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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Low cost, microcomputer-based interactive analysis system for direct-reception and archived remote sensing data

A hardware/software system has been developed for use in meteorological field experiments and by developing countries which need low-cost remote sensing data analysis capabilities. The system can directly receive satellite transmissions of the AVHRR, TOVS, Argos, GOES, GMS, and Meteosat systems. Also, the system can process computer tapes from Landsat. Received data are ingested directly into the computer's disk storage, eliminating the need for a wide-band analog tape drive. Data may be interpreted in terms of cloud imagery, cloudtop temperature, sea surface temperature, vegetation index, and temperature/humidity profiles with overlays of geographic boundaries and latitude/longitude grids. The image processing, enhancement functions, and modeling capabilities of the system are discussed.

Vermillion, Charles H.↗
NASA NTRS1992

Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) PARM tape user's guide

The Scanning Multichannel Microwave Radiometer (SMMR) instrument, onboard the Nimbus-7 spacecraft, collected data from Oct. 1978 until Jun. 1986. The data were processed to physical parameter level products. Geophysical parameters retrieved include the following: sea-surface temperatures, sea-surface windspeed, total column water vapor, and sea-ice parameters. These products are stored on PARM-LO, PARM-SS, and PARM-30 tapes. The geophysical parameter retrieval algorithms and the quality of these products are described for the period between Nov. 1978 and Oct 1985. Additionally, data formats and data availability are included.

Han, D.↗
NASA NTRS1994

Tropical cloud feedbacks and natural variability of climate

Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a 'red' spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.

Miller, R. L.↗
NASA NTRS2002

The Science Behind the NASA/NOAA Electronic Theater 2002

Details of the science stories and scientific results behind the Etheater Earth Science Visualizations from the major remote sensing institutions around the country will be explained. The NASA Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to Temple Square and the University of Utah Campus. Go back to the early weather satellite images from the 1960s see them contrasted with the latest US/Europe/Japan global weather data. See the latest images and image sequences from NASA & NOAA missions like Terra, GOES, NOAA, TRMM, SeaWiFS, Landsat 7 visualized with state-of-the art tools. A similar retrospective of numerical weather models from the 1960s will be compared with the latest "year 2002" high-resolution models. See the inner workings of a powerful hurricane as it is sliced and dissected using the University of Wisconsin Vis-5D interactive visualization system. The largest super computers are now capable of realistic modeling of the global oceans. See ocean vortexes and currents that bring up the nutrients to feed phitoplankton and zooplankton as well as draw the crill fish, whales and fisherman. See the how the ocean blooms in response to these currents and El Nino/La Nina climate regimes. The Internet and networks have appeared while computers and visualizations have vastly improved over the last 40 years. These advances make it possible to present the broad scope and detailed structure of the huge new observed and simulated datasets in a compelling and instructive manner. New visualization tools allow us to interactively roam & zoom through massive global images larger than 40,000 x 20,000 pixels. Powerful movie players allow us to interactively roam, zoom & loop through 4000 x 4000 pixel bigger than HDTV movies of up to 5000 frames. New 3D tools allow highly interactive manipulation of detailed perspective views of many changing model quantities. See the 1m resolution before and after shots of lower Manhattan and the Pentagon after the September 11 disaster as well as shots of Afghanistan from the Space Imaging IKONOS as well as debris plume images from Terra MODIS and SPOT Image. Shown by the SGI-Octane Graphics-Supercomputer are visualizations of hurricanes Michelle 2001, Floyd, Mitch, Fran and Linda. Our visualizations of these storms have been featured on the covers of the National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA's large collection of High Definition TV (HDTV) visualizations clips New visualizations of a Los Alamos global ocean model, and high-resolution results of a NASA/JPL Atlantic ocean basin model showing currents, and salinity features will be shown. El Nino/La Nina effects on sea surface temperature and sea surface height of the Pacific Ocean will also be shown. The SST simulations will be compared with GOES Gulf Stream animations and ocean productivity observations. Tours will be given of the entire Earth's land surface at 500 m resolution from recently composited Terra MODIS data, Visualizations will be shown from the Earth Science Etheater 2001 recently presented over the last years in New Zealand, Johannesburg, Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York City, Pasadena, UCAR/Boulder, and Penn State University. The presentation will use a 2-CPU SGI/CRAY Octane Super Graphics workstation with 4 GB RAM and terabyte disk array at 2048 x 768 resolution plus multimedia laptop with three high resolution projectors. Visualizations will also be featured from museum exhibits and presentations including: the Smithsonian Air & Space Museum in Washington, IMAX theater at the Maryland Science Center in Baltimore, the James Lovell Discovery World Science museum in Milwaukee, the American Museum of Natural History (NYC) Hayden Planetarium IMAX theater, etc. The Etheater is sponsored by NASA, NOAA and the American Meteorological Society. This presentation is brought to you by the University of Utah College of Mines and Earth Sciences and, the Utah Museum of Natural History.

