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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Sea ice-atmosphere interaction. Application of multispectral satellite data in polar surface energy flux estimates

Satellite data for the estimation of radiative and turbulent heat fluxes is becoming an increasingly important tool in large-scale studies of climate. One parameter needed in the estimation of these fluxes is surface temperature. To our knowledge, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic, an area where the first effects of a changing climate are expected to be seen. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol profiles, the microphysical properties of polar clouds, and the spectral characteristics of the wide variety of surface types found there. We have developed a means to correct for the atmospheric attenuation of satellite-measured clear sky brightness temperatures used in the retrieval of ice surface temperature from the split-window thermal channels of the advanced very high resolution radiometer (AVHRR) sensors on-board three of the NOAA series satellites. These corrections are specified for three different 'seasons' and as a function of satellite viewing angle, and are expected to be applicable to the perennial ice pack in the central Arctic Basin.

Steffen, Konrad↗
NASA NTRS1983

Continental land cover classification using meteorological satellite data

The use of the National Oceanic and Atmospheric Administration's advanced very high resolution radiometer satellite data for classifying land cover and monitoring of vegetation dynamics over an extremely large area is demonstrated for the continent of Africa. Data from 17 imaging periods of 21 consecutive days each were composited by a technique sensitive to the in situ green-leaf biomass to provide cloud-free imagery for the whole continent. Virtually cloud-free images were obtainable even for equatorial areas. Seasonal variation in the density and extent of green leaf vegetation corresponded to the patterns of rainfall associated with the inter-tropical convergence zone. Regional variations, such as the 1982 drought in east Africa, were also observed. Integration of the weekly satellite data with respect to time produced a remotely sensed assessment of biological activity based upon density and duration of green-leaf biomass. Two of the 21-day composited data sets were used to produce a general land cover classification. The resultant land cover distributions correspond well to those of existing maps.

Tucker, C. J.↗
NASA NTRS1985

Utilization of satellite data and regional scale numerical models in short range weather forecasting

Overwhelming evidence was developed in a number of studies of satellite data impact on numerical weather prediction that it is unrealistic to expect satellite temperature soundings to improve detailed regional numerical weather prediction. It is likely that satellite data over the United States would substantially impact mesoscale dynamical predictions if the effort were made to develop a composite moisture analysis system. The horizontal variability of moisture, most clearly depicited in images from satellite water vapor channels, would not be determined from conventional rawinsondes even if that network were increased by a doubling of both the number of sites and the time frequency.

Kreitzberg, C. W.↗
NASA NTRS1992

High resolution gravity models combining terrestrial and satellite data

Spherical harmonic expansions to degree 360 have been developed that combine satellite potential coefficient information, terrestrial gravity data, satellite altimeter information as a direct tracking data type and topographic information. These models define improved representations of the Earth's gravitational potential beyond that available from just satellite or terrestrial data. The development of the degree 360 models, however, does not imply a uniform accuracy in the determination of the gravity field as numerous geographic areas are devoid of terrestrial data or the resolution of such data is limited to, for example, 100 km. This paper will consider theoretical and numerical questions related to the combination of the various data types. Various models of the combination process are discussed with a discussion of various correction terms for the different models. Various sources of gravity data will be described. The new OSU91 360 model will be discussed with comparisons made to previous 360 models and to other potential coefficient models that are complete to degree 50. Future directions in high degree potential coefficient models will be discussed.

Rapp, Richard H.↗
NASA NTRS2000

A Method for Assessing the Quality of Model-Based Estimates of Ground Temperature and Atmospheric Moisture Using Satellite Data

