Ni-20Cr Wire in a Simulated Mars Atmosphere for the Sample Analysis at Mars (SAM) Instrument Suit Gas Processing System (GPS) Carbon Dioxide Scrubber; The Planning and Implementation of Test Facility Improvements; and Development of a Silicon Carbide Molecular Beam Nozzle for Simulation Planetary Flybys and Low-Earth Orbit.

Packard, Edward↗

GSFC Technology Thrusts and Partnership Opportunities

This slide presentation reviews the technology thrusts and the opportunities to partner in developing software in support of the technological advances at the Goddard Space Flight Center (GSFC). There are thrusts in development of end-to-end software systems for mission data systems in areas of flight software, ground data systems, flight dynamic systems and science data systems. The required technical expertise is reviewed, and the supported missions are shown for the various areas given.

Le Moigne, Jacqueline↗

Restoration of Apollo Data by the NSSDC and the PDS Lunar Data Node

The Lunar Data Node (LDN), under the auspices of the Geosciences Node of the Planetary Data System (PDS), is restoring Apollo data archived at the National Space Science Data Center. The Apollo data were arch ived on older media (7 -track tapes. microfilm, microfiche) and in ob solete digital formats, which limits use of the data. The LDN is maki ng these data accessible by restoring them to standard formats and archiving them through PDS. The restoration involves reading the older m edia, collecting supporting data (metadata), deciphering and understa nding the data, and organizing into a data set. The data undergo a pe er review before archive at PDS. We will give an update on last year' s work. We have scanned notebooks from Otto Berg, P.1. for the Lunar Ejecta and Meteorites Experiment. These notebooks contain information on the data and calibration coefficients which we hope to be able to use to restore the raw data into a usable archive. We have scanned Ap ollo 14 and 15 Dust Detector data from microfilm and are in the proce ss of archiving thc scans with PDS. We are also restoring raw dust de tector data from magnetic tape supplied by Yosio Nakamura (UT Austin) . Seiichi Nagihara (Texas Tech Univ.) and others in cooperation with NSSDC are recovering ARCSAV tapes (tapes containing raw data streams from all the ALSEP instruments). We will be preparing these data for archive with PDS. We are also in the process of recovering and archivi ng data not previously archived, from the Apollo 16 Gamma Ray Spectro meter and the Apollo 17 Infrared Spectrometer.

Williams, David R.↗

ESIP Documentation Cluster Session: GCMD Keyword Update

The Global Change Master Directory (GCMD) Keywords are a hierarchical set of controlled Earth Science vocabularies that help ensure Earth science data and services are described in a consistent and comprehensive manner and allow for the precise searching of collection-level metadata and subsequent retrieval of data and services. Initiated over twenty years ago, the GCMD Keywords are periodically analyzed for relevancy and will continue to be refined and expanded in response to user needs. This talk explores the current status of the GCMD keywords, the value and usage that the keywords bring to different tools/agencies as it relates to data discovery, and how the keywords relate to SWEET (Semantic Web for Earth and Environmental Terminology) Ontologies.

data discover↗

Complexities in Subsetting Level 2 Data

Satellite Level 2 data presents unique challenges for tools and services. From nonlinear spatial geometry to inhomogeneous file data structure to inconsistent temporal variables to complex data variable dimensionality to multiple file formats, there are many difficulties in creating general tools for Level 2 data support. At NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we are implementing a general Level 2 Subsetting service for Level 2 data to a user-specified spatio-temporal region of interest (ROI). In this presentation, we will unravel some of the challenges faced in creating this service and the strategies we used to surmount them.

Data acces↗

Data Preservation: Final Step in the Life Cycle of a Mission

Many NASA Earth Observing System (EOS) have either already reached the end of their active life or are nearing it. Preservmissionsation of data products is a fairly well defined task for the NASA EOS Data Centers or DAACs.The Goddard Earth Sciences Data and Information Services Center (GES-DISC) has implemented a repository system, which is capable of long-term archive of documentation artifacts and other associated digital content. The existing GES-DISC Repository System is based on Fedora Commons, an open-source repository management software, for cost savings and flexibility.The first mission to utilize the GES-DISC Repository System was the High Resolution Dynamics Limb Sounder (HIRDLS) on the Aura spacecraft. Since then, the GES DISC has gathered documentation from the UARS and TOMS into the Repository. The Microwave Limb Sounder (MLS) team has begun delivering some early pre-launch documents to the GES-DISC Repository System as well. Other missions in planning or progress include AIRS, OMI, SORCE, SNPP Sounder, and TRMM.

