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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Lightning Strike Distance Distribution Beyond a Preexisting Lightning Area

The 45th Weather Squadron (45 WS) asked the Applied Meteorology Unit (AMU) to review the 30-year-old, lightning stand-off distances of 5 nautical miles (nmi) for applicability to today's operations. This was based on the realization that previous lightning strike distance studies did not match how 45 WS issues lightning warnings (Roeder, 2008). The previous lightning distance studies were from the point of origin of the lightning or the average starting location that would tend to be in the core of the thunderstorm. However, the 45 WS issues lightning warnings based on the edge of a preexisting lightning area. Before beginning the AMU project, it took several years to develop a method to calculate a distance distribution beyond a preexisting area (Roeder, 2015). The AMU pulled Lightning Detection and Ranging (LDAR) sensor data from 1/1/2013 to 12/31/2013. This dataset consisted of 37 million individual source data points from the LDAR sensors. Only sources within 50 km north, south, east or west of the LDAR grid center were included in the dataset. This limited the use of LDAR data to that with the greatest accuracy of source detection and increased data processing. Points were grouped into flashes based on spatial and temporal criteria. Based on the sensitivity analysis the AMU performed on the flash clustering algorithm, a time value of 0.3 seconds was found to model flashes adequately. Distance parameters were tested from 1,500 to 7,500 meters (m) in 500 m increments. Distance parameters of both 3,000 m and 4,000 m produced results in the plotting tool that were most representative of the physical behavior of lightning. Thus statistics were gathered for the most representative of these spatial and temporal criteria on the flash size and the polygon expansion distance in order to find the correct data distributions. The best fit curves for the LDAR polygon expansion frequency vs. distances for both the 3 kilometer (km) and 4 km distance threshold values were exponential decay functions and had R2 values of > 0.998, indicating good model fits. The equations of the best fit curves were then used to calculate a desired safety radius of 4 nmi for either 3 km or 4 km distance threshold criteria. The AMU analysis concludes the safe reduction of the 5 nmi lightning warning circles to 4 nmi should improve the operational impact by 36% if based on distance from the center of the property area being protected. If based on the edge of the property being protected, then the reduction is 4.5 nmi to 4 nmi and the operational impact is decreased by 21%. For the 6 nmi lightning warning circles, the recommended 4 nmi stand-off distance will result in a safe reduction of operational impact of 31% if based on the center of the area being protected, or 16% if based on the edge of the property.

Flash clustering algorithm↗
NASA NTRS1977

Change detection in coastal zone environments

A study was conducted with the objective to develop and evaluate various change detection techniques based upon computer-aided analysis of Landsat multispectral scanner (MSS) data to monitor coastal zone environments. The study site selected includes a portion of the Matagorda Bay estuarine system located along the Texas Coast. The principal data sources for the study were MSS data collected on November, 27, 1972 and February 25, 1975. The MSS data were processed and a multidata eight-channel data set at a scale of 1:24,000 was obtained. A description is presented of four change detection techniques which were designed and implented for evaluation, taking into account postclassification comparison change detection, delta data change detection, spectral/temporal change classification, and layered spectral/temporal approach. The results of the investigation are discussed.

Weismiller, R. A.↗
NASA NTRS1980

Applications of radar imagery to arctic and subarctic problems

Radar imagery provides year around data acquisition of areas in the Arctic and the Subarctic. The foremost factor influencing the choice of radar imagery as the major data source was the demand for neotric data. The weather is so adverse in parts of Alaska that radar imagery was the only remote sensing technique which could meet the demand. The major map products derived from radar imagery are landform maps and lineament maps. These maps are used to make environmental assessments of areas and to reconstruct the geomorphic history of certain regions or features. Since radar imagery provides information about geologic structure and geomorphic features, it can be used to determine the relationship which exists between geologic structure and geomorphology. Important geologic information related to surface roughness can be obtained through a dry snow cover. Radar imagery is the only remote sensing technique which can provide information needed about sea ice through a cloud cover and dry snow, during strong wind conditions, and throughout the Arctic night.

