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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

A Spatial Analysis and Modeling System (SAMS) for environment management

This is a proposal to develop a uniform global environmental data gathering and distribution system to support the calibration and validation of remotely sensed data. SAMS is based on an enhanced version of FEMA's Integrated Emergency Management Information Systems and the Department of Defense's Air land Battlefield Environment Software Systems. This system consists of state-of-the-art graphics and visualization techniques, simulation models, database management and expert systems for conducting environmental and disaster preparedness studies. This software package will be integrated into various Landsat and UNEP-GRID stations which are planned to become direct readout stations during the EOS (Earth Observing System) timeframe. This system would be implemented as a pilot program to support the Tropical Rainfall Measuring Mission (TRMM). This will be a joint NASA-FEMA-University-Industry project.

Stetina, Fran↗
NASA NTRS1999

The Role of Data Assimilation in the Study of Regional and Global Variability of the Hydrological Cycle

In the coming years, researchers will have at their disposal a host of new observations from advanced space-based sensors (e.g. the Tropical Rainfall Measuring Mission, EOS Terra and PM missions) providing, among other things, a more complete and accurate description of various components of the Earth's hydrological cycle. Also, increasingly more sophisticated and comprehensive geophysical models will provide researchers better tools for simulating the hydrological cycle, and for carrying out mechanistic studies of the role of moist processes in the climate system. In addition, new data sets generated with global four-dimensional data assimilation (4DDA) systems will provide comprehensive and complete information on both the state and forcing of the climate system. Ideally, the 4DDA systems optimally incorporate all relevant information from the observations together with a first guess from a state-of-the-art geophysical model to produce a "best" estimate of the climate state. Furthermore, to the extent that the assimilating models are realistic and are constrained by the observations, they should provide reliable estimates of the associated physical processes or climate forcing fields. While operational weather centers now have a considerable history of providing reliable estimates of the basic atmospheric state variables, the associated processes or diagnostic fields (which are less well constrained by the observations and sensitive to errors in the model's physical parameterizations) are still considered experimental and of uncertain quality. In this study we will examine the current generation of reanalysis products to assess the capabilities of 4DDA systems to represent components of the hydrological cycle. The focus is on the role of the model in providing consistent estimates of moist processes. We will also assess whether current observations provide sufficient constraints on these model- generated fields.

Schubert, Siegfried↗
NASA NTRS2004

Application of Geostatistical Simulation to Enhance Satellite Image Products

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

Hlavka, Christine A.↗
NASA NTRS1992

A Spatial Analysis and Modeling System (SAMS) for environment management

This is a proposal to develop a uniform global environmental data gathering and distribution system to support the calibration and validation of remotely sensed data. SAMS is based on an enhanced version of FE MA's Integrated Emergency Management Information Systems and the Department of Defense's Air Land Battlefield Environment Software Systems. This system consists of state-of-the-art graphics and visualization techniques, simulation models, database management and expert systems for conducting environmental and disaster preparedness studies. This software package will be integrated into various Landsat and UNEP-GRID stations which are planned to become direct readout stations during the EOS timeframe. This system would be implemented as a pilot program to support the Tropical Rainfall Measuring Mission (TRMM). This will be a joint NASA-FEMA-University-Industry project.

Vermillion, Charles H.↗
DOE OSTI2025

Learning robust parameter inference and density reconstruction in flyer plate impact experiments

Estimating physical parameters or material properties from experimental observations is a common objective in many areas of physics and material science. In many experiments, especially in shock physics, radiography is the primary means of observing the system of interest. However, radiography does not provide direct access to key state variables, such as density, which prevents the application of traditional parameter estimation approaches. Here we focus on flyer plate impact experiments on porous materials, and resolving the underlying parameterized equation of state (EoS) and crush porosity model parameters given radiographic observation(s). We use machine learning as a tool to demonstrate with high confidence that using only high impact velocity data does not provide sufficient information to accurately infer both EoS and crush model parameters, even with fully resolved density fields or a dynamic sequence of images. We thus propose an observable data set consisting of low and high impact velocity experiments/simulations that capture different regimes of compaction and shock propagation, and proceed to introduce a generative machine learning approach which produces a posterior distribution of physical parameters directly from radiographs. We demonstrate the effectiveness of the approach in estimating parameters from simulated flyer plate impact experiments, and show that the obtained estimates of EoS and crush model parameters can then be used in hydrodynamic simulations to obtain accurate and physically admissible density reconstructions. Finally, we examine the robustness of the approach to model mismatches, and find that the learned approach can provide useful parameter estimates in the presence of out-of-distribution radiographic noise and previously unseen physics, thereby promoting a potential breakthrough in estimating material properties from experimental radiographic images.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Applications of ISES for the atmospheric sciences

