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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Thermospheric and ionospheric structure of the Southern Hemisphere polar cap on October 21, 1981, as determined from Dynamics Explorer 2 satellite data

For a number of years, satellites have been employed to measure auroral particles and fields within the high-latitude thermosphere. In the present paper, data from orbit 1174 of the Dynamics Explorer 2 satellite on October 21, 1981, are utilized to calculate the structure of the ionosphere and thermosphere below the satellite altitude down to about 80 km. Attention is given to details regarding the DE 2 measurements, a satellite track model, the calculated ionospheric structure, and the calculated neutral gas heating rates. The investigation demonstrates that the technique of deriving characteristics of the ionosphere and atmosphere below a satellite track promises to be very fruitful for defining the characteristics of the lower thermosphere for use in large numerical models of the thermosphere and ionosphere.

Emery, B. A.↗
NASA NTRS1972

Interhemispheric comparison of atmospheric circulation features as evaluated from Nimbus satellite data

The report includes a complete analyses of O3 data inferred from Nimbus-3 measurements, a discussion of future areas of study, description of the regression and inversion methods developed to infer atmospheric temperature and tropopause characteristics, as well as the plan to process the satellite data for a systematic study of the relative circulation differences between Northern and Southern Hemispheres.

Reiter, E. R.↗
NASA NTRS1979

Data System Implications Derived from User Application Requirements for Satellite Data

An investigation of the data system needs as driven by users of space acquired Earth observation data is documented. Two major categories of users, operational and research, are identified. Limiting data acquisition alleviates some of the delays in processing thus improving timeliness of the delivered product. Trade offs occur between timeliness and data distribution costs, and between data storage and reprocessing. The complexity of the data system requirements to apply space data to users' needs is such that no single analysis suffices to design and implement the optimum system. A series of iterations is required with analyses of the salient problems in a general way, followed by a limited implementation of benefit to some users with a continual upgrade in system capacity, functions, and applications served. The resulting most important requirement for the data system is flexibility to accommodate changing requirements as the system is implemented.

Neiers, J.↗
NASA NTRS1989

Use of satellite data and modeling to asses the influence of stratospheric processes on the troposphere

The research is comprised of the following tasks: use of simple analytical and numerical models of a coupled troposphere-stratosphere system to examine the effects of radiation and ozone on planetary wave dynamics and the tropospheric circulation; use of satellite data obtained from the Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) instrument and Solar Backscattered Ultraviolet (SBUV) experiment, in conjunction with National Meteorological Center (NMC) data, to determine the planetary wave vertical structures, dominant wave spectra, ozone spectra, and time variations in diabatic heating rate; and synthesis of the modeling and observational results to provide a better understanding of the effects that stratospheric processes have on tropospheric dynamics.

Nathan, Terrence R.↗
DOE OSTI2026

Measuring impacts of California agri-environmental programs using field-scale satellite data

In the past decade, California has invested over $\$$200 million in direct grants to growers to support the adoption of agricultural practices that save water and/or improve soil health while also reducing greenhouse gas emissions. Ex-post evaluation of agri-environmental outcomes of these grant programs, however, is limited. We use satellite data to monitor changes in field-level consumptive water use and greenness (i.e. normalized difference vegetation index), a proxy for agricultural productivity, for the most frequently funded crop-types (almonds, grapes, and walnuts) in two California Department of Food and Agriculture programs. Nearly 600 fields receiving funding during the 2014–2022 period were analyzed using two causal inference methods. Fields that received grants to both upgrade irrigation systems and install irrigation water management sensors showed reduced consumptive water use and greenness by an average of 3.5% and 4.2%, respectively (significant at the 10% level). In contrast, we find that the adoption of only irrigation water management sensors, which are designed to inform irrigation scheduling and management, resulted in an average increase of 4.1% and 4.8% in consumptive water use and greenness respectively (significant at the 5% level). We find negligible effects for either consumptive water use or greenness when both pump efficiency upgrades and sensors were implemented. We further find that grants for compost addition and cover cropping led to small greenness increases of 1.7% and 2.8% respectively (significant at the 10% level) and had insignificant effects on consumptive water use. Our analysis of five agri-environmental program interventions reveals that several practice outcomes may be at odds with stated program goals of reducing water use while maintaining or improving agricultural productivity.

agriculture↗
NASA NTRS1999

Utilization of Satellite Data in Land Surface Hydrology: Sensitivity and Assimilation

This paper investigates the sensitivity of potential evapotranspiration to input meteorological variables, viz- surface air temperature and surface vapor pressure. The sensitivity studies have been carried out for a wide range of land surface variables such as wind speed, leaf area index and surface temperatures. Errors in the surface air temperature and surface vapor pressure result in errors of different signs in the computed potential evapotranspiration. This result has implications for use of estimated values from satellite data or analysis of surface air temperature and surface vapor pressure in large scale hydrological modeling. The comparison of cumulative potential evapotranspiration estimates using ground observations and satellite observations over Manhattan, Kansas for a period of several months shows very little difference between the two. The cumulative differences between the ground based and satellite based estimates of potential evapotranspiration amounted to less that 20mm over a 18 month period and a percentage difference of 15%. The use of satellite estimates of surface skin temperature in hydrological modeling to update the soil moisture using a physical adjustment concept is studied in detail including the extent of changes in soil moisture resulting from the assimilation of surface skin temperature. The soil moisture of the surface layer is adjusted by 0.9mm over a 10 day period as a result of a 3K difference between the predicted and the observed surface temperature. This is a considerable amount given the fact that the top layer can hold only 5mm of water.

