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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Impact of Quikscat Data on Numerical Weather Prediction

Scatterometer observations of the ocean surface wind speed and direction improve the depiction and prediction of storms at sea. These data are especially valuable where observations are otherwise sparse ---mostly in the Southern Hemisphere and tropics, but also on occasion in the North Atlantic and North Pacific. The SeaWinds scatterometer on the QuikScat satellite was launched in July 1999 and it represents a dramatic departure in design from the other scatterometer instruments launched during the past decade (ERS-1,2 and NSCAT). The NASA Data Assimilation Office (DAO) was the first data assimilation center to assimilate QuikScat SeaWinds data and evaluate their impact on numerical weather prediction. Several data impact experiments have been performed, using systems from both the DAO (GEOS-3) and from NCEP (GDAS). In general, these experiments have shown a modest impact of SeaWinds data on numerical weather prediction, the magnitude of which appears to be comparable to the magnitude of the impact of AMI scatterometer data from the ERS satellites. Some of the main results from these experiments will be presented at the meeting.

Atlas, Robert↗
DOE OSTI2026

Enabling event-by-event precision in γ-ray cascades for neutron-induced reactions

Neutron-induced γ-ray spectra provide key inputs for modern active interrogation applications. A precise modeling of the nuclear reaction and subsequent emission of γ rays is challenging and often impossible due to limitations on evaluated data file formats and nuclear transport simulation codes. We present a framework that addresses these challenges by combining experimental data and reaction-model calculation outputs into an extended candidate version of the Generalized Nuclear Data Structure (GNDS) file, the successor format for the legacy Evaluated Nuclear Data File (ENDF-6). This proposed GNDS hierarchical format contains all the necessary ingredients for inline γ-ray cascade reproduction with event-by-event precision, including continuum–continuum and continuum–discrete transitions following neutron-capture and inelastic neutron scattering reactions. Cascade-event generation based on our approach demonstrates improved energy conservation on an event-by-event basis and permits the use of γ-γ coincidences in applications. This work offers, for the first time, a method to generate neutron-capture and inelastic neutron-scattering γ-ray cascades where energy conservation, correlations, and experimental primaries are fully accounted for.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2022

NASA's Next Generation of Atmospheric Data Science

The Multi-Angle Imager for Aerosols (MAIA) and the Tropospheric Emission: Monitoring of Pollution(TEMPO) are NASA’s next-generation satellite missions for air quality monitoring. These missions will produce high-quality, high-resolution air quality data to support cross-displinary research. The MAIA mission is collaborating with health science researchers and epidemiologists to study the impacts of air quality on health outcomes. TEMPO aims to improve our understanding of tropospheric air pollution chemistry and our ability to make predictions about air quality and climate forcing. TEMPO will offer hourly measurements of tropospheric ozone, aerosols, and clouds focused on North America at high-spatial resolution, while MAIA will produce high-resolution measurements of speciated particulate matter targeting densely populated cities around the globe. Data from these missions will help improve our understanding of the sources, types, and interactions among the aerosols and trace gases that are polluting Earth’s atmosphere, as well as our understanding of the impact of air pollution on pollution on a wide range of important areas including human health, agriculture, weather, and climate change. The challenges of cross-disciplinary research, computationally expensive multi-variate analyses, and high-resolution data at both local and global scales are driving substantial changes across all of NASA’s Distributed Active Archive Centers (DAACs). High resolution data at scales such these requires a new approach to data ingest, archive, and publication. Like other NASA DAACs, the Atmospheric Science Data Center (ASDC), the DAAC that will be responsible for publishing MAIA and TEMPO data products has historically archived and distributed data on premise. DAACs of the future will archive and distribute data in the cloud, enabling them to remake themselves as research-focused data centers that will support on-demand, data-intensive computations for highly accurate retrospective analyses and predictions. Under the new paradigm, data formats and metadata must support on-demand spatial and temporal sub-setting, as well as other data transformation services such as re-gridding and re-sampling. This presentation will discuss work being done to address data formatting and metadata requirements in this dynamic new environment. In addition to the changes in data stewardship practices at the ASDC, the increased focus on supporting scientific research is driving changes in the relationship between DAACs and researchers. While the ASDC will continue to provide first rate data management and stewardship, it is increasingly focused on serving as a partner not only to the science teams that gather and produce the data it publishes, but to the researchers that use that data.