The proposed Information Sciences Experiment System (ISES) will offer the opportunity for real-time access to measurements acquired aboard the Earth Observation System (Eos) satellite. These measurements can then be transmitted to remotely located ground based stations. The application of such measurements to issues related to atmospheric science which was presented to a workshop convened to review possible application of the ISES in earth sciences is summarized. The proposed protocol for Eos instruments requires that measurement results be available in a central data archive within 72 hours of acquiring data. Such a turnaround of raw satellite data to the final product will clearly enhance the timeliness of the results. Compared to the time that results from many current satellite programs, the 72 hour turnaround may be considered real time. Examples are discussed showing how real-time measurements from one or more of the proposed Eos instruments could have been applied to the study of certain issues important to global atmospheric chemistry. Each of the examples discussed is based upon a field mission conducted during the past five years. Each of these examples will emphasize how real-time data could have been used to alter the course of a field experiment, thereby enhancing the scientific output. For the examples, brief overviews of the scientific rationale and objectives, the region of operation, the measurements aboard the aircraft, and finally how one or more of the proposed Eos instruments could have provided data to enhance the productivity of the mission are discussed.

Hoell, James M., Jr.↗
NASA NTRS1990

NASA Communications Augmentation network

The NASA Communications (Nascom) Division of the Mission Operations and Data Systems Directorate (MO&DSD) is to undertake a major initiative to develop the Nascom Augmentation (NAUG) network to achieve its long-range service objectives for operational data transport to support the Space Station Freedom Program, the Earth Observing System (EOS), and other projects. The NAUG is the Nascom ground communications network being developed to accommodate the operational traffic of the mid-1990s and beyond. The NAUG network development will be based on the Open Systems Interconnection Reference Model (OSI-RM). This paper describes the NAUG network architecture, subsystems, topology, and services; addresses issues of internetworking the Nascom network with other elements of the Space Station Information System (SSIS); discusses the operations environment. This paper also notes the areas of related research and presents the current conception of how the network will provide broadband services in 1998.

Omidyar, Guy C.↗
NASA NTRS1996

The Challenges Facing Science Data Archiving on Current Mass Storage Systems

This paper discusses the desired characteristics of a tape-based petabyte science data archive and retrieval system required to store and distribute several terabytes (TB) of data per day over an extended period of time, probably more than 115 years, in support of programs such as the Earth Observing System Data and Information System (EOSDIS). These characteristics take into consideration not only cost effective and affordable storage capacity, but also rapid access to selected files, and reading rates that are needed to satisfy thousands of retrieval transactions per day. It seems that where rapid random access to files is not crucial, the tape medium, magnetic or optical, continues to offer cost effective data storage and retrieval solutions, and is likely to do so for many years to come. However, in environments like EOS these tape based archive solutions provide less than full user satisfaction. Therefore, the objective of this paper is to describe the performance and operational enhancements that need to be made to the current tape based archival systems in order to achieve greater acceptance by the EOS and similar user communities.

Peavey, Bernard↗
NASA NTRS2009

Transitioning NPOESS Data to Weather Offices: The SPoRT Paradigm with EOS Data

Real-time satellite information provides one of many data sources used by NWS weather forecast offices (WFOs) to diagnose current weather conditions and to assist in short-term forecast preparation. While GOES satellite data provides relatively coarse spatial resolution coverage of the continental U.S. on a 10-15 minute repeat cycle, polar orbiting imagery has the potential to provide snapshots of weather conditions at high-resolution in many spectral channels. Additionally, polar orbiting sounding data can provide additional information on the thermodynamic structure of the atmosphere in data sparse regions of at asynoptic observation times. The NASA Short-term Prediction Research and Transition (SPoRT) project has demonstrated the utility of polar orbiting MODIS and AIRS data on the Terra and Aqua satellites to improve weather diagnostics and short-term forecasting on the regional and local scales. SPoRT scientists work directly forecasters at selected WFOS in the Southern Region (SR) to help them ingest these unique data streams into their AWIPS system, understand how to use the data (through on-site and distance learn techniques), and demonstrate the utility of these products to address significant forecast problems. This process also prepares forecasters for the use of similar observational capabilities from NPOESS operational sensors. NPOESS environmental data records (EDRs) from the Visible 1 Infrared Imager I Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrlS) and Advanced Technology Microwave Sounder (ATMS) instruments and additional value-added products produced by NESDIS will be available in near real-time and made available to WFOs to extend their use of NASA EOS data into the NPOESS era. These new data streams will be integrated into the NWs's new AWIPS II decision support tools. The AWIPS I1 system to be unveiled in WFOs in 2009 will be a JAVA-based decision support system which preserves the functionality of the existing systems and offers unique development opportunities for new data sources and applications in the Service Orientated Architecture ISOA) environment. This paper will highlight some of the SPoRT activities leading to the integration of VllRS and CrIS/ATMS data into the display capabilities of these new systems to support short-term forecasting problems at WFOs.