Johnson, J.↗

A Newly Developing Community-Oriented Data System from NASA GES DISC

Data services are essential to facilitate data access and to aid efficiency of conducting research and application activities. With emerging technologies such as cloud computing and AI/ML (Artificial Intelligence/Machine Learning) leading the pace of the data world, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), home to the permanent archive for multidisciplinary Earth Observation (EO) geospatial data to study atmospheric composition, weather and climate variability, and water and energy cycles is no exception.Interfacing directly with users as part of data center work, we understand the challenges for the required time and effort to discover, visualize, and analyze large varieties and quantities of Earth Observation information for research, monitoring, and decision-making, largely due to the existing data and information systems aim to support experienced users, but has been proved difficult for non-earth scientists and new users that are unfamiliar with the variety of formats and structures in which data, metadata, and information are stored, as well as the required methods to use them. To address these challenges, I will update our latest activities with regard to water-and energy-related products and community-oriented and user-friendly services at the GES DISC, including our plans for the emerging technologies.

Jennifer Wei↗

Using Federated Learning to Overcome Data Gravity in Space

Humans intend to take longer missions to outer space. Understanding the impact that space has on human health is paramount to the success of these missions. Controlled experiments with model organisms are run to infer the impact of space conditions on human health, but the data these experiments generate are too large to transfer to Earth for building models. The same is true for space-relevant data generated on Earth. Ideally, these datasets should be combined to improve statistical power and model accuracy without having to transfer data. Federated learning is such a method which trains an algorithm across decentralized computing systems, each of which has their own local copy of training and testing data. In this research, made possible by NASA@Work, the AI for Life in Space group at NASA demonstrates the use of federated learning to train an ensemble of causality inference models on a combination of data residing on the International Space Station (ISS) and in the cloud. Our work leverages CRISP, a causal inference platform developed during the 2020 Frontier Development Lab’s “Astronaut Health Challenge.” We also leverage the OpenFL federated learning library which was collaboratively developed at Intel and UPenn. We used publicly available data from the NASA Ames Life Sciences Data Archive to identify features in ionizing radiation experiments as causal of changes in cardiac blood velocity. This research demonstrates, for the first time, the possibility of running machine learning algorithms on datasets separated by astronomical distances. In this experiment, all the data were generated in terra, half of which were transferred to the ISS and analyzed on the Spaceborne Computer. In the future, our research will leverage federated learning on data generated in situ on the ISS with data generated terrestrially to predict the impact of spaceflight on mammalian female reproductive capacity.

James Casaletto↗

ASDC Distribution and Services of TEMPO Data

The Tropospheric Emissions: Monitoring of POllution (TEMPO) instrument represents a groundbreaking advancement in remote sensing technology, providing real-time and high-resolution measurements of atmospheric pollutants and air quality monitoring. This presentation will highlight the significance of TEMPO and its data distribution by NASA’s Atmospheric Science Data Center (ASDC) to facilitate the analyses by the research and end user communities. TEMPO's geostationary orbit allows for continuous and high-resolution measurements of key atmospheric pollutants, including nitrogen dioxide (NO 2 ), ozone (O 3 ), and formaldehyde (HCHO). As a result, researchers can investigate the distribution patterns of these pollutants on an hourly basis, providing valuable information for understanding regional and temporal variations in air quality. Furthermore, this presentation will highlight the usability of TEMPO data in complementing ground-based air quality monitoring networks. ASDC distribution services and tools facilitate efficient data handling and analysis to support research and application uses of TEMPO data. As part of NASA’s Earthdata ecosystem, TEMPO will be available through Earthdata Search and Worldview, as well as have variable and spatial subsetting capabilities. This presentation will provide an overview of data access and services available for TEMPO data.

Hazem Mahmoud↗

Data as a Key Resource in Catalysis: A Community Account

The deployment of artificial intelligence (AI) is transforming the scientific fields central to interdisciplinary catalysis research. By enabling more effective use of data, AI (including simpler machine learning and data science tools) holds great promise for accelerating discoveries. However, progress has so far been modest, largely due to the lack of standardized, machine-readable, and openly shared catalysis data. This perspective, accounting for community insights emerging at conferences, analyses the underlying reasons for these challenges and proposes solutions to a future whereFAIR data management becomes an integral part of research in catalysis. In the short-term, we deem that mandatory FAIR data depositing prior to scientific publications along with consensualized top-down guidelines on data sharing powered by ease-to-use tools can make the necessary step change happen to catalyse data as key resource in our community.

36 - MATERIALS SCIENCE↗

Producing Global Science Products for the Moderate Resolution Imaging Spectroradiometer (MODIS) in MODAPS

The MODerate resolution Imaging Spectroradiometer (MODIS) was launched on NASA's EOS-Terra spacecraft December 1999. With 36 spectral bands covering the visible, near wave and short wave infrared. MODIS produces over 40 global science data products, including sea surface temperature, ocean color, cloud properties, vegetation indices land surface temperature and land cover change. The MODIS Data Processing System (MODAPS) produces 400 GB/day of global MODIS science products from calibrated radiances generated in the Earth Observing System Data and Information System (EOSDIS). The science products are shipped to the EOSDIS for archiving and distribution to the public. An additional 200 GB of products are shipped each day to MODIS team members for quality assurance and validation of their products. In the sections that follow, we will describe the architecture of the MODAPS, identify processing bottlenecks encountered in scaling MODAPS from 50 GB/day backup system to a 400 GB/day production system and discuss how these were handled.

Masuoka, Edward J.↗