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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Stream network analysis from orbital and suborbital imagery, Colorado River Basin, Texas

The author has identified the following significant results. Orbital SL-2 imagery (earth terrain camera S-190B), received September 5, 1973, was subjected to quantitative network analysis and compared to 7.5 minute topographic mapping (scale: 1/24,000) and U.S.D.A. conventional black and white aerial photography (scale: 1/22,200). Results can only be considered suggestive because detail on the SL-2 imagery was badly obscured by heavy cloud cover. The upper Bee Creek basin was chosen for analysis because it appeared in a relatively cloud-free portion of the orbital imagery. Drainage maps were drawn from the three sources digitized into a computer-compatible format, and analyzed by the WATER system computer program. Even at its small scale (1/172,000) and with bad haze the orbital photo showed much drainage detail. The contour-like character of the Glen Rose Formation's resistant limestone units allowed channel definition. The errors in pattern recognition can be attributed to local areas of dense vegetation and to other areas of very high albedo caused by surficial exposure of caliche. The latter effect caused particular difficulty in the determination of drainage divides.

Baker, V. R.↗
NASA NTRS2015

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = −0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Soil MOisture↗
NASA NTRS2017

Antarctic Ice Shelf Potentially Stabilized by Export of Meltwater in Surface River

Meltwater stored in ponds and crevasses can weaken and fracture ice shelves, triggering their rapid disintegration. This ice-shelf collapse results in an increased flux of ice from adjacent glaciers and ice streams, thereby raising sea level globally. However, surface rivers forming on ice shelves could potentially export stored meltwater and prevent its destructive effects. Here we present evidence for persistent active drainage networks-interconnected streams, ponds and rivers-on the Nansen Ice Shelf in Antarctica that export a large fraction of the ice shelf's meltwater into the ocean. We find that active drainage has exported water off the ice surface through waterfalls and dolines for more than a century. The surface river terminates in a 130-metre-wide waterfall that can export the entire annual surface melt over the course of seven days. During warmer melt seasons, these drainage networks adapt to changing environmental conditions by remaining active for longer and exporting more water. Similar networks are present on the ice shelf in front of Petermann Glacier, Greenland, but other systems, such as on the Larsen C and Amery Ice Shelves, retain surface water at present. The underlying reasons for export versus retention remain unclear. Nonetheless our results suggest that, in a future warming climate, surface rivers could export melt off the large ice shelves surrounding Antarctica-contrary to present Antarctic ice-sheet models, which assume that meltwater is stored on the ice surface where it triggers ice-shelf disintegration.

Bell, Robin E.↗
NASA NTRS2016

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

The purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product quality in various land data assimilation systems.

NLDAS-2↗
NASA NTRS2023

Explainable deep learning for insights in El Niño and river flows

The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interannual variability in regional hydrology across the world through long-range dependence or teleconnections. Recent research has demonstrated the value of Deep Learning (DL) methods for improving ENSO prediction as well as Complex Networks (CN) for understanding teleconnections. However, gaps in predictive understanding of ENSO-driven river flows include the black box nature of DL, the use of simple ENSO indices to describe a complex phenomenon and translating DL-based ENSO predictions to river flow predictions. Here we show that eXplainable DL (XDL) methods, based on saliency maps, can extract interpretable predictive information contained in global SST and discover SST information regions and dependence structures relevant for river flows which, in tandem with climate network constructions, enable improved predictive understanding. Our results reveal additional information content in global SST beyond ENSO indices, develop understanding of how SSTs influence river flows, and generate improved river flow prediction, including uncertainty estimation. Observations, reanalysis data, and earth system model simulations are used to demonstrate the value of the XDL-CN based methods for future interannual and decadal scale climate projections.