Jedlovec, Gary↗
NASA NTRS2007

Recent Theoretical Advances in Analysis of AIRS/AMSU Sounding Data

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. This paper describes the AIRS Science Team Version 5.0 retrieval algorithm. Starting in early 2007, the Goddard DAAC will use this algorithm to analyze near real time AIRS/AMSU observations. These products are then made available to the scientific community for research purposes. The products include twice daily measurements of the Earth's three dimensional global temperature, water vapor, and ozone distribution as well as cloud cover. In addition, accurate twice daily measurements of the earth's land and ocean temperatures are derived and reported. Scientists use this important set of observations for two major applications. They provide important information for climate studies of global and regional variability and trends of different aspects of the earth's atmosphere. They also provide information for researchers to improve the skill of weather forecasting. A very important new product of the AIRS Version 5 algorithm is accurate case-by-case error estimates of the retrieved products. This heightens their utility for use in both weather and climate applications. These error estimates are also used directly for quality control of the retrieved products. Version 5 also allows for accurate quality controlled AIRS only retrievals, called "Version 5 AO retrievals" which can be used as a backup methodology if AMSU fails. Examples of the accuracy of error estimates and quality controlled retrieval products of the AIRS/AMSU Version 5 and Version 5 AO algorithms are given, and shown to be significantly better than the previously used Version 4 algorithm. Assimilation of Version 5 retrievals are also shown to significantly improve forecast skill, especially when the case-by-case error estimates are utilized in the data assimilation process.

Susskind, Joel↗
NASA NTRS2012

Geophysical Information from Advanced Sounder Infrared Spectral Radiance

Advanced satellite sensors are tasked with improving global observations of the Earth's atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Satisfying this type of improvement for inferred geophysical information from these observations requires optimal usage of data from current systems as well as enhancements to future sensors. This presentation addresses the information content present in infrared spectral radiance from advanced atmospheric sounders with an emphasis on knowledge of thermodynamic state and trace species. Results of trade-off studies conducted to evaluate the impact of spectral resolution, spectral coverage, instrument noise, and a priori knowledge on remote sensing system information content will be discussed. A focus is placed on information achievable from the Atmospheric InfraRed Sounder (AIRS) on the NASA EOS Aqua satellite in orbit since 2002, the Infrared Atmospheric Sounding Interferometer (IASI) aboard MetOp-A since 2006, and the Cross-track Infrared Sounder (CrIS) instrument aboard the NPP and JPSS series of satellites which began 28 October 2011.

Larar, Allen M.↗
NASA NTRSDate not supplied

Dissemination of Global Flood Severity and Surface Water Mapping using Remote Sensing Data to Global Stakeholders

Flooding is a natural event that occurs frequently with high severity worldwide, responsible for significant societal and economic impacts. Disaster managers face significant challenges managing essential information for preparedness, response, and recovery efforts. The development of an open access, global flood alerting system for effective identification of flood impacted areas, classification of potential impacts, and the formulation of effective emergency response measures requires the incorporation of a wide variety of flood models and remote sensing data sources from multiple platforms. NASA is currently funding projects focused on flood forecasting, post-event flood mapping, flood depth estimation and pre-event flood severity estimation using Earth observation (EO) datasets and derived flood products. A new initiative in the Disasters Program is underway to disseminate flood products from different hydrologic models and sensors to global stakeholders via Pacific Disaster Center’s DisasterAWARE®, NASA’s Disasters Mapping Portal and potentially other mechanisms. This initiative focuses on improving response capacity and use of EO products in near real-time by a broader community for resource planning in case of extreme events. As part of this initiative, we have deployed Model of Models (MoM) – an open-source ensemble approach, that integrates outputs from hydrologic models and EO data from optical imagery to assess flood severity daily at sub-watershed level globally. The MoM output is integrated with the incident event system of DisasterAWARE to generate flood severity risk and flood impact boundaries, which are disseminated via the DisasterAWARE platform to different stakeholders globally for decision-making and response efforts. The next step will focus on using MoM outputs to estimate flood depth and extent mapping using high-resolution Synthetic Aperture Radar imagery, impact assessment using optical imagery and population datasets, and damage estimation using critical infrastructure datasets, which would be disseminated via DisasterAWARE to decision-makers, emergency managers and first responders around the world.