Cannon, P. J.↗
NASA NTRS1979

A method for the processing and analysis of digital terrain elevation data

A method is presented for the processing and analysis of digital topography data that can subsequently be entered in an interactive data base in the form of slope, slope length, elevation, and aspect angle. A discussion of the data source and specific descriptions of the data processing software programs are included. In addition, the mathematical considerations involved in the registration of raw digitized coordinate points to the UTM coordinate system are presented. Scale factor considerations are also included. Results of the processing and analysis are illustrated using the Shiprock and Gallup Quadrangle test data.

Junkin, B. G.↗
NASA NTRS1983

An evaluation of Landsat data for input to a state geographic information system

The results of a study to evaluate Landsat digital data, categorized by land cover, for input to the Maryland Automated Geographic Information (MAGI) system, the state georeferenced data base, are presented. Good correspondence is found between the MAGI system and Landsat data for six of seven categories: forest, water, crop/pasture, medium-density residential, low-density residential, and transitional (disturbed land, construction). Discrepancies between the results are found for commercial/industrial/institutional areas which are due to differences in interpretative methodologies, not to deficiencies in either data source. It is concluded that Landsat data are suitable for future Maryland land cover inventories, and can also be used to augment MAGI system data.

Middleton, E. M.↗
NASA NTRS1985

Formulation and implementation of nonstationary adaptive estimation algorithm with applications to air-data reconstruction

The dynamics model and data sources used to perform air-data reconstruction are discussed, as well as the Kalman filter. The need for adaptive determination of the noise statistics of the process is indicated. The filter innovations are presented as a means of developing the adaptive criterion, which is based on the true mean and covariance of the filter innovations. A method for the numerical approximation of the mean and covariance of the filter innovations is presented. The algorithm as developed is applied to air-data reconstruction for the space shuttle, and data obtained from the third landing are presented. To verify the performance of the adaptive algorithm, the reconstruction is also performed using a constant covariance Kalman filter. The results of the reconstructions are compared, and the adaptive algorithm exhibits better performance.

Whitmore, S. A.↗
NASA NTRS1985

Formulation and implementation of nonstationary adaptive estimation algorithm with applications to air-data reconstruction

The dynamics model and data sources used to perform air-data reconstruction are discussed, as well as the Kalman filter. The need for adaptive determination of the noise statistics of the process is indicated. The filter innovations are presented as a means of developing the adaptive criterion, which is based on the true mean and covariance of the filter innovations. A method for the numerical approximation of the mean and covariance of the filter innovations is presented. The algorithm as developed is applied to air-data reconstruction for the Space Shuttle, and data obtained from the third landing are presented. To verify the performance of the adaptive algorithm, the reconstruction is also performed using a constant covariance Kalman filter. The results of the reconstructions are compared, and the adaptive algorithm exhibits better performance.

Whitmore, S. A.↗
NASA NTRS1986

Preparation of satellite soundings for insertion in a variational objective analysis model

The performance of a variational analysis model being developed at the Illinois State Water Survey, which allows blending of satellite and conventional soundings in a way which preserves the information content of both data sources, requires preparation of the input data before insertion into the model. Using operationally retrieved Tiros-N TOVS soundings and rawinsonde data, four procedures to prepare satellite soundings for model insertion are demonstrated: (1) determination and removal of biases, (2) determination of standard errors of the satellite temperatures to assist in the assignment of weights in the model, (3) conversion of layer mean temperatures to level temperatures, and (4) determination of the action necessary for correcting for the nonsynoptic nature of the satellite data.

Kidder, Stanley Q.↗
NASA NTRS1987

Shuttle payload bay thermal environments: Summary and conclusion report for STS Flights 1-5

The thermal data for the payload bay of the first five shuttle flights is summarized and the engineering evaluation of that data is presented. After a general discussion on mission profiles and vehicle configurations, the thermal design and flight instrumentation systems of the payload bay are described. The thermal flight data sources and a categorization of the data are then presented. A thermal flight data summarization section provides temperature data for the five phases of a typical mission profile. These are: prelaunch, ascent, on-orbit, entry and postlanding. The thermal flight data characterization section encompasses this flight data for flight to flight variations, payload effects, temperature ranges, and other variations. Discussion of the thermal environment prediction models in use by industry and various NASA Centers, and the results predicted by these models, is followed by an evaluation of the correlation between the actual flight data and the results predicted by the models. Finally, the available thermal data are evaluated from the viewpoint of the user concerned with establishing the thermal environment in the payload bay. The data deficiencies are discussed and recommendations for their elimination are presented.