SST↗
NASA NTRS2019

A Joint Analysis of GPS Displacement and GRACE Geopotential Data for Simultaneous Estimation of Geocenter Motion and Gravitational Field

Gravitational potential data from GRACE are being used to study mass redistribution within and between the atmosphere, hydrosphere, cryosphere, and solid Earth. The GRACE data are made available in a reference frame with its origin at the center of mass of the Earth system (geocenter) while many other geophysical models and data sets refer to a reference frame attached to the Earth's surface. Changes in the offset between these reference frames (geocenter motion) must be accounted for when GRACE data are used to quantify surface mass changes. In this study, we developed a technique for co‐estimation of geocenter motion and gravitational potential field seamlessly from degree 1 to 90 by simultaneously inverting a set of globally‐distributed GPS displacement time series and the temporally‐varying GRACE gravity data. We found that the effect of geocenter motion was evident particularly in the GPS time series of horizontal displacements. Our estimates of geocenter motion are most consistent with the Satellite Laser Ranging (SLR) results within 1 mm in X and Z components and a submillimeter in Y component, when compared to monthly variability averaged over the period of 2003–2016. The overall magnitude of the degree‐1 (l = 1) surface mass load is estimated to be ~3 cm in equivalent water height annually migrating south‐westward from Europe (December–January) to the South Pacific (June–July). Our results also show that dense GPS network data improve water storage recovery in major river basins in the United States and Europe by contributing significantly to the recovery of higher‐degree (l ≥ ~20) geopotential coefficients.

Razeghi, Mahdiyeh↗
NASA NTRSDate not supplied

Assessing Sediment Inputs into the Shoshone River in Wyoming to Determine Areas for Protection and Restoration Practices

In 2016, a routine repair operation at the Willwood Dam released tons of built-up sediment into the Shoshone River, polluting the river and killing thousands of fish. This release greatly concerned the communities that rely on the river for farming, recreation, and tourism. In partnership with the Wyoming Department of Environmental Quality (WDEQ), Shoshone River Partners, and the United States Geological Survey (USGS) Wyoming-Montana Water Science Center, this multipart project illustrated the application of high-resolution satellite imagery and hydrological modeling techniques to identify major tributaries contributing to sediment influxes into the Shoshone River between the Buffalo Bill Dam and the Willwood Dam. The team used PlanetScope and Sentinel-2 Multi-Spectral Instrument (MSI) satellite images to assess changes in the surface reflectance of the river in response to precipitation events. To determine these storm events, the team selected dates of interest using Global Precipitation Measurement (GPM) Integrated Multi-Spectral Retrieval (IMERG) and gauge precipitation data from the Global Historical Climatology Network Daily (GHCNd). The continuation of this research further quantified sediment influx in the Shoshone River following snowfall and melt events using the Soil & Water Assessment Tool (SWAT). The precipitation analysis and sediment contribution maps helped the partner organizations prioritize their current decision making and best management practices to specific sites along the river. The results demonstrated the feasibility of using PlanetScope data for categorizing sediment in the Shoshone River.

Caroline Williams↗
NASA NTRS1986

Rapid evolution of a jet streak circulation in a pre-convective environment

An analysis of the April 10, 1979 Red River Valley severe weather outbreak, using a three-hourly rawinsonde network, indicates that the preconvection environment is influenced by upper-level and lower-level tropospheric jet streaks (ULJs and LLJs) that act to destabilize the atmosphere, and contribute to low-level heat and moisture transports and convergence that act to initiate the storm system. Transformation of an indirect circulation noted within the exit region of the ULJ at 1200 and 1500 GMT is observed within a six-hour period. Dramatic changes are found in the jet streak circulations over a short period of time as the system deviates from that approximated by the geostrophic momentum approximation, and these deviations suggest that adjustments asssociated with ULJs in this case could not be resolved using a simplified two-dimensional approach.