Beth Huffer↗
NASA NTRS2009

Applications of Meteorological Tower Data at Kennedy Space Center

Members of the National Aeronautics and Space Administration (NASA) design and operation communities rely on meteorological information collected at Kennedy Space Center (KSC), located near Cape Canaveral, Florida, to correctly apply the ambient environment to various tasks. The Natural Environments Branch/EV44, located at Marshall Space Flight Center (MSFC) in Huntsville, Alabama, is responsible for providing its NASA customers with meteorological data using various climatological data sources including balloons, surface stations, aircraft, hindcast models, and meteorological towers. Of the many resources available within the KSC region, meteorological towers are preferred for near-surface applications because they record data at regular, frequent intervals over an extensive period of record at a single location. This paper discusses the uses of data measured at several different meteorological towers for a common period of record and how the data can be applied to various engineering decisions for the new Constellation Program Ares and Orion space vehicles.

Altino, Karen M.↗
DOE OSTI2025

CROCUS Urban Canyons - Space Science and Engineering Center (SPARC) Doppler lidar data

This is the netCDF format output from the Halo Photonics Streamline XR Doppler lidar that was deployed next to the Space Science and Engineering Center (SPARC) trailer at the University of Illnois-Chicago greenhouse parking lot during CROCUS Urban Canyons. The purpose of collecting this dataset is to provide vertical and horizontal wind profiles for studying the characteristics of turbulence over the urban canyon of Chicago. This data contains the radial velocity, intensity, and backscatter from the vertical profile, range height indicator, and sector scans that were performed over both Intensive Operating Period 1 and 2 of CROCUS Urban Canyons. There are four different types of files: * The Range Height Indicator (RHI) files contain scans that are along a constant azimuth, spanning the entire hemisphere of elevation values above the surface. * The Velocity Azimuth Display (VAD) files contain the raw radial velocity data from the 6-beam, 60 degree scans. * The User1 files contain stacked Plan Position Indicator scans over a 45 degree quadrant over downtown Chicago. * The Stare files contain vertically pointing scans. These are standard netCDF files that can be opened using xarray. The VAD scans can be processed from their raw radial velocities to horizontal wind speeds with the Atmospheric data Community Toolkit (https://arm-doe.github.io/ACT/).

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WINDS↗
NASA NTRSDate not supplied

Improving GES Disc Data Search and Discovery Through AI Metadata Augmentation

NASA’s Goddard Earth Science (GES) Data and Information Services Center (DISC) is one of twelve data centers in NASA's Science Mission Directorate (SMD), providing vital earth science data to a diverse user base. To enhance the discoverability of this data, GES DISC employs a keyword search system, which leverages scientific keywords embedded in dataset metadata. However, the evolving nature of scientific applications of our data necessitates regular review and augmentation of these keywords. To address this, we developed a service to automatically predict missing science keywords in the metadata. This service constructs a knowledge graph from the latest GES DISC metadata within NASA’s Common Metadata Repository (CMR). Using an open-source library, we trained a machine learning model to predict absent science keywords in the metadata. Our preliminary results indicate that the model has high levels of accuracy at predicting science keywords in the dataset metadata when exposed to data not included in its training. These predicted keywords were then evaluated by GES DISC data curation scientists and compared against other AI tools for metadata augmentation. We aim to enhance the overall usability and accessibility of NASA’s earth science data by implementing this tool in our data curation processes.