Fu, J. H.↗
NASA NTRS1990

Tornadogenesis via squall line and supercell interaction revisited - The 15 November 1989 Huntsville tornado

A case study analyzing the environmental setting and storm system morphology that provides observational evidence of a mechanism involving the interaction of a gust front with a preexisting mesocyclone is presented. This case serves to reemphasize the existence of a high conditional probability of tornado occurrence, given the merger of a gust front (or storm outflow) with a moderate to strong thunderstorm ahead of it. The resultant data serve to illustrate some important unresolved issues relevant to the severe weather warning system that involve the present and planned local warning and network radars, and future algorithms that might intelligently integrate other data sources and models with the radar data.

Goodman, Steven J.↗
NASA NTRS1992

Thermal protection materials: Thermophysical property data

This publication presents a thermophysical property survey on materials that could potentially be used for future spacecraft thermal protection systems (TPS). This includes data that was reported in the 1960's as well as more current information reported through the 1980's. An attempt was made to cite the manufacturers as well as the data source in the bibliography. This volume represents an attempt to provide in a single source a complete set of thermophysical data on a large variety of materials used in spacecraft TPS analysis. The property data is divided into two categories: ablative and reusable. The ablative materials have been compiled into twelve categories that are descriptive of the material composition. An attempt was made to define the Arrhenius equation for each material although this data may not be available for some materials. In a similar manner, char data may not be available for some of the ablative materials. The reusable materials have been divided into three basic categories: thermal protection materials (such as insulators), adhesives, and structural materials.

Williams, S. D.↗
NASA NTRS1995

Data management and scientific integration within the Atmospheric Radiation Measurement Program

The Atmospheric Radiation Measurement (ARM) Program has been developed by the U.S. Department of Energy with the goal to improve the predictive capabilities of General Circulation Models (GCM's) in their treatment of clouds and radiative transfer effects. To achieve this goal, three experimental testbeds were designed for the deployment of instruments that will collect atmospheric data used to drive the GCM's. Each site, known as a Cloud and Radiation Testbed (CART), consists of a highly available, redundant data system for the collection of data from a variety of instrumentation. The first CART site was deployed in April 1992 in the Southern Great Plains (SGP), Lamont, Oklahoma, with the other two sites to follow in September 1995 in the Tropical Western Pacific and in 1997 on the North Slope of Alaska. Approximately 400 MB of data are transferred per day via the Internet from the SGP site to the ARM Experiment Center at Pacific Northwest Laboratory in Richland, Washington. The Experiment Center is central to the ARM data path and provides for the collection, processing, analysis, and delivery of ARM data. Data are received from the CART sites from a variety of instrumentation, observational systems, amd external data sources. The Experiment Center processes these data streams on a continuous basis to provide derived data products to the ARM Science Team in near real-time while providing a three-month running archive of data. A primary requirement of the ARM Program is to preserve and protect all data produced or acquired. This function is performed at Oak Ridge National Laboratory where leading edge technology is employed for the long-term storage of ARM data. The ARM Archive provides access to data for participation outside of the ARM Program. The ARM Program involves a collaborative effort by teams from various DOE National Laboratories, providing multi-disciplinary areas of expertise. This paper will discuss the collaborative methods in which the ARM teams translate the scientific goals of the Program into data products. By combining atmospheric scientists, systems engineers, and software engineers, the ARM Program has successfully designed and developed an environment where advances in understanding the parameterizations of GCM's can be made.