Kocin, P. J.↗
NASA NTRS2006

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Adler, Robert F.↗
NASA NTRS2015

Florida Atlantic Coast Telemetry (FACT) Array: A Working Partnership

The Florida Atlantic Coast Telemetry (FACT) Array is a collaborative partnership of researchers from 24 different organizations using passive acoustic telemetry to document site fidelity, habitat preferences, seasonal migration patterns, and reproductive strategies of valuable sportfish, sharks, and marine turtles. FACT partners have found that by bundling resources, they can leverage a smaller investment to track highly mobile animals beyond a study area typically restrained in scale by funds and manpower. FACT is guided by several simple rules: use of the same type of equipment, locate receivers in areas that are beneficial to all researchers when feasible, maintain strong scientific ethics by recognizing that detection data on any receiver belongs to the tag owner, do not use other members detection data without permission and acknowledge FACT in publications. Partners have access to a network of 480 receivers deployed along a continuum of habitats from freshwater rivers to offshore reefs and covers 1100 km of coastline from the Dry Tortugas, Florida to South Carolina and extends to the Bahamas. Presently, 49 species, (25 covered by Fisheries Management Plans and five covered by the Endangered Species Act) have been tagged with 2736 tags in which 1767 tags are still active.

Scheidt, Douglas↗
NASA NTRS1981

Landsat hydrobiological classification for an inland fresh water marsh within Everglades National Park

The considered investigation is concerned with the application of Landsat Multispectral Scanner (MSS) data to the classification of vegetative communities and the establishment of flow vectors for the Shark River Slough in Everglades National Park, Florida. A systematic array of 'ground truth' was established utilizing comprehensive hydrologic field data and conventional high altitude infrared aerial photography. A control network was defined that represented all hydrobiological zones (those wetland vegetative communities that directly influence the rate of overland sheet flow) in the Shark River Slough. These data were then directly applied to the Landsat imagery utilizing an interactive multispectral processor which generated hydrographic maps of the slough and defined the surface radiance characteristics of each hydrobiological system. It was found that the application of Landsat imagery for hydrologic applications in a wetlands area, such as the Shark River Slough in Everglades National Park, is definitely a viable tool for resource management.

Rose, P. W.↗
NASA NTRS2004

ICESat Observations of Inland Surface Water Stage, Slope, and Extent: a New Method for Hydrologic Monitoring

River discharge and changes in lake, reservoir and wetland water storage are critical terms in the global surface water balance, yet they are poorly observed globally and the prospects for adequate observations from in-situ networks are poor (Alsdorf et al., 2003). The NASA-sponsored Surface Water Working Group has established a framework for advancing satellite observations of river discharge and water storage changes which focuses on obtaining measurements of water surface height (stage), slope, and extent. Satellite laser altimetry, which can achieve centimeter-level elevation precision for single, small laser footprints, provides a method to obtain these inland water parameters and contribute to global water balance monitoring. Since its launch in January, 2003 the Ice, Cloud, and land Elevation Satellite (ICESat), a NASA Earth Observing System mission, has achieved over 540 million laser pulse observations of ice sheet, ocean surface, land topography, and inland water elevations and cloud and aerosol height distributions. By recording the laser backscatter from 80 m diameter footprints spaced 175 m along track, ICESat acquires globally-distributed elevation profiles, using a 1064 nm laser altimeter channel, and cloud and aerosol profiles, using a 532 nm atmospheric lidar channel. The ICESat mission has demonstrated the following laser altimeter capabilities relevant to observations of inland water: (1) elevation measurements with a precision of 2 to 3 cm for flat surfaces, suitable for detecting river surface slopes along long river reaches or between multiple crossings of a meandering river channel, (2) from the laser backscatter waveform, detection of water surface elevations beneath vegetation canopies, suitable for measuring water stage in flooded forests, (3) single pulse absolute elevation accuracy of about 50 cm (1 sigma) for 1 degree sloped surfaces, with calibration work in progress indicating that a final accuracy of about 12 cm (1 sigma) will be achieved for clear atmosphere conditions, suitable for detection of stage changes through time, (4) ability to precisely point the spacecraft so as to position the laser profile on the Earth the surface with a cross-track accuracy of 50 m (1 sigma), enabling small water bodies and specific locations to be targeted and re-observed through time, (5) adequate signal levels from specular water surfaces up to 5 degrees off-nadir, enabling complete global access to any location on the Earth's surface from the ICESat repeat orbit by off-nadir pointing, and (6) day and night operation with successful laser ranging to the Earth's surface through thin to moderate cloud cover, enabling more frequent measurements than can be achieved by passive optical sensors. Here we illustrate these capabilities by showing ICESat observations through time for selected river and lake locations.