Kendall Gilbert↗
NASA NTRS2002

Plans for Assimilating AQUA data at NASA's DAO

NASA's Data Assimilation Office (DAO) is expanding its work with TIROS Operational Vertical Sounder (TOVS) to assimilate data from the advanced instruments which will fly on NASA's AQUA satellite in early 2002. The Atmospheric Infrared Sounder (AIRS), which has over 2000 channels, together with the Advanced Microwave Sounding Unit-A (AMSU-A) and the Humidity Sounder Brazil (HSB) will provide many technical challenges for data assimilation centers. One of the primary concerns is how best to subset the data in order to efficiently extract information about the Earth's atmosphere and surface. This includes static and dynamic channel selection as well as pixel thinning. The DAO is currently experimenting with simulated AIRS/AMSU/HSB radiances within the framework of our finite volume data assimilation system (NDAS) using the OPTRAN radiative transfer code developed as part of the NOAA/NASA Joint Center for Satellite Data Assimilation. The short-term goals include the assessment of the cost of processing various data subsets and preparation for near-real-time assimilation within a few months of launch. We will also discuss plans and tools for evaluating the quality of AIRS data including radiances and level 2 products from the AIRS science team.

Frank, Donald↗
NASA NTRS1975

Interactive image processing for meteorological applications at NASA/Goddard Space Flight Center

The meteorological data processing program at the space center is centered on the analysis of geostationary satellite data. Its objectives are to detect and predict severe storms, to improve short range and long range global numerical weather forecasting models, and to develop improved satellite systems. The Image Display and Manipulation System (IDAMS) for earth resources satellite data processing is described, as is the special purpose software package, METPAK, for performing meteorology operations on IDAMS. The Atmospheric and Oceanographic Information Processing System (AOIPS), a dual terminal multiprocessor is also described.

Billingsley, J. B.↗
NASA NTRS2016

Managing and Servicing Physical Oceanographic Data at a NASA Distributed Active Archive Center

The NASA Earth Science Data Information Systems Project funds and operates 12 Distributed Active Archive Center(s) (DAAC) throughout the United States. Of these 12 centers, the Physical Oceanography DAAC (PO.DAAC) is committed to providing long term archival, distribution and stewardship for NASA physical oceanographic data, primarily derived from space-born satellite systems, but also including a growing set of recent and future in situ observations from the SPURS-1 and SPURS-2 campaigns. Notable NASA missions supported include: Seasat, TOPEX/Poseidon, NSCAT, QuikSCAT, ISS-RapidScat, Jason-1, Jason-2/OSTM, GRACE, Aquarius, GHRSST, and MODIS. The following interagency and international missions are also supported by PO.DAAC: AVHRR, Coriolis, DMSP, MetOp-A, MetOp-B, Oceansat-2. The PO.DAAC currently holds 525 datasets in public distribution, spanning the following observational parameters: sea surface temperature, sea surface salinity, ocean color, ocean surface currents, ocean surface wind speed, ocean surface wind direction, sea surface height, significant wave height, ocean water mass/thickness, and sea ice age. A hundred of these datasets are available in near-real-time. Datasets are distributed through a variety of open-source access protocols including FTP, OPeNDAP, and THREDDS. FTP will soon be phased out in favor of a recently introduced HTTPS PO.DAAC Drive interface that supports WebDAV and interoperable machine-to-machine communication. OPeNDAP supports remote data/metadata query, subset, and download. THREDDS provides the features of OPeNDAP with the additional feature of temporal aggregation. PO.DAAC also offers proprietary tools and services to further enhance the data discovery, visualization and analysis experience, including but not limited to: State of the Ocean, Web Services (data/metadata discovery and extraction), HiTIDE Level-2 subsetter, Live Access Server (LAS), Webification (w10nsci), and Rich Site Summary (RSS) Datacasting. To assist with provenance of datasets, PO.DAAC has implemented DOIs for the data it distributes so that they can be properly cited. There is a user forum and helpdesk that contains data recipes and via which users can get guidance. In summary, this presentation aims to provide a general overview of PO.DAAC’s web portal and data holdings along with a set of illustrative examples leading prospective data users into the practical utility of its tools and services.