Hasler, A. Fritz↗
NASA NTRS2018

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +/-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

retrieval algorithm↗
NASA NTRS2018

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

calibration↗
NASA NTRS2022

The impacts of immersion ice nucleation parameterizations on Arctic mixed-phase stratiform cloud properties and the Arctic radiation budget in GEOS-5

The influence of four different immersion freezing parameterizations on Arctic clouds and the top-of-the atmosphere (TOA) and surface radiation fluxes is investigated in the fifth version of the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System (GEOS-5) with sea surface temperature, sea ice fraction and aerosol emissions held fixed. The different parameterizations were derived from a variety of sources, including classical nucleation theory, field and laboratory measurements. Despite the large spread in the ice-nucleating particle (INP) concentrations in the parameterizations, the cloud properties and radiative fluxes had a tendency to form two groups, with the lower INP concentration category producing larger water path and low-level cloud fraction during winter and early spring, whereas the opposite occurred during the summer season. The stability of the lower troposphere was found to strongly correlate with low-cloud fraction, and along with the effect of ice nucleation, ice sedimentation and melting rates, appears to explain the spring-to-summer reversal pattern in the relative magnitude of the cloud properties between the two categories of simulations. The strong modulation effect of the liquid phase on immersion freezing led to the successful simulation of the characteristic Arctic cloud structure, with a layer rich in supercooled water near cloud top and ice and snow at lower levels. Comparison with satellite retrievals and in situ data suggest that simulations with low INP concentrations more realistically represent Arctic clouds and radiation.

Arctic↗
NASA NTRS2000

Climate and infectious disease: use of remote sensing for detection of Vibrio cholerae by indirect measurement

It has long been known that cholera outbreaks can be initiated when Vibrio cholerae, the bacterium that causes cholera, is present in drinking water in sufficient numbers to constitute an infective dose, if ingested by humans. Outbreaks associated with drinking or bathing in unpurified river or brackish water may directly or indirectly depend on such conditions as water temperature, nutrient concentration, and plankton production that may be favorable for growth and reproduction of the bacterium. Although these environmental parameters have routinely been measured by using water samples collected aboard research ships, the available data sets are sparse and infrequent. Furthermore, shipboard data acquisition is both expensive and time-consuming. Interpolation to regional scales can also be problematic. Although the bacterium, V. cholerae, cannot be sensed directly, remotely sensed data can be used to infer its presence. In the study reported here, satellite data were used to monitor the timing and spread of cholera. Public domain remote sensing data for the Bay of Bengal were compared directly with cholera case data collected in Bangladesh from 1992-1995. The remote sensing data included sea surface temperature and sea surface height. It was discovered that sea surface temperature shows an annual cycle similar to the cholera case data. Sea surface height may be an indicator of incursion of plankton-laden water inland, e.g., tidal rivers, because it was also found to be correlated with cholera outbreaks. The extensive studies accomplished during the past 25 years, confirming the hypothesis that V. cholerae is autochthonous to the aquatic environment and is a commensal of zooplankton, i.e., copepods, when combined with the findings of the satellite data analyses, provide strong evidence that cholera epidemics are climate-linked.