flood↗
NASA NTRS2011

Hyperspectral Mapping of the Invasive Species Pepperweed and the Development of a Habitat Suitability Model

Mapping and predicting the spatial distribution of invasive plant species is central to habitat management, however difficult to implement at landscape and regional scales. Remote sensing techniques can reduce the impact field campaigns have on these ecologically sensitive areas and can provide a regional and multi-temporal view of invasive species spread. Invasive perennial pepperweed (Lepidium latifolium) is now widespread in fragmented estuaries of the South San Francisco Bay, and is shown to degrade native vegetation in estuaries and adjacent habitats, thereby reducing forage and shelter for wildlife. The purpose of this study is to map the present distribution of pepperweed in estuarine areas of the South San Francisco Bay Salt Pond Restoration Project (Alviso, CA), and create a habitat suitability model to predict future spread. Pepperweed reflectance data were collected in-situ with a GER 1500 spectroradiometer along with 88 corresponding pepperweed presence and absence points used for building the statistical models. The spectral angle mapper (SAM) classification algorithm was used to distinguish the reflectance spectrum of pepperweed and map its distribution using an image from EO-1 Hyperion. To map pepperweed, we performed a supervised classification on an ASTER image with a resulting classification accuracy of 71.8%. We generated a weighted overlay analysis model within a geographic information system (GIS) framework to predict areas in the study site most susceptible to pepperweed colonization. Variables for the model included propensity for disturbance, status of pond restoration, proximity to water channels, and terrain curvature. A Generalized Additive Model (GAM) was also used to generate a probability map and investigate the statistical probability that each variable contributed to predict pepperweed spread. Results from the GAM revealed distance to channels, distance to ponds and curvature were statistically significant (p < 0.01) in determining the locations of suitable pepperweed habitats.

Pepperweed↗
NASA NTRS2004

The Lifecycle of NASA's Earth Science Enterprise Data Resources

A major endeavor of NASA's Earth Science Enterprise (ESE) is to acquire, process, archive and distribute data from Earth observing satellites in support of a broad set of science research and applications in the U. S. and abroad. NASA policy directives specifically call for the agency to collect, announce, disseminate and archive all scientific and technical data resulting from NASA and NASA-funded research. During the active life of the satellite missions, while the data products are being created, validated and refined, a number of NASA organizations have the responsibility for data and information system functions. Following the completion of the missions, the responsibility for the long-term stewardship of the ocean and atmospheric, and land process data products transitions to the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS), respectively. Ensuring that long-term satellite data be preserved to support global climate change studies and other research topics and applications presents some major challenges to NASA and its partners. Over the last several years, with the launch and operation of the EOS satellites and the acquisition and production of an unprecedented volume of Earth science data, the importance of addressing these challenges has been elevated. The lifecycle of NASA's Earth science data has been the subject of several agency and interagency studies and reports and has implications and effects on agency charters, policies and budgets and on their data system's requirements, implementation plans and schedules. While much remains to be done, considerable progress has been made in understanding and addressing the data lifecycle issues.

McDonald, Kenneth R.↗
NASA NTRS1999

An Overview of Future NASA Missions, Concepts, and Technologies Related to Imaging of the World's Land Areas