Moroni, David F.↗
NASA NTRS2019

NASA Global Satellite and Model Data Products and Services for Tropical Cyclone Research

The lack of observations over vast tropical oceans is a major challenge for tropical cyclone research. Satellite observations and model reanalysis data play an important role in filling these- gaps. Established in the mid-1980's, the Goddard Earth Sciences Data and Information Services Center (GES DISC), as one of the 12 NASA data centers, archives and distributes data from several Earth science disciplines such as precipitation, atmospheric dynamics, atmospheric composition, hydrology, including well-known NASA satellite missions (e.g. TRMM, GPM) and model assimilation projects (MERRA-2). Acquiring datasets suitable for tropical cyclone research in a large data archive is a challenge for many, especially for those who are not familiar with satellite or model data. Over the years, the GES DISC has developed user-friendly data services. For example, Giovanni is an online visualization and analysis tool, allowing users to visualize and analyze over 2000 satellite- and model-based variables with a Web browser, without downloading data and software. In this chapter, we will describe data and services at the GES DISC with emphasis on tropical cyclone research. We will also present two case studies and discuss future plans.

Liu, Zhong↗
NASA NTRSDate not supplied

NASA Giovanni: Analyze, Compare, and Visualize 2000+ Earth Satellite and Model Variables Without Downloading Data and Software

Over vast oceans and remote continents, observations are often scarce and discontinuous. Satellite and model data play a critical role in research and applications. However, finding and accessing satellite and model data can be a daunting task for many, especially those outside the community. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA Science Mission Directorate Data Centers, provides Earth science data, information, and services to everyone such as researchers, application users, educators, and students. GES DISC archives and supports datasets applicable to several NASA Earth Science Focus Areas including Atmospheric Composition, Water & Energy Cycles, Carbon Cycle & Ecosystem, and Climate Variability. To facilitate data discovery, evaluation, and exploration, GES DISC has developed the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni), an online tool to analyze and visualize NASA remote sensing and model data without downloading data and software. As of this writing, over 2000 Earth satellite and model variables are available in Giovanni, including several wellknown NASA satellite missions (e.g., TRMM, GPM) and projects (e.g., MERRA-2, GPCP). Giovanni provides twenty-two plots that can be used to analyze, compare, and explore Earth data across different disciplines. Results can be shared with colleagues and downloaded for further analysis. Over the years, Giovanni has helped publish over 3000 referral papers. In this presentation, we will showcase key variables and plot types in Giovanni with examples. In particular, we will present several popular precipitation products from GPM and CPCP for evaluation and comparison.

data analysis↗
NASA NTRS1976

Space communication system for compressed data with a concatenated Reed-Solomon-Viterbi coding channel

A space communication system incorporating a concatenated Reed Solomon Viterbi coding channel is discussed for transmitting compressed and uncompressed data from a spacecraft to a data processing center on Earth. Imaging (and other) data are first compressed into source blocks which are then coded by a Reed Solomon coder and interleaver, followed by a convolutional encoder. The received data is first decoded by a Viterbi decoder, followed by a Reed Solomon decoder and deinterleaver. The output of the latter is then decompressed, based on the compression criteria used in compressing the data in the spacecraft. The decompressed data is processed to reconstruct an approximation of the original data-producing condition or images.

Rice, R. F.↗
NASA NTRS1996

Earth-Mars Telecommunications and Information Management System (TIMS): Antenna Visibility Determination, Network Simulation, and Management Models

This report presents the results of our research on Earth-Mars Telecommunications and Information Management System (TIMS) network modeling and unattended network operations. The primary focus of our research is to investigate the feasibility of the TIMS architecture, which links the Earth-based Mars Operations Control Center, Science Data Processing Facility, Mars Network Management Center, and the Deep Space Network of antennae to the relay satellites and other communication network elements based in the Mars region. The investigation was enhanced by developing Build 3 of the TIMS network modeling and simulation model. The results of several 'what-if' scenarios are reported along with reports on upgraded antenna visibility determination software and unattended network management prototype.

Odubiyi, Jide↗
NASA NTRS2002

Large Forecast Centers Using TRMM Real-Time Data

As a part of NASA's Earth System Enterprise, The Tropical Rainfall Measuring Mission (TRMM) seeks to understand the mechanisms through which changes in tropical rainfall influence global circulation. Over the past 3 years, TRMM has contributed significantly towards reducing uncertainty in satellite estimates of rainfall in the Tropics, where almost 67% of the Earth's rain falls. TRMM has provided knowledge related to the climatology, seasonality, and variation of tropical rainfall; the mesoscale structure of rain-producing systems, and the physics of precipitation. As with many NASA missions, however, TRMM has provided surprising new knowledge and insight in scientific areas ranging from hurricane diagnosis/prediction to weather forecasting. Examples of current and future plans for use of TRMM data by operational weather centers will be discussed.