Cholera/epidemiology↗
NASA NTRS1994

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

One essential parameter used in the estimation of radiative and turbulent heat fluxes from satellite data is surface temperature. Sea and land surface temperature (SST and LST) retrieval algorithms that utilize the thermal infrared portion of the spectrum have been developed, with the degree of success dependent primarily upon the variability of the surface and atmospheric characteristics. However, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic and Antarctic pack ice or the ice sheet surface temperature over Antarctica and Greenland. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol vertical, spatial and temporal distributions, the microphysical properties of polar clouds, and the spectral characteristics of snow, ice, and water surfaces. Over the open ocean the surface is warm, dark, and relatively homogeneous. This makes SST retrieval, including cloud clearing, a fairly straightforward task. Over the ice, however, the surface within a single satellite pixel is likely to be highly heterogeneous, a mixture of ice of various thicknesses, open water, and snow cover in the case of sea ice. Additionally, the Arctic is cloudy - very cloudy - with typical cloud cover amounts ranging from 60-90 percent. There are few observations of cloud cover amounts over Antarctica. The goal of this research is to increase our knowledge of surface temperature patterns and magnitudes in both polar regions, by examining existing data and improving our ability to use satellite data as a monitoring tool. Four instruments are of interest in this study: the AVHRR, ATSR, SMMR, and SSM/I. Our objectives are as follows. Refine the existing AVHRR retrieval algorithm defined in Key and Haefliger (1992; hereafter KH92) and applied elsewhere. Develop a method for IST retrieval from ATSR data similar to the one used for SST. Further investigate the possibility of estimating surface temperature from passive microwave data (in conjunction with AVHRR clear sky samples) through the use of 'effective emissivities' and physical relationships between skin temperature and subsurface temperature. Use the general method outlined in MK93 to calculate a 12-year record of clear sky equivalent surface temperatures, or possibly all-sky snow-ice interface physical temperatures, from SMMR and SSM/I, compare these temperatures to climatologies, ECMWF modeled surface temperatures, and surface temperatures predicted by a 2-D ice model. And intercompare several ice surface retrieval methods and validate them against ground measurements from the Swiss Camp on the Greenland ice sheet. Additionally, we intend to develop a surface temperature product based on AVHRR data and possibly blended with drifting buoy and meteorological station temperatures.

Key, Jeff↗
NASA NTRS1995

Polarimetric measurements of sea surface brightness temperatures using an aircraft K-band radiometer

This paper presents the first experimental evidence that the polarimetric brightness temperatures of sea surfaces are sensitive to ocean wind direction in the incidence angle range of 30 to 50 degrees. Our experimental data were collected by a K-band (19.35 GHz) polarimetric wind radiometer (WINDRAD) mounted on the NASA DC-8 aircraft. A set of aircraft radiometer flights was successfully completed in November 1993. We performed circle flights over National Data Buoy Center (NDBC) moored buoys deployed off the northern California coast, which provided ocean wind measurements. The first WINDRAD flight was made on November 4, 1993. There was clear weather with a wind speed of 12 m/s at 330 degrees around the Pt. Arena buoy. We circled the buoy at three incidence angles, and all data when plotted as functions of azimuth angles show clear modulations of several Kelvin. At 40 degrees incidence angle, there is a 5 Kelvin peak-to-peak signal in the second Stokes parameter Q and the third Stokes parameter U. The Q data maximum is in the upwind direction and U has a 45 degrees phase shift in azimuth as predicted by theory. There is also an up/downwind asymmetry of 2 Kelvin in the Q data, and 1 Kelvin in the U data. At 50 degrees incidence angle, the collected data show very similar wind direction signatures to the SSM/I model function. Additional flights were made on other days under cloudy conditions. Data taken at a wind speed of 8 m/s show that at 40 degrees incidence Q and U have a smaller azimuthal modulation of 3 Kelvin, probably due to the lower wind speed. Additionally, the simultaneously recorded video images of sea surfaces suggested that Q and U data were less sensitive to unpolarized geophysical variations, such as clouds and whitecaps, while the T(v) and T(h) increased by a few Kelvin when the radiometer beam crossed over clouds, or there was a sudden increase of whitecaps in the radiometer footprint. The results of our aircraft flights indicate that passive polarimetric radiometry has a strong potential for global ocean wind speed and direction measurements from space.