A method is developed for validating model-based estimates of atmospheric moisture and ground temperature using satellite data. The approach relates errors in estimates of clear-sky longwave fluxes at the top of the Earth-atmosphere system to errors in geophysical parameters. The fluxes include clear-sky outgoing longwave radiation (CLR) and radiative flux in the window region between 8 and 12 microns (RadWn). The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data, and multiple global four-dimensional data assimilation (4-DDA) products. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic clear-sky longwave fluxes from two different 4-DDA data sets. Simple linear regression is used to relate the clear-sky longwave flux discrepancies to discrepancies in ground temperature ((delta)T(sub g)) and broad-layer integrated atmospheric precipitable water ((delta)pw). The slopes of the regression lines define sensitivity parameters which can be exploited to help interpret mismatches between satellite observations and model-based estimates of clear-sky longwave fluxes. For illustration we analyze the discrepancies in the clear-sky longwave fluxes between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS2) and a recent operational version of the European Centre for Medium-Range Weather Forecasts data assimilation system. The analysis of the synthetic clear-sky flux data shows that simple linear regression employing (delta)T(sub g)) and broad layer (delta)pw provides a good approximation to the full radiative transfer calculations, typically explaining more thin 90% of the 6 hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters, Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for (delta)T(sub g) to approx. 20% for the lower tropospheric moisture between 500 hPa and surface. The regression relationships developed from the synthetic flux data, together with CLR and RadWn observed with the Clouds and Earth Radiant Energy System instrument, ire used to assess the quality of the GEOS2 T(sub g) and pw. Results showed that the GEOS2 T(sub g) is too cold over land, and pw in upper layers is too high over the tropical oceans and too low in the lower atmosphere.

Wu, Man Li C.↗
NASA NTRS2015

Simultaneous Radar and Satellite Data Storm-Scale Assimilation Using an Ensemble Kalman Filter Approach for 24 May 2011

Assimilating high-resolution radar reflectivity and radial velocity into convection-permitting numerical weather prediction models has proven to be an important tool for improving forecast skill of convection. The use of satellite data for the application is much less well understood, only recently receiving significant attention. Since both radar and satellite data provide independent information, combing these two sources of data in a robust manner potentially represents the future of high-resolution data assimilation. This research combines Geostationary Operational Environmental Satellite 13 (GOES-13) cloud water path (CWP) retrievals with Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity to examine the impacts of assimilating each for a severe weather event occurring in Oklahoma on 24 May 2011. Data are assimilated into a 3-km model using an ensemble adjustment Kalman filter approach with 36 members over a 2-h assimilation window between 1800 and 2000 UTC. Forecasts are then generated for 90 min at 5-min intervals starting at 1930 and 2000 UTC. Results show that both satellite and radar data are able to initiate convection, but that assimilating both spins up a storm much faster. Assimilating CWP also performs well at suppressing spurious precipitation and cloud cover in the model as well as capturing the anvil characteristics of developed storms. Radar data are most effective at resolving the 3D characteristics of the core convection. Assimilating both satellite and radar data generally resulted in the best model analysis and most skillful forecast for this event.

Jones, Thomas A.↗
NASA NTRS1992

ARC - A source of multisensor satellite data for polar science

The NSF's Antarctic Research Center (ARC) has been established to furnish real-time polar-orbiting satellite data in support of Antarctic field studies, as well as to maintain a multisensor satellite data (MSD) archive for retrospective data analysis. An account is presently given of the ways in which the complementary nature of an MSD set can deepen understanding of Antarctic physical processes. An active microwave SAR with 30-m resolution and a radar altimeter will be added to the ARC resources later in this decade, as will the Earth Observing System.

Van Woert, Michael L.↗
NASA NTRS1977

ASDAR (aircraft to satellite data relay) flight test report

The aircraft to Satellite Data Relay (ASDAR), an airborne data collection system that gathers meteorological data from existing aircraft instrumentation and relays it to ground user via a geo-synchronous meteorological satellite, is described and the results of the first test flight on a commercial Boeing 747 aircraft are presented. The flight test was successful and verified system performance in the anticipated environment.

Domino, E. J.↗
NASA NTRS2014

Open Source GIS Connectors to NASA GES DISC Satellite Data

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) houses a suite of high spatiotemporal resolution GIS data including satellite-derived and modeled precipitation, air quality, and land surface parameter data. The data are valuable to various GIS research and applications at regional, continental, and global scales. On the other hand, many GIS users, especially those from the ArcGIS community, have difficulties in obtaining, importing, and using our data due to factors such as the variety of data products, the complexity of satellite remote sensing data, and the data encoding formats. We introduce a simple open source ArcGIS data connector that significantly simplifies the access and use of GES DISC data in ArcGIS.