Lakshmi, Venkataraman↗
NASA NTRS1981

Computer generated maps from digital satellite data - A case study in Florida

Ground cover maps are important tools to a wide array of users. Over the past three decades, much progress has been made in supplementing planimetric and topographic maps with ground cover details obtained from aerial photographs. The present investigation evaluates the feasibility of using computer maps of ground cover from satellite input tapes. Attention is given to the selection of test sites, a satellite data processing system, a multispectral image analyzer, general purpose computer-generated maps, the preliminary evaluation of computer maps, a test for areal correspondence, the preparation of overlays and acreage estimation of land cover types on the Landsat computer maps. There is every indication to suggest that digital multispectral image processing systems based on Landsat input data will play an increasingly important role in pattern recognition and mapping land cover in the years to come.

Arvanitis, L. G.↗
NASA NTRS2016

Estimation of Daily PM(sub 10) Concentrations in Italy (2006-2012) Using Finely Resolved Satellite Data, Land Use Variables and Meteorology

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM10=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM10levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Particulate Matter/analysis↗
NASA NTRS1990

Use of satellite data and modeling to assess the influence of stratospheric processes on the troposphere

Current research focused on the examination of the effects of ozone heating and Newtonian cooling on the linear stability of transient planetary waves. A finite difference numerical model was developed in which the basic state wind, temperature, and ozone distributions were constructed using ground-based and satellite data. Preliminary results indicate that ozone dynamics interaction may play a more important role in the stability and maintenance of planetary waves than previously thought, particularly in summer when the mean solar zenith angle is smallest and thus ozone heating largest. Examination of the finite amplitude interactions among radiation, ozone, and dynamics was carried out. Self-consistent, coupled equations governing the weakly nonlinear interactions are currently being analyzed to provide a better understanding of wave-mean flow interactions and ozone transport in a continuously stratified model of the troposphere-stratosphere coupled system.

Nathan, Terrence↗
NASA NTRS2022

Estimating groundwater use and demand in arid Kenya through assimilation of satellite data and in-situ sensors with machine learning toward drought early action

Groundwater is an important source of water for people, livestock, and agriculture during drought in the Horn of Africa. In this work, areas of high groundwater use and demand in drought-prone Kenya were identified and forecasted prior to the dry season. Estimates of groundwater use were extended from a sentinel network of 69 in-situ sensored mechanical boreholes to the region with satellite data and a machine learning model. The sensors contributed 756 site-month observations from June 2017 to September 2021 for model building and validation at a density of approximately one sensor per 3700 sq.km. An ensemble of 19 parameterized algorithms was informed by features including satellite-derived precipitation, surface water availability, vegetation indices, hydrologic land surface modeling, and site characteristics to dichotomize high groundwater pump utilization. Three operational definitions of high demand on groundwater infrastructure were considered: 1) mechanical runtime of pumps greater than a quarter of a day (6+ hr) and daily per capita volume extractions indicative of 2) domestic water needs (35+ L), and 3) intermediate needs including livestock (75+ L). Gridded interpolation of localized groundwater use and demand was provided from 2017 to 2020 and forecasted for the 2021 dry season, June–September 2021. Cross-validated skill for contemporary estimates of daily pump runtime and daily volume extraction to meet domestic and intermediate water needs was 68%, 69%, and 75%, respectively. Forecasts were externally validated with an accuracy of at least 56%, 70%, or 72% for each groundwater use definition. The groundwater maps are accessible to stakeholders including the Kenya National Drought Management Authority (NDMA) and the Famine Early Warning Systems Network (FEWS NET). These maps represent the first operational spatially-explicit sub-seasonal to seasonal (S2S) estimates of groundwater use and demand in the literature. Knowledge of historical and forecasted groundwater use is anticipated to improve decision-making and resource allocation for a range of early warning early action applications.