Harding, David J.↗
NASA NTRS2018

Bloom Modeling and Prediction of the Harmful Algae Alexandrium in Bellingham Bay, WA

Bellingham, Washington is located near the American-Canadian border in the northwestern part of Washington state, and is bordered on its west side by the Lummi reservation. Between Lummi and Bellingham lies Bellingham bay, which has a history of harmful algae related closures dating back to 1978. The subject of this work is a genus of dinoflagellates: Alexandrium, within which many species have the capacity to produce a suite of toxins known as saxitoxin. These toxins bioaccumulate in bivalves, which in turn cause paralytic shellfish poisoning in marine consumers (mammals, birds, and fish), including humans. Symptoms in humans can range from tingling and numbness to difficulty or inability to breathe, resulting in death. Because of the longstanding history of shellfish gathering among Salish tribes and the fact that Washington is the leading U.S. producer of farmed bivalves, harmful algae blooms impact both native and non-native peoples living in the Salish Sea area negatively. The objective of this work is to identify factors which influence Alexandrium blooms in Bellingham Bay, as well as predict Alexandrium blooms in the future. The method of doing so involves two processes: an initial statistical modeling phase to find in situ and remote sensing observations correlated to bloom density (including, but not limited to: water temperature, chlorophyll-a, salinity, color dissolved organic matter, and discharge rate of local rivers), followed by use of that data as a training set for a recursive neural network. This predictive capacity may inform future closures, help ensure the safety of shellfish consumers, and act as a baseline for future modeling efforts in the region.

Harmful↗
NASA NTRS2019

Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)

Satellite-based precipitation is an essential tool for regional water resource applications that requires frequent observations of meteorological forcing, particularly in areas that have sparse rain gauge networks. To fully realize the utility of remotely sensed precipitation products in watershed modeling and decision-making, a thorough evaluation of the accuracy of satellite-based rainfall and regional gauge network estimates is needed. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 v.7 and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall estimates were compared with daily rain gauge observations from 2000 to 2014 in the Lower Mekong River Basin (LMRB) in Southeast Asia. Monthly, seasonal, and annual comparisons were performed, which included the calculations of correlation coefficient, coefficient of determination, bias, root mean square error (RMSE), and mean absolute error (MAE). Our validation test showed TMPA to correctly detect precipitation or no-precipitation 64.9% of all days and CHIRPS 66.8% of all days, compared to daily in-situ rainfall measurements. The accuracy of the satellite-based products varied greatly between the wet and dry seasons. Both TMPA and CHIRPS showed higher correlation with in-situ data during the wet season (June–September) as compared to the dry season (November–January). Additionally, both performed better on a monthly than an annual time-scale when compared to in-situ data. The satellite-based products showed wet biases during months that received higher cumulative precipitation. Based on a spatial correlation analysis, the average r-value of CHIRPS was much higher than TMPA across the basin. CHIRPS correlated better than TMPA at lower elevations and for monthly rainfall accumulation less than 500 mm. While both satellite-based products performed well, as compared to rain gauge measurements, the present research shows that CHIRPS might be better at representing precipitation over the LMRB than TMPA.

Dandridge, Chelsea↗
NASA NTRS1982

Defense Meteorological Satellite Program (DMSP)

The Defense Meteorological Satellite Program is a total satellite system composed of spacecraft with meteorological sensors, an Earth-based command and control network, user stations, launch vehicle and support; with a communication network linking the various segments together. The various system segments are described.

Rivers, J. W., Jr.↗
NASA NTRS1985

Tropospheric gravity waves observed by three closely-spaced ST radars

During a 6 week period in 1982, 3 ST (Stratosphere-Troposphere) radars measured horizontal and vertical wavelengths of small scale tropospheric gravity waves. These 50 MHz, vertically-directed radars were located in a trianglar network with approximately 5 km spacing on the southern coast of France at the mouth of the Rhone River during the ALPEX (Alpine Experiment) program.

Carter, D. A.↗