user↗
NASA NTRS1983

Analysis of cloud characteristics derived from archived satellite data

The present investigation is concerned with the differing scientific user community requirements for cloud data and the nature of archived satellite data. It is concluded that information on cloud characteristics and cloud cover is of the utmost importance for at least three scientific research areas, viz. numerical weather forecasting, environmental remote sensing, and climatic monitoring and modelling. However, these three user groups require information at different levels of temporal and spatial resolution, and the nature of the comparison between surface and satellite assessment of cloud cover differs among the three groups. Taking into account the diverse requirements of the scientific community and difficulty of a mutually agreed definition of the cloud parameters, a number of recommendations are made. It is suggested that radiance data, not cloud data, should be archived directly from satellite observations, and that the highest spatial and temporal resolutions available should be retained in the archive.

Hughes, N. A.↗
NASA NTRS1987

The area-time-integral technique to estimate convective rain volumes over areas applied to satellite data - A preliminary investigation

The use of the area-time-integral (ATI) technique, based only on satellite data, to estimate convective rain volume over a moving target is examined. The technique is based on the correlation between the radar echo area coverage integrated over the lifetime of the storm and the radar estimated rain volume. The processing of the GOES and radar data collected in 1981 is described. The radar and satellite parameters for six convective clusters from storm events occurring on June 12 and July 2, 1981 are analyzed and compared in terms of time steps and cluster lifetimes. Rain volume is calculated by first using the regression analysis to generate the regression equation used to obtain the ATI; the ATI versus rain volume relation is then employed to compute rain volume. The data reveal that the ATI technique using satellite data is applicable to the calculation of rain volume.

Doneaud, Andre A.↗
NASA NTRS2015

The Process of Bringing Dark Data to Light: The Rescue of the Early Nimbus Satellite Data

Myriad environmental satellite missions are currently orbiting the earth. The comprehensive monitoring by these sensors provide scientists, policymakers, and the public critical information on the earths weather and climate system. The state of the art technology of our satellite monitoring system is the legacy of the first environment satellites, the Nimbus systems launched by NASA in the mid-1960s. Such early data can extend our climate record and provide important context in longer-term climate changes. However, the data was stowed away and, over the years, largely forgotten. It was nearly lost before its value was recognized and attempts to recover the data were undertaken. This paper covers what it took the authors to recover, navigate and reprocess the data into modern formats so that it could be used as a part of the satellite climate record. The procedures to recover the Nimbus data, from both film and tape, could be used by other data rescue projects, however the algorithms presented will tend to be Nimbus specific. Data rescue projects are often both difficult and time consuming but the data they bring back to the science community makes these efforts worthwhile.

dark↗
NASA NTRS1988

A multivariate variational objective analysis-assimilation method. Part 2: Case study results with and without satellite data

The variational multivariate assimilation method described in a companion paper by Achtemeier and Ochs is applied to conventional and conventional plus satellite data. Ground-based and space-based meteorological data are weighted according to the respective measurement errors and blended into a data set that is a solution of numerical forms of the two nonlinear horizontal momentum equations, the hydrostatic equation, and an integrated continuity equation for a dry atmosphere. The analyses serve first, to evaluate the accuracy of the model, and second to contrast the analyses with and without satellite data. Evaluation criteria measure the extent to which: (1) the assimilated fields satisfy the dynamical constraints, (2) the assimilated fields depart from the observations, and (3) the assimilated fields are judged to be realistic through pattern analysis. The last criterion requires that the signs, magnitudes, and patterns of the hypersensitive vertical velocity and local tendencies of the horizontal velocity components be physically consistent with respect to the larger scale weather systems.

Achtemeier, Gary L.↗
NASA NTRS1987

Lightning data study in conjunction with geostationary satellite data

During the summer of 1985, cloud-to-ground stroke lightning were collected. Thirty minute samples of lightning were compared with GOES IR fractional cold cloud coverage computed for three temperature thresholds (213, 243, and 273 K) twice daily (morning and evening). It was found that satellite measurements of cold cloud have a relationship to the flashrate and, in a more limited way, to the polarity and numbers of return strokes. Results varied little by location. Lightning, especially positive strokes, was found to be correlated with fractional cloud coverage, especially for clouds at or below 213 K. Other data and correlations are discussed.

Auvine, Brian↗