Katie Fankhauser↗
NASA NTRSDate not supplied

Creating IR-verified Gridded Fire Burn Maps using Public NASA and Satellite Data

Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop a high-confidence grid-based wildfire burn product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This product will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use VIIRS (Visible Infrared Imaging Radiometer Suite) 375 m fire detections and Sentinel-2 10 m satellite imagery to create a 20-m gridded fire burn product. Our process is based on the level of confidence in the data source and takes into account vegetation change throughout the life of the fire. For example, Sentinel-2 vegetation-change indices have a higher level of confidence when congruent with VIIRS active-fire detection data, rather than VIIRS detections alone. We have also verified our fire burn product against MODIS/ASTER Airborne Simulator (MASTER) Infrared (IR) data from the Fire Influence on Regional to Global Environments Experiment - Air Quality (FIREX-AQ) 2019 campaign, with 88% overall agreement. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗
NASA NTRS1992

A parameterization for longwave surface radiation from satellite data - Recent improvements

Several improvements have been made recently to the parameterization for surface longwave radiation described by Gupta (1989). Model constants have been modified in order to use meteorological data from the International Satellite Cloud Climatology Project instead of from the TIROS Operational Vertical Sounder data, primarily to take advantage of the vastly superior cloud information available from the former. Additional modifications were made to improve the estimation of cloud effect in the presence of low-level clouds. The latter modifications reduced the systematic error of the overcast-sky fluxes from 10.0 to 1.7 W/sq m and the random error from +/- 18.9 to +/- 6.3 W/sq m when compared to the fluxes computed with a detailed radiative transfer model.

Gupta, Shashi K.↗
NASA NTRS2014

Use of NASA Near Real-Time and Archived Satellite Data to Support Disaster Assessment

NASA's Short‐term Prediction Research and Transition (SPoRT) Center partners with the NWS to provide near realtime data in support of a variety of weather applications, including disasters. SPoRT supports NASA's Applied Sciences Program: Disasters focus area by developing techniques that will aid the disaster monitoring, response, and assessment communities. SPoRT has explored a variety of techniques for utilizing archived and near real‐time NASA satellite data. An increasing number of end‐users - such as the NWS Damage Assessment Toolkit (DAT) - access geospatial data via a Web Mapping Service (WMS). SPoRT has begun developing open‐standard Geographic Information Systems (GIS) data sets via WMS to respond to end‐user needs.

McGrath, Kevin M.↗
NASA NTRS1996

NASDA's earth observation satellite data archive policy for the earth observation data and information system (EOIS)

NASDA's new Advanced Earth Observing Satellite (ADEOS) is scheduled for launch in August, 1996. ADEOS carries 8 sensors to observe earth environmental phenomena and sends their data to NASDA, NASA, and other foreign ground stations around the world. The downlink data bit rate for ADEOS is 126 MB/s and the total volume of data is about 100 GB per day. To archive and manage such a large quantity of data with high reliability and easy accessibility it was necessary to develop a new mass storage system with a catalogue information database using advanced database management technology. The data will be archived and maintained in the Master Data Storage Subsystem (MDSS) which is one subsystem in NASDA's new Earth Observation data and Information System (EOIS). The MDSS is based on a SONY ID1 digital tape robotics system. This paper provides an overview of the EOIS system, with a focus on the Master Data Storage Subsystem and the NASDA Earth Observation Center (EOC) archive policy for earth observation satellite data.

Sobue, Shin-ichi↗
NASA NTRS1978

Comparison of surface and satellite gravity data

Satellite derived potential coefficients (GEM 9) are compared to terrestrial gravity data by degree in terms of coefficient differences and in terms of mean anomaly differences. The root mean square undulation difference (to degree 20) was 9 + or - m and the anomaly difference was + or - 7 mgals with GEM 9 commission errors of + or - 1.7 m and + or - 3.8 mgals. The standard deviations of the GEM 9 implied undulations increased from + or - 4 cm at degree 2 to + or - 53 cm at degree 20. The corresponding values implied by a recent (June 1978) terrestrial 5 deg field were + or - 2.53 m and + or - 0.38 m (at degree 20). Comparisons between Geos-3 altimeter derived anomalies and 1 deg X 1 Deg terrestrial data showed that + or - 6-8 mgals is a reasonable accuracy estimate for the altimeter derived anomalies. Anomalies derived from satellite to satellite tracking data indicate an accuracy of about + or - 6 mgals for the recovery of 5 deg equal area blocks.

Rapp, R. H.↗
NASA NTRS2003

Applications of Sea-Ice Motion and Deformation Derived from Satellite Data

QuikSCAT backscatter, AMSR and DMSP SSM/I radiance data have been used to derive sea ice motion for both the Arctic and Antarctic region using the wavelet analysis tracking method. All results from QuikSCAT, AMSR and SSM5 are compatible with buoys and can then be merged by data fusion method to generate composite sea ice motion maps for more complete coverage. Furthermore, based on this merged data set daily sea-ice deformation (shear, and convergence) maps have been produced and show consistent spatial and temporal patterns. Temporal correlation maps between ice deformation and SSM/II ice concentration show interesting results in the Arctic, especially the coast area. In this study, principal component analysis for both the merged ice tracking result from satellite data and pressure field from buoy have also been examined for the relationship between the principal components and eigenvectors from these two data sets. While the result shows that principal components of modes 1 and 2 from two data sets are highly correlated which confirms that wind forcing is a major factor driving the ice drift, it also reveals that other high energy modes are not highly correlated which maybe caused by coastal effects. Principal component analysis of Arctic sea-ice motion during fall/winter period in different years shows the reverse of dominant modes or patterns is related to the Arctic Oscillation.

Liu, Antony K.↗