Gracio, Deborah K.↗
NASA NTRS1998

Variations in Atmospheric Water Vapor as Seen in Satellite Data and Model Reanalysis Fields

New data sets used to describe components of the hydrologic and energy cycles of the Earth system are currently being produced and disseminated through the NASA EOS DAACs and several data assimilation centers supported by such organizations as NASA and NOAA. These data sets incorporate hybrid data analysis schemes and portray satellite and radiosonde data combined in a diagnostic sense and in a forecast mode. There is a need to develop a better understanding of the accuracy and utility of these global, relatively long-term, datasets to describe components of the hydrologic cycle and to understand atmospheric moisture variability and its relation to climatological significant events Much progress has been made in the last ten years in the development of global atmospheric models and analysis of satellite data for global studies. The atmospheric models have improved in their ability to predict both short term and longer term weather events. This has been possible through better understanding of atmosphere dynamics and very rapid advances in computer technology. Over the same period, data assimilation methods have advanced and unconventional data sources such as aircraft and satellite data, drifting buoys, etc., can be assimilated at non-synaptic times. As a result of these improvements, comprehensive global atmospheric fields based on four-dimensional data assimilation methods now provide one of the most reliable methods for studying dynamical and physical behavior in the atmosphere.

Jedlovec, Gary J.↗
NASA NTRS2007

A Gateway to Support Interoperability of OPeNDAP and OGC Protocols

Data access and analysis tools that are developed within specific disciplines and the protocols that they are built upon provide valuable services to their respective users but can actually be a barrier to the interation of data from a broad set of data sources. An example of this is data supported by OPeNDAP that is widely used in the ocean and atmospheric sciences, and data provided through the interface specifications of the Open Geospatial Consortium (OGC) that typically serves the land science community. This paper described a project that is developing a gateway to bridge these two data system infrastructures, in response to a specific need expressed by CEOP, an international science program.

McDonald, Kenneth↗
NASA NTRS2010

Centralized Alert-Processing and Asset Planning for Sensorwebs

A software program provides a Sensorweb architecture for alert-processing, event detection, asset allocation and planning, and visualization. It automatically tasks and re-tasks various types of assets such as satellites and robotic vehicles in response to alerts (fire, weather) extracted from various data sources, including low-level Webcam data. JPL has adapted cons iderable Sensorweb infrastructure that had been previously applied to NASA Earth Science applications. This NASA Earth Science Sensorweb has been in operational use since 2003, and has proven reliability of the Sensorweb technologies for robust event detection and autonomous response using space and ground assets. Unique features of the software include flexibility to a range of detection and tasking methods including those that require aggregation of data over spatial and temporal ranges, generality of the response structure to represent and implement a range of response campaigns, and the ability to respond rapidly.

Castano, Rebecca↗
NASA NTRS2012

The NASA Tournament Laboratory (NTL): Improving Data Access at PDS while Spreading Joy and Engaging Students through 16 Micro-Contests

NASA PDS hosts terabytes of valuable data from hundreds of data sources and spans decades of research. Data is stored on flat-file systems regulated through careful meta dictionaries. PDS's data is available to the public through its website which supports data searches through drill-down navigation. While the system returns data quickly, result sets in response to identical input differ depending on the drill-down path a user follows. To correct this Issue, to allow custom searching, and to improve general accessibility, PDS sought to create a new data structure and API, and to use them to build applications that are a joy to use and showcase the value of the data to students, teachers and citizens. PDS engaged TopCoder and Harvard Business School through the NTL to pursue these objectives in a pilot effort. Scope was limited to Small Bodies Node data. NTL analyzed data, proposed a solution, and implemented it through a series of micro-contests. Contest focused on different segments of the problem; conceptualization, architectural design, implementation, testing, etc. To demonstrate the utility of the completed solution, NTL developed web-based and mobile applications that can compare targets, regardless of mission. To further explore the potential of the solution NTL hosted "Mash-up" challenges that integrated the API with other publically available assets, to produce consumer and teaching applications, including an Augmented Reality iPad tool. Two contests were also posted to middle and high school students via the NoNameSite.com platform, and as a result of these contests, PDS/SBN has initiated a Facebook program. These contests defined and implemented a data warehouse with the necessary migration tools to transform legacy data, produced a public web interface for the new search, developed a public API, and produced four mobile applications that we expect to appeal to users both within and, without the academic community.

LaMora, Andy↗
NASA NTRS2011

The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

Whiteman, David N.↗