Shepherd, James Marshall↗
NASA NTRSDate not supplied

Impact of Anthropogenic Activity, Climate Change, and Urbanization on Wetland Habitat in the Platte River Basin​

The Platte River Basin (PRB) is a dynamic ecosystem where wetlands play a pivotal role as essential habitats for various flora and fauna, including local and migratory birds. It provides many crucial ecosystem services that benefit humans directly and indirectly. However, anthropogenic activity, climate change, and urbanization have resulted in decline in wildlife habitat, elevated flood risk, and wetland loss. To address this issue, NASA DEVELOP partnered with Audubon Great Plains (AGP) to address the vital habitats within urban areas to protect bird species, reduce flood hazards, and analyze the potential impact of future development on wetlands. We utilized remotely sensed data from Landsat 8 Operational Land Imager (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture Radar (SAR) to assess land use and land cover (LULC) change. Nighttime lights data from Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) as well as NASA Socioeconomic Data and Applications Center (SEDAC) population data were also used as inputs to simulate urban growth potential up to 2050 using the open-source FUTure Urban-Regional Environment Simulation (FUTURES) model. A broad scale analysis across 13 focal cities showed varied changes in land use patterns across the PRB, with the most notable being a decrease in agricultural land coverage and an increase in vegetation and grassland coverage. We overlaid a flood extent map with the LULC classifications in Grand Island to identify possible restoration sites under AGP’s Urban Woods and Prairies Initiative. The results for two proposed scenarios showed that at least 51 counties out of 81 in the PRB would experience growth by year 2050. The first scenario (all wetlands are protected) showed that there will be no loss of wetlands by 2050. However, the second scenario (no wetlands are protected) showed a decrease in wetland area and loss of habitat for bird conservation. The results will help AGP to lead awareness workshops for communities about wetland protection and to form impactful conservation strategies in the future.​

Nancee Uniyal↗
NASA NTRS2007

Using Selection Pressure as an Asset to Develop Reusable, Adaptable Software Systems

The Goddard Earth Sciences Data and Information Services Center (GES DISC) at NASA has over the years developed and honed several reusable architectural components for supporting large-scale data centers with a large customer base. These include a processing system (S4PM) and an archive system (S4PA) based upon a workflow engine called the Simple Scalable Script based Science Processor (S4P) and an online data visualization and analysis system (Giovanni). These subsystems are currently reused internally in a variety of combinations to implement customized data management on behalf of instrument science teams and other science investigators. Some of these subsystems (S4P and S4PM) have also been reused by other data centers for operational science processing. Our experience has been that development and utilization of robust interoperable and reusable software systems can actually flourish in environments defined by heterogeneous commodity hardware systems the emphasis on value-added customer service and the continual goal for achieving higher cost efficiencies. The repeated internal reuse that is fostered by such an environment encourages and even forces changes to the software that make it more reusable and adaptable. Allowing and even encouraging such selective pressures to software development has been a key factor In the success of S4P and S4PM which are now available to the open source community under the NASA Open source Agreement

Berrick, Stephen↗
DOE OSTI2020

Surveilling Influenza Incidence With Centers for Disease Control and Prevention Web Traffic Data: Demonstration Using a Novel Dataset

Influenza epidemics result in a public health and economic burden worldwide. Traditional surveillance techniques, which rely on doctor visits, provide data with a delay of 1 to 2 weeks. A means of obtaining real-time data and forecasting future outbreaks is desirable to provide more timely responses to influenza epidemics. This study aimed to present the first implementation of a novel dataset by demonstrating its ability to supplement traditional disease surveillance at multiple spatial resolutions. We used internet traffic data from the Centers for Disease Control and Prevention (CDC) website to determine the potential usability of this data source. Additionally, we tested the traffic generated by 10 influenza-related pages in 8 states and 9 census divisions within the United States and compared it against clinical surveillance data.

60 APPLIED LIFE SCIENCES↗