In the near term NASA is entering into the peak activity period of the Earth Observing System (EOS). The EOS AM-1 /"Terra" spacecraft is nearing launch and operation to be followed soon by the New Millennium Program (NMP) Earth Observing (EO-1) mission. Other missions related to land imaging and studies include EOS PM-1 mission, the Earth System Sciences Program (ESSP) Vegetation Canopy Lidar (VCL) mission, the EOS/IceSat mission. These missions involve clear advances in technologies and observational capability including improvements in multispectral imaging and other observing strategies, for example, "formation flying". Plans are underway to define the next era of EOS missions, commonly called "EOS Follow-on" or EOS II. The programmatic planning includes concepts that represent advances over the present Landsat-7 mission that concomitantly recognize the advances being made in land imaging within the private sector. The National Polar Orbiting Environmental Satellite Series (NPOESS) Preparatory Project (NPP) is an effort that will help to transition EOS medium resolution (herein meaning spatial resolutions near 500 meters), multispectral measurement capabilities such as represented by the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) into the NPOESS operational series of satellites. Developments in Synthetic Aperture Radar (SAR) and passive microwave land observing capabilities are also proceeding. Beyond these efforts the Earth Science Enterprise Technology Strategy is embarking efforts to advance technologies in several basic areas: instruments, flight systems and operational capability, and information systems. In the case of instruments architectures will be examined that offer significant reductions in mass, volume, power and observational flexibility. For flight systems and operational capability, formation flying including calibration and data fusion, systems operation autonomy, and mechanical and electronic innovations that can reduce spacecraft and subsystem resource requirements. The efforts in information systems will include better approaches for linking multiple data sets, extracting and visualizing information, and improvements in collecting, compressing, transmitting, processing, distributing and archiving data from multiple platforms. Overall concepts such as sensor webs, constellations of observing systems, and rapid and tailored data availability and delivery to multiple users comprise and notions Earth Science Vision for the future.

Salomonson, Vincent V.↗
NASA NTRS2024

Baltimore Energy & Infrastructure: Assessing Urban Heat Vulnerability in Baltimore Neighborhoods to Inform Transportation Resiliency Planning Efforts

Across the world, climate change is altering cities and their local climate systems. Following global trends of rising mean temperatures, Baltimore, Maryland is projected to experience more frequent extreme heat events. Exacerbated by Urban Heat Island (UHI) effects, residents of the city face high temperatures from limited tree canopy, highly paved and impervious surfaces, limited air flow, and high concentrations of localized emissions. Urban heat is dispersed asymmetrically, with historically marginalized populations experiencing disproportionately severe heat. Recognizing the impacts of extreme urban heat, the Maryland Transit Administration (MTA) collaborated with us, the Spring 2024 Goddard Energy and Infrastructure NASA DEVELOP team to assess urban impacts of MTA users and assets and explore opportunities to enhance resiliency planning. We evaluated the feasibility of NASA Earth observations (EOs) in visualizing heat vulnerability in Baltimore City and County. We mapped UHI and extreme heat using remote sensing observations, tailored a Heat Priority Score (HPS) to analyze heat data in tandem with socioeconomic data from American Community Survey (ACS), and utilized SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model to estimate MTA riders’ thermal comfort. NASA EOs served to quantify the distribution and severity of extreme heat at the block group level, which was found to correlate with a lack of vegetation and presence of densely built-up surroundings. The HPS revealed that extreme heat events most negatively impact communities that exhibit social vulnerability through indicators such as age, race, and income. These findings will inform neighborhood resiliency plans for the MTA that can be incorporated into their Adaptation Resiliency Toolbox (ART).

Baltimore,↗
NASA NTRSDate not supplied

Using NASA LANCE Near Real-Time Earth Observations for Disaster Risk Reduction

The NASA Earth Science Disasters Program handles requests from stakeholders and provides rapid response for Disaster Risk Reduction using Near Real-Time (NRT) products from NASA’s Land, Atmosphere NRT Capability for Earth Observing System (EOS) (LANCE). The combination of all available LANCE NRT satellite products provides global coverage at multiple times per day, which makes it possible to help users in different phases of the disaster’s life cycle. For wildfires and volcano eruption disasters, LANCE NRT fire and atmosphere products have been used to locate fires and high-temperature heat sources, and to assess the extent of air pollutions. Knowledge of the geographical position and direction of smokes, fires, lava flows provided critical information for disaster prediction and prevention. For hurricanes, tropical cyclones and earthquakes, LANCE global flood products and NASA’s Black Marble night-time light products have been used for monitoring land cover and land use change over time in disaster impacted areas. Users can use pre- and post-disaster maps to assess the extent of damage, and to make decisions for activities in reconstruction and recovery in infrastructure and health on the ground. LANCE NRT data are made available through the Earth data website and have been archived and visualized in NASA Disasters Mapping Portal, NASA LANCE Fire Information for Resource Management System (FIRMS) and NASA Worldview for the use of stakeholders.

Tian Yao↗
NASA NTRS2018

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Earth observations↗