Yueh, Simon H.↗
NASA NTRS1994

On the Validation of Satellite-Derived Sea Ice Surface Temperature

The surface temperature of sea ice controls the rate of ice growth and heat exchange between the ocean and the atmosphere. An algorithm for the satellite retrieval of ice surface temperature has recently been published, but due to the lack of validation data has not been extensively tested. In this paper, data from a recent Arctic field experiment is used in an attempt to validate that algorithm. While the procedure is, in principle, straightforward, we demonstrate that validation is complicated by a variety of factors, including incorrectly assumed atmospheric conditions, undetected clouds in the satellite data, spatial and temporal variability in the surface temperature field, and surface and satellite measurement errors. Comparisons between surface temperatures determined from upwelling broadband longwave radiation, spatial measurements of narrow-band radiation, thermocouples buried just below the snow surface, and narrow-band satellite data show differences of 1 to 3 deg. C. The range in these independent measurements indicates the need for specially designed validation experiments utilizing narrow-band radiometers on aircraft to obtain broad spatial coverage.

Key, J.↗
DOE OSTI2021

Greater committed warming after accounting for the pattern effect

Our planet’s energy balance is sensitive to spatial inhomogeneities in sea surface temperature and sea ice changes, but this is typically ignored in climate projections. Here, we show the energy budget during recent decades can be closed by combining changes in effective radiative forcing, linear radiative damping and this pattern effect. The pattern effect is of comparable magnitude but opposite sign to Earth’s net energy imbalance in the 2000s, indicating its importance when predicting the future climate on the basis of observations. Additionally, after the pattern effect is accounted for, the best-estimate value of committed global warming at present-day forcing rises from 1.31 K (0.99–2.33 K, 5th–95th percentile) to over 2 K, and committed warming in 2100 with constant long-lived forcing increases from 1.32 K (0.94–2.03 K) to over 1.5 K, although the magnitude is sensitive to sea surface temperature dataset. Further constraints on the pattern effect are needed to reduce climate projection uncertainty.

58 GEOSCIENCES↗
NASA NTRS1991

Biological control of surface temperature in the Arabian Sea

In the Arabian Sea, the southwest monsoon promotes seasonal upwelling of deep water, which supplies nutrients to the surface layer and leads to a marked increase in phytoplankton growth. Remotely sensed data on ocean color are used here to show that the resulting distribution of phytoplankton exerts a controlling influence on the seasonal evolution of sea surface temperature. This results in a corresponding modification of ocean-atmosphere heat exchange on regional and seasonal scales. It is shown that this biological mechanism may provide an important regulating influence on ocean-atmosphere interactions.

Sathyendranath, Shubha↗
NASA NTRS1982

A comparison of HCMM surface temperatures with in situ temperature data

All HCMM required were processed. Calibrated and atmospherically corrected sea surface temperatures were developed for the Nantucket Shoals and Gulf of Mexico regions. These data were analyzed and the sea surface temperatures along the various transacts were compared with in situ data. The comparisons indicate that there is, on the average, a root mean square difference between the in situ data and the HCMM sea surface temperatures of + or - 1.0 C. The linear correlation coefficient was 0.97.

Vukovich, F. M.↗
NASA NTRS1991

Errors of five-day mean surface wind and temperature conditions due to inadequate sampling

Surface meteorological reports of wind components, wind speed, air temperature, and sea-surface temperature from buoys located in equatorial and midlatitude regions are used in a simulation of random sampling to determine errors of the calculated means due to inadequate sampling. Subsampling the data with several different sample sizes leads to estimates of the accuracy of the subsampled means. The number N of random observations needed to compute mean winds with chosen accuracies of 0.5 (N sub 0.5) and 1.0 (N sub 1,0) m/s and mean air and sea surface temperatures with chosen accuracies of 0.1 (N sub 0.1) and 0.2 (N sub 0.2) C were calculated for each 5-day and 30-day period in the buoy datasets. Mean values of N for the various accuracies and datasets are given. A second-order polynomial relation is established between N and the variability of the data record. This relationship demonstrates that for the same accuracy, N increases as the variability of the data record increases. The relationship is also independent of the data source. Volunteer-observing ship data do not satisfy the recommended minimum number of observations for obtaining 0.5 m/s and 0.2 C accuracy for most locations. The effect of having remotely sensed data is discussed.

Legler, David M.↗