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At least 289 records · Page 16

Gridded Hourly Text Products: A TRMM Data Reduction Approach

The quantity of precipitation data from satellite-based observations is a blessing and a curse. The sheer volume of the data makes it difficult for many researchers to use in targeted applications. This volume increases further as algorithm improvements lead to the reprocessing of mission data. In addition to the overall volume of data, the size and format complexity of orbital granules contribute to the difficulty in using all the available data. Finally, the number of different instruments available to measure rainfall and related parameters further contributes to the volume concerns. In summary, we have an embarrassment of riches. The science team of the Tropical Rainfall Measuring Mission (TRMM) recognized this dilemma and has developed a strategy to address it. The TRMM Science Data and Information System (TSDIS) produces, at the direction of the Joint TRMM Science Team, a number of instantaneous rainfall products. The TRMM Microwave Imager (TMI), the Precipitation Radar and a Combined TMI/PR are the key "instruments" used in this production. Each of these products contains an entire orbit of data. The algorithm code computes not just rain rates but a large number of other physical parameters as well as information needed for monitoring algorithm performance. That makes these products very large. For example, a single orbit of TMI rain rate product is 99 MB, a single orbit of the combined product yields a granule that is 158 MB, while the 80 vertical levels of rain information from the PR yields an orbital product of 253 MB. These are large products that are often difficult for science users to electronically transfer to their sites especially if they want a large period of time. Level 3 gridded products are much smaller, but their 5 or 30 day temporal resolution is insufficient for many researchers. In addition, TRMM standard products are produced in the HDF format. While a large number of user-friendly tools are available to hide the details of the format (including a toolkit developed at TSDIS for the TRMM science team), many potential users shy away

Stocker, Erich↗

Physical state of interstellar atoms

Brief survey of the physical conditions along the lines of sight to reddened and unreddened stars, as determined from Copernicus observation of interstellar lines between 95 and 300 nm. Differences in ionization structure and density between clouds and the local intercloud medium are discussed. Some new data for beta Centauri is used to supplement the previously available data.

York, D. G.↗

Evidence for long-term variability in the ultra high energy photon flux from Cygnus X-3

A time-correlation analysis of atmospheric Cerenkov pulses by a wide-angle photomultiplier system was previously shown to have present in it a nonrandom component which seemed associated with the Right Ascension (RA) range approx. 20+or-04h. A recent examination of multi-muon events recorded by a photon-decay detector shows a similar time-dependent effect, closely matching the previous results, supporting the suggestion that the effect is of cosmic origin. However, even though Cyg. X-3 lies well inside the region of peak intensity, it does not seem possible to ascribe to it the whole effect, for the implied photon flux appears too large to be reconciled to various gamma-ray measurements of Cyg. X-3. The original data were subjected to a phase-histogram analysis and it as found that only 2.5% of overall recorded data are compatible with a phase-dependent emission from Cyg. X-3. Assuming these events to be gamma rays yields a detected flux of (2.6 + or - 0.3) x 10 to the minus 12th power gamma cm -2s-1 above 5 x 10 to the 14th power eV. Comparing this value with more recent ultra high energy (UHE) photon data from the same source, it is suggested that the available data generally favor a long-term reduction in the Cyg. X-3 inferred luminosity ( 10 to the 13th power eV) by a factor of (1.8 + or - 0.3) per year.

Bhat, C. L.↗

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

VandeVen, C.↗

Aviation Data Integration System

During the analysis of flight data and safety reports done in ASAP and FOQA programs, airline personnel are not able to access relevant aviation data for a variety of reasons. We have developed the Aviation Data Integration System (ADIS), a software system that provides integrated heterogeneous data to support safety analysis. Types of data available in ADIS include weather, D-ATIS, RVR, radar data, and Jeppesen charts, and flight data. We developed three versions of ADIS to support airlines. The first version has been developed to support ASAP teams. A second version supports FOQA teams, and it integrates aviation data with flight data while keeping identification information inaccessible. Finally, we developed a prototype that demonstrates the integration of aviation data into flight data analysis programs. The initial feedback from airlines is that ADIS is very useful in FOQA and ASAP analysis.

Kulkarni, Deepak↗

Russian-US Partnership to Study the 23-km-diameter El'gygtgyn Impact Crater, Northeast Russia

El'gygytgyn crater, located within Eastern Siberia, is a Pliocene-aged (3.6 Ma), well-preserved impact crater with a rim diameter of roughly 23 km. The target rocks are a coherent assemblage of crystalline rocks ranging from andesite to basalt. At the time of impact the region was forested and the Arctic Ocean was nearly ice-free. A 15-km lake fills the center of the feature and water depths are approximately 175 m. Evidence of shock metamorphism, -- including coesite, fused mineral glasses, and planar deformation features in quartz -- has been reported. This feature is one of the youngest and best preserved complex craters on Earth. Because of its remote Arctic setting, however, El gygytgyn crater remains poorly investigated. The objectives of this three-year project are to establish and maintain a research partnership between scientists from Russia and the United States interested in the El gygytgyn crater. The principal institutions in the U.S. will be the Geophysical Institute, University of Alaska Fairbanks and the University of Massachusetts Amherst. The principal institution in Russia will be the North East Interdisciplinary Scientific Research Institute (NEISRI), which is the Far-East Branch of the Russian Academy of Science. Three science tasks are identified for the exchange program: (1) Evaluate impactite samples collected during previous field excursions for evidence of and level of shock deformation. (2) Build a high-resolution digital elevation model for the crater and its surroundings using interferometric synthetic aperture radar techniques on JERS-1, ERS-1, ERS-2, and/or RadarSat range-doppler data. (3) Gather all existing surface data available from Russian and U.S. institutions (DEM, remote sensing image data, field-based lithological and sample maps, and existing geophysical data) and assemble into a Geographic Information Systems database.

Sharpton, Virgil L.↗

NASA Software Estimating Tool (N-SET)

The goals of this project are to: Develop an early lifecycle software cost estimation tool leveraging existing data and capabilities Collect additional software data from: a) Jet Propulsion Laboratory; b) Goddard Space Flight Center; and c) Marshall Space Flight Center. Analyze, normalize, evaluate, stratify, and validate data. Create a calibrated, validated, and documented tool initially using available data and subsequently using newly collected data.

cost estimating tools↗

Application of Machine Learning to Rotorcraft Health Monitoring

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

machine learning↗

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers, and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Carl Malings↗

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Nathan R. Pavlovic↗

Hypersonic Turbulent Boundary-Layer and Free Sheer Database Datasets

A critical assessment and compilation of data are presented on attached hypersonic turbulent boundary layers in pressure gradients and compressible turbulent mixing layers. Extensive searches were conducted to identify candidate experiments, which were subjected to a rigorous set of acceptance criteria. Accepted datasets are both tabulated and provided in machine-readable form. The purpose of this database effort is to make existing high quality data available in detailed form for the turbulence-modeling and computational fluid dynamics communities. While significant recent data were found on the subject of compressible turbulent mixing, the available boundary-layer/pressure-gradient experiments are all older ones of which no acceptable data were found at hypersonic Mach numbers.

Settles, Gary S.↗

Solid rocket booster performance evaluation model. Volume 1: Engineering description

The space shuttle solid rocket booster performance evaluation model (SRB-II) is made up of analytical and functional simulation techniques linked together so that a single pass through the model will predict the performance of the propulsion elements of a space shuttle solid rocket booster. The available options allow the user to predict static test performance, predict nominal and off nominal flight performance, and reconstruct actual flight and static test performance. Options selected by the user are dependent on the data available. These can include data derived from theoretical analysis, small scale motor test data, large motor test data and motor configuration data. The user has several options for output format that include print, cards, tape and plots. Output includes all major performance parameters (Isp, thrust, flowrate, mass accounting and operating pressures) as a function of time as well as calculated single point performance data. The engineering description of SRB-II discusses the engineering and programming fundamentals used, the function of each module, and the limitations of each module.

Source record↗

Development of Digital Twin Technologies for Climate Projections

Climate projections are increasingly needed for adaptation, climate resilience and related decision making. However, existing projections have systematic biases, are limited in scope, and are not readily available for most potential users. While the ideal of an observational data-driven ‘digital twin’ for climate is initially attractive, there is only a very limited set of climate data available with which to train such a tool. Nonetheless, we are confident that there is a role for ‘digital twin technologies’ in removing biases, increasing computational efficiency, expanding scenarios and data accessibility.

digital twins↗

A study of boundary layer transition on outgassing cones in hypersonic flow

Surface heat-transfer rates and pressures were measured at hypersonic speeds on sharp cones at zero angle of attack with and without gas injection. Using the non-injection results for reference data the effects on heating and transition location of surface roughness and injectant rate, distribution and composition were determined. The transition location was sensitive to the injectant distribution. The transition Reynolds numbers were significantly greater when the injectant distribution was constant than with a variable distribution. The measured heat-transfer distribution were also strongly dependent upon the injectant distribution. Transition Reynolds number results obtained during this program with a variable injectant distribution were correlated with a limited amount of data available for a degrading model tested in a different facility. Transitional data with constant injectant distribution were correlated with earlier results. An empirical correlation of heat-transfer reduction due to gas injection in turbulent flow was developed for both distributions tested. Several effects of mass addition on heating and transition, which have been earlier reported, were observed.

Stalmach, C. J., Jr.↗

Comparison of techniques for determination of boundary layer transition in shock wave induced flows

Three methods of determining transition times in shock wave-induced boundary layers are compared. Experimental transition data for these comparisons were obtained in two different shock tube facilities for shock wave Mach numbers from 3.0 to 5.5. Bias in determining transition times by the conventional thin-film temperature history and difficulty in reading schlieren photographs suggest the use of a new heat-flux technique for determining transition. It is suggested that the heat-flux technique be used when possible, because of better sensitivity and a view of the entire transition process and because it reveals important information concerning departures from theoretical laminar boundary-layer development. Transition results presented extend the range of data available in the literature and are in good agreement with existing data through transition Reynolds numbers of 1,000,000.

Hall, J. L.↗

Data base management study

Data base management techniques and applicable equipment are described. Recommendations which will assist potential NASA data users in selecting and using appropriate data base management tools and techniques are presented. Classes of currently available data processing equipment ranging from basic terminals to large minicomputer systems were surveyed as they apply to the needs of potential SEASAT data users. Cost and capabilities projections for this equipment through 1985 were presented. A test of a typical data base management system was described, as well as the results of this test and recommendations to assist potential users in determining when such a system is appropriate for their needs. The representative system tested was UNIVAC's DMS 1100.

Source record↗

User's guide to the Nimbus-4 backscatter ultraviolet experiment data sets

The first year's data from the Nimbus 4 backscatter ultraviolet (BUV) experiment have been archived in the National Space Science Data Center (NSSDC). Backscattered radiances in the ultraviolet measured by the satellite were used to compute the global total ozone for the period April 1970 - April 1971. The data sets now in the NSSDC are the results obtained by the Ozone Processing Team, which has processed the data with the purpose of determining the best quality of the data. There are four basic sets of data available in the NSSDC representing various stages in processing. The primary data base contains organized and cleaned data in telemetry units. The radiance data has had most of the engineering calibrations performed. The detailed total ozone data is the result of computations to obtain the total ozone; the Compressed Total Ozone data is a convenient condensation of the detailed total ozone. Product data sets are also included.

Lowrey, B. E.↗