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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 55 records · Page 3
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NASA NTRS1984

A model function for ocean radar cross sections at 14.6 GHz

The relationship between the ocean's normalized radar cross section (NRCS) at 14.6 GHz and the surface wind vector is derived using the 3 months of Seasat microwave scatterometer (SASS) measurements. The derivation is based on the statistics of the SASS observations, and no in situ measurements are required, other than a mean global wind speed, which comes from climatology. The frequency distribution of the global wind vectors observed by SASS is assumed to be a bivariate normal probability function. A NRCS model function is found that maps the assumed wind vector statistics into the observed SASS NRCS statistics. This function is compared with a NRCS model coming from the Joint Air Sea Interaction Experiment (JASIN) and with aircraft scatterometer measurements. The results indicate that the statistically derived NRCS model is an improvement over the JASIN model, which was based on a limited number of in situ anemometer measurements.

Wentz, F. J.↗
NASA NTRS1985

Seasat microwave wind and rain observations in severe tropical and midlatitude marine storms

Initial results of studies concerning Seasat measurements in and around tropical and severe midlatitude cyclones over the open ocean are presented, together with an assessment of their accuracy and usefulness. Complementary measurements of surface wind speed and direction, rainfall rate, and the sea surface temperature obtained with the Seasat-A Satellite Scatterometer (SASS), the Scanning Multichannel Microwave Radiometer (SMMR), and the Seasat SAR are analyzed. The Seasat data for the Hurrricanes Fico, Ella, and Greta and the QE II storm are compared with data obtained from aircraft, buoys, and ships. It is shown that the SASS-derived wind speeds are accurate to within 10 percent, and the directions are accurate to within 20 percent. In general, the SASS estimates tend to measure light winds too high and intense winds too low. The errors of the SMMR-derived measurements of the winds in hurricanes tend to be higher than those of the SASS-derived measurements.

Black, P. G.↗
NASA NTRS1980

Seasat: - JASIN workshop report. Volume 1: Findings and conclusions

Data acquired from the Joint Air-Sea Interaction (JASIN) Experiment and Seasat data from overpasses that covered the JASIN area were compared and evaluated. The JASIN data were used as a high quality withheld data set. The Seasat data were prepared for each instrument: the Seasat-A Satellite Scatterometer (SASS), the Scanning Multichannel microwave radiometer (SMMR), and the synthetic aperture radar (SAR). The following results demonstrate the performance of Seasat: it was possible to identify mesoscale systems with the SASS as well as fronts; the SMMR provided accurate water vapor content of the atmosphere; the SAR showed evidence of helical rolls in the marine boundary layer; a SASS anomaly could be traced back to thunderstorm activity.

Source record↗
NASA NTRS1982

The relationship between wind vector and normalized radar cross section used to derive Seasat-A Satellite Scatterometer winds

The Seasat-A Satellite Scatterometer (SASS) ocean normalized radar cross section (NRCS) dependence on the 19.5-m neutral stability wind vector may be specified as a function of radar incidence angle, the angle between wind direction and radar azimuth, and the neutral stability wind speed expressed in m/sec at a height of 19.5 m. An account is given of the development of models both expressing this relationship and providing the basis of inversion of NRCS to SASS winds, from initially aircraft scatterometer measurement-based forms to three Seasat field-validation experiments which furnish model NRCