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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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NASA NTRS1995

Tests and consequences of disk plus halo models of gamma-ray burst sources

The gamma-ray burst observations made by the Burst and Transient Source Experiment (BATSE) and by previous experiments are still consistent with a combined Galactic disk (or Galactic spiral arm) plus extended Galactic halo model. Testable predictions and consequences of the disk plus halo model are discussed here; tests performed on the expanded BATSE database in the future will constrain the allowed model parameters and may eventually rule out the disk plus halo model. Using examples, it is shown that if the halo has an appropriate edge, BATSE will never detect an anisotropic signal from the halo of the Andromeda galaxy. A prediction of the disk plus halo model is that the fraction of the bursts observed to be in the 'disk' population rises as the detector sensitivity improves. A careful reexamination of the numbers of bursts in the two populations for the pre-BATSE databases could rule out this class of models. Similarly, it is predicted that different satellites will observe different relative numbers of bursts in the two classes for any model in which there are two different spatial distribiutions of the sources, or for models in which there is one spatial distribution of the sources that is sampled to different depths for the two classes. An important consequence of the disk plus halo model is that for the birthrate of the halo sources to be small compared to the birthrate of the disk sources, it is necessary for the halo sources to release many orders of magnitude more energy over their bursting lifetime than the disk sources. The halo bursts must also be much more luminous than the disk bursts; if this disk-halo model is correct, it is necessary to explain why the disk sources do not produce halo-type bursts.

Smith, I. A.↗
NASA NTRS2008

Exploiting Satellite Remote-Sensing Data in Fine Particulate Matter Characterization for Serving the Environmental Public Health Tracking Network (EPHTN): The HELIX-Atlanta Experience and NPOESS Implications

As part of the U.S. National Environmental Public Health Tracking Network (EPHTN), the National Center for Environmental Health (NCEH) at the U.S. Centers for Disease Control and Prevention (CDC) led a project in collaboration with the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) called Health and Environment Linked for Information Exchange (HELIX-Atlanta). Under HELIX-Atlanta, pilot projects were conducted to develop methods to better characterize exposure; link health and environmental datasets; and analyze spatial/temporal relationships. This paper describes and demonstrates different techniques for surfacing daily environmental hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM(sub 2.5) for the purpose of integrating respiratory health and environmental data for the CDC's pilot study of HELIX-Atlanta. It describes a methodology for estimating ground-level continuous PM(sub 2.5) concentrations using spatial surfacing techniques and leveraging NASA Moderate Resolution Imaging Spectrometer (MODIS) data to complement the U.S. Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM(sub 2.5) from the EPA database for the year 2003 as well as PM(sub 2.5) estimates derived from NASA's MODIS data. Hazard data have been processed to derive the surrogate exposure PM(sub 2.5) estimates. The paper has shown that merging MODIS remote sensing data with surface observations of PM(sub 2.5), may provide a more complete daily representation of PM(sub 2.5), than either data set alone would allow, and can reduce the errors in the PM(sub 2.5) estimated surfaces. Future work in this area should focus on combining MODIS column measurements with profile information provided by satellites like the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The Visible Infrared Imager/Radiometer Suite (VIIRS) and the Aerosol Polarimeter Sensor (APS) NPOESS sensors will provide first-order information on aerosol particle size and are anticipated to provide information on aerosol products at higher resolution and accuracy than MODIS. Use of the NPOESS remote sensing data should result in more robust remotely sensed data that can be coupled with the methods discussed in this paper to generate surface concentrations of PM(2.5) for linkage with health data in Environmental Public Health Tracking.

Al-Hamdan, Mohammad Z.↗
NASA NTRS2012

Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

Bedka, Kristopher M.↗
NASA NTRS2000

Supporting NASA Facilities Through GIS

The NASA GIS Team supports NASA facilities and partners in the analysis of spatial data. Geographic Information System (G[S) is an integration of computer hardware, software, and personnel linking topographic, demographic, utility, facility, image, and other geo-referenced data. The system provides a graphic interface to relational databases and supports decision making processes such as planning, design, maintenance and repair, and emergency response.

Ingham, Mary E.↗
NASA NTRS2012

Mixing of Dust and NH3 Observed Globally over Anthropogenic Dust Sources

The global distribution of dust column burden derived from MODIS Deep Blue aerosol products is compared to NH3 column burden retrieved from IASI infrared spectra. We found similarities in their spatial distributions, in particular their hot spots are often collocated over croplands and to a lesser extent pastures. Globally, we found 22% of dust burden collocated with NH3, with only 1% difference between land-use databases. This confirms the importance of anthropogenic dust from agriculture. Regionally, the Indian subcontinent has the highest amount of dust mixed with NH3 (26 %), mostly over cropland and during the pre-monsoon season. North Africa represents 50% of total dust burden but accounts for only 4% of mixed dust, which is found over croplands and pastures in Sahel and the coastal region of the Mediterranean. In order to evaluate the radiative effect of this mixing on dust optical properties, we derive the mass extinction efficiency for various mixtures of dust and NH3, using AERONET sunphotometers data. We found that for dusty days the coarse mode mass extinction efficiency decreases from 0.62 to 0.48 square meters per gram as NH3 burden increases from 0 to 40 milligrams per square meter. The fine mode extinction efficiency, ranging from 4 to 16 square mters per gram, does not appear to depend on NH3 concentration or relative humidity but rather on mineralogical composition and mixing with other aerosols. Our results imply that a significant amount of dust is already mixed with ammonium salt before its long range transport. This in turn will affect dust lifetime, and its interactions with radiation and cloud properties

dust sources↗
NASA NTRSDate not supplied

A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations

Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.

Radiation↗
NASA NTRS1995

A Note on the Barotropic Response of Sea Level to Time-Dependent Wind Forcing

This study examines the extent to which sea level variations at periods between 30 days and 1 year and spatial scales greater than 1000 km can be described by the wind- driven linear barotropic vorticity dynamics. The TOPEX/POSEIDON altimetric observations of sea level and the wind products of the National Meteorological Center are used as the database for the study. Each term of the linear barotropic vorticity equation was evaluated by averaging over regions of 10 deg x 10 deg. In most of the open ocean the result of the analysis suggests that the sea level variabilities at the scales considered cannot be fully described by the equation; the apparent net vorticity change is more than what can be explained by the local wind stress curl. In the few regions where the wind stress curl is strong enough to balance the vorticity budget, predominantly in the northeast Pacific and the southeast Pacific, the balance is basically achieved in terms of the time-dependent topographic Sverdrup relation, namely, the balance between the advection of the planetary vorticity plus the topography-induced vorticity and the forcing by the wind stress curl.

Fu, Lee-Lueng↗
NASA NTRS2005

Transferable Calibration Standard Developed for Quantitative Raman Scattering Diagnostics in High-Pressure Flames

Researchers from NASA Glenn Research Center s Combustion Branch and the Ohio Aerospace Institute (OAI) have developed a transferable calibration standard for an optical technique called spontaneous Raman scattering (SRS) in high-pressure flames. SRS is perhaps the only technique that provides spatially and temporally resolved, simultaneous multiscalar measurements in turbulent flames. Such measurements are critical for the validation of numerical models of combustion. This study has been a combined experimental and theoretical effort to develop a spectral calibration database for multiscalar diagnostics using SRS in high-pressure flames. However, in the past such measurements have used a one-of-a-kind experimental setup and a setup-dependent calibration procedure to empirically account for spectral interferences, or crosstalk, among the major species of interest. Such calibration procedures, being non-transferable, are prohibitively expensive to duplicate. A goal of this effort is to provide an SRS calibration database using transferable standards that can be implemented widely by other researchers for both atmospheric-pressure and high-pressure (less than 30 atm) SRS studies. A secondary goal of this effort is to provide quantitative multiscalar diagnostics in high pressure environments to validate computational combustion codes.

Nguyen, Quang-Viet↗
NASA NTRS2007

The EPIC-MOS Particle-Induced Background Spectra

In order to analyse diffuse emission that fills the field of view, one must accurately characterize the instrumental backgrounds. For the XMM-Newton EPIC instrument these backgrounds include a temporally variable "quiescent" component. as well as the strongly variable soft proton contamination. We have characterized the spectral and spatial response of the EPIC detectors to these background components and have developed tools to remove these backgrounds from observations. The "quiescent" component was characterized using a combination of the filter-wheel-closed data and a database of unexposed-region data. The soft proton contamination was characterized by differencing images and spectra taken during flared and flare-free intervals. After application of our modeled backgrounds, the differences between independent observations of the same region of "blank sky" are consistent with the statistical uncertainties except when there is clear spectral evidence of solar wind charge exchange emission. Using a large sample of blank sky data, we show that strong magnetospheric SWCX emission requires elevated solar wind fluxes; observations through the densest part of the magnetosheath are not necessarily strongly contaminated with SWCX emission.

Kuntz, K. D.↗
NASA NTRS2018

An Overview of Mesoscale Aerosol Processes, Comparisons, and Validation Studies from DRAGON Networks

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

Holben, Brent N.↗
NASA NTRS2000

Implications from Near-Shoemaker Imaging of Eros for Small-Scale Structure and Surface Sampling

What we know about asteroids has always been bifurcated by the enormous gap between astronomical studies of small, distant bodies, and the close-up laboratory measurements of hand-sample sized meteorites. The gulf has been narrowed somewhat by improvements in Earth-based astronomical techniques (e.g. Hubble Space Telescope, radar, adaptive optics) and especially by spacecraft fly-bys of asteroids. But the Near Earth Asteroid Rendezvous (NEAR)-Shoemaker mission has gone considerably more in the direction of bridging the gap. Any consideration of intelligent sample-return from an asteroid must be based on the best possible knowledge of the asteroid at the spatial scales pertinent to operations at the asteroid and of the sample/s. Otherwise, we are in danger of succumbing to the 'Martian Horror Story' that Bruce Murray, in the 1960's, envisioned might impair our exploration of the surface of the red planet if we tried to land on it without first bolstering the information content of our database about Mars, especially at high resolutions. NEAR-Shoemaker is helping to bridge that gap in the case of Eros. The best resolution obtained by the Galileo spacecraft on Ida was 25 m/pixel. As of this writing, NEAR has already obtained images with resolutions at least five times better (information content 25 times better) and vastly better images may be available at the time of this Workshop from the late October low flyby. Already, we are seeing that the Martian horror story looks tame compared with Eros. Everywhere we have landed on Mars, the surface has been covered with rocks and boulders, with much higher spatial coverage than seen anywhere on the lunar surface. We have, in fact, been rather lucky that none of our Martian landers have tipped over so far, and there were justified fears in the early aftermath of last year's failure of Mars Polar Lander that it had suffered from inadequate high-resolution characterization of polar regions on Mars (the failure is now known to have had another cause). Eros looks potentially even more terrifying. Additional information is contained in the original extended abstract.

Chapman, C. R.↗
NASA NTRS2010

ICESat Lidar and Global Digital Elevation Models: Application to DESDynI

Geodetic control is extremely important in the production and quality control of topographic data sets, enabling elevation results to be referenced to an absolute vertical datum. Global topographic data with improved geodetic accuracy achieved using global Ground Control Point (GCP) databases enable more accurate characterization of land topography and its change related to solid Earth processes, natural hazards and climate change. The multiple-beam lidar instrument that will be part of the NASA Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission will provide a comprehensive, global data set that can be used for geodetic control purposes. Here we illustrate that potential using data acquired by NASA's Ice, Cloud and land Elevation Satellite (ICEsat) that has acquired single-beam, globally distributed laser altimeter profiles (+/-86deg) since February of 2003 [1, 2]. The profiles provide a consistently referenced elevation data set with unprecedented accuracy and quantified measurement errors that can be used to generate GCPs with sub-decimeter vertical accuracy and better than 10 m horizontal accuracy. Like the planned capability for DESDynI, ICESat records a waveform that is the elevation distribution of energy reflected within the laser footprint from vegetation, where present, and the ground where illuminated through gaps in any vegetation cover [3]. The waveform enables assessment of Digital Elevation Models (DEMs) with respect to the highest, centroid, and lowest elevations observed by ICESat and in some cases with respect to the ground identified beneath vegetation cover. Using the ICESat altimetry data we are developing a comprehensive database of consistent, global, geodetic ground control that will enhance the quality of a variety of regional to global DEMs. Here we illustrate the accuracy assessment of the Shuttle Radar Topography Mission (SRTM) DEM produced for Australia, documenting spatially varying elevation biases of several meters in magnitude.

Carabajal, Claudia C.↗
NASA NTRS2021

The Large Footprint of Small-scale Artisanal Gold Mining in Ghana

Gold mining has played a significant role in Ghana's economy for centuries. Regulation of this industry has varied over time and while industrial mining is prevalent in the country, the expansion of artisanal mining, or Galamsey has escalated in recent years. Many of these artisanal mines are not only harmful to human health due to the use of Mercury (Hg) in the amalgamation process, but also leave a significant footprint on terrestrial ecosystems, degrading and destroying forested ecosystems in the region. In this study, the Landsat image archive available through Google Earth Engine was used to quantify the total footprint of vegetation loss due to artisanal goldmines in Ghana from 2005 to 2019 and understand how conversion of forested regions to mining has changed over a decadal period from 2007 to 2017. A combination of machine learning and change detection algorithms were used to calculate different land cover conversions and the timing of conversion annually. Within the study area of southwestern Ghana, our results indicate that approximately 47,000 ha (⨦2218 ha) of vegetation were converted to mining at an average rate of ~2600 ha yr−1. The results indicate that a high percentage(~50%) of this mining occurred between 2014 and 2017. Around 700 ha of this mining occurred within protected areas as mapped by the World Database of Protected Areas. In addition to deforestation, increased artisanal mining activity in recent years has the potential to affect human health, access to drinking water resources and food security. This work expands upon limited research into the spatial footprint of Galamseyin Ghana, complements mapping efforts by local geographers, and will support efforts by the government of Ghana to monitor deforestation caused by artisanal mining.

Abigail Barenblitt↗
NASA NTRS1990

Rapid traversal of an image database using binary synthetic discriminant filters

Pattern recognition invariant to image rotations of up to 75 deg, using a single filter, has been demonstrated for binary synthetic discriminant function (BSDF) optical filters, suggesting their use in directed graph-arranged data bases which can be rapidly traversed by means of a filter-plane programmable spatial light modulator (SLM). The filter data base is arranged as a tree structure in which the root node filters are invariant to over 60 deg rotation, while the leaves are 5-deg invariant. Results are presented from experiments with BSDFs designed to recognize in-plane-rotated views of a Space Shuttle Orbiter. Using a magnetooptic SLM that is driven at 350 Hz in the filter plane, orientation identifications requiring less than 30 msec have been achieved after sequencing through only 10 BSDFs.

Reid, Max B.↗
NASA NTRS1995

Finding the forest in the trees: The challenge of combining diverse environmental data

It has become increasingly important to conduct interdisciplinary environmental research assessments, both nationally and internationally. For this reason, the Committee for a Pilot Study on Database Interfaces was charged to review and advise on data interfacing activities. The committee used six case studies (1) to identify and understand the most important problems associated with collecting, integrating, and analyzing environmental data from local to global spatial scales and over a very wide range of temporal scales; and (2) to elaborate the common barriers to interfacing data of disparate sources and types. Consistent with the committee's charge, the primary focus was the interfacing of geophysical and ecological data. The case studies used by the committee were: The Impact Assessment Project for Drought Early Warning in the Sahel, The National Acid Precipitation Assessment Program, The H.J. Andrew Experimental Forest Long-Term Ecological Research Site, The Carbon Dioxide Information Analysis Center, The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment, and The California Cooperative Oceanic Fisheries Investigation. The committee derived a number of lessons from the case studies, and these lessons are summarized at the end of each case study and analyzed in the last chapter. Some are generic in nature; others are more specific to a discipline or project. The conclusions and recommendations are based on the committee's analysis of the case studies and additional research. They are organized according to four major areas of barriers or challenges to the effective interfacing of diverse environmental data. In the final section the committee offers a set of broadly applicable principles (Ten Keys to Success) that can be used by scientists and data managers in planning and conducting interfacing activities.

Source record↗
NASA NTRS2018

The Sensitivity of US Wildfire Occurrence to Pre-Season Soil Moisture Conditions Across Ecosystems

It is well accepted that drought and low moisture conditions are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state has been challenging due to a lack of soil moisture observations at an appropriate spatial scale. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission, combined in a predictive algorithm with the US Forest Service’s Fire-Occurrence Database. We estimate a relationship between historic surface moisture and wildfire occurrence to produce annual probable wildfire occurrence and burned area at 0.25-degree resolution for the contiguous United States by land-cover classification. Cross-validation indicates increased frequency of smaller fires when the months preceding fire season are wet, while larger fires are more frequent when soils are dry. This demonstrates that assimilated GRACE data holds information that could aid national-scale fire potential assessments for early decision-support.

Fire-Occurrence database↗
NASA NTRS1988

Studying Turbulence Using Numerical Simulation Databases, 2. Proceedings of the 1988 Summer Program

The focus of the program was on the use of direct numerical simulations of turbulent flow for study of turbulence physics and modeling. A special interest was placed on turbulent mixing layers. The required data for these investigations were generated from four newly developed codes for simulation of time and spatially developing incompressible and compressible mixing layers. Also of interest were the structure of wall bounded turbulent and transitional flows, evaluation of diagnostic techniques for detection of organized motions, energy transfer in isotropic turbulence, optical propagation through turbulent media, and detailed analysis of the interaction of vortical structures.

Source record↗
NASA NTRSDate not supplied

Generation of Continental Scale Percent Tree Cover Product Using Deep-learning and Multi-scale Remote Sensing Data

Spatially explicit percent tree cover (TC) estimation is critical for mapping forest aboveground biomass and its dynamics. While various TC products have been developed, there has not been a generalized framework that can be applied to diverse terrestrial ecosystems due to underlain extreme complexities. Deep learning algorithms can learn a spatial pattern and radiometric characteristics of tree canopy as a robust approximation of physical or empirical models, and thus have emerged as promising and efficient tools for large-scale TC mapping. In this study, we synergistically use very high-resolution aerial imageries (National Agriculture Imagery Program, NAIP) and medium resolution Landsat data to map continental-scale TC (CONUS and Mexico) through a hierarchical deep learning approach (Convolutional Neural Network), i.e., NAIP TC generated from a NAIP model is utilized to train a Landsat model. The produced TC product (hereafter, NEX-TC) is able to capture the spatial pattern of TC distribution and its changes driven by natural disturbance and human land management. We further explore and analyze the reliability and potential uncertainty of the NEX-TC by comparing it to lidar- (lidar-TC), National Land Cover Database (NLCD-TC), and MODIS Vegetation Continuous Field (MODIS-TC). This evaluation practice reveals that TC products based on passive optical sensors tend to underestimate TC across all land cover types while Landsat-based TCs (i.e., NEX-TC & NLCD-TC) perform better than the coarser MODIS TC estimate. Our results show that the NEX-TC is generally comparable to NLCD-TC but it particularly outperforms NLCD-TC and MODIS-TC over the dense forests where lidar-TC indicates >80% TC. These results indicate that our hierarchical deep learning approach and TC product will be effective and useful for characterizing large-scale tree cover and possibly associated carbon dynamics.

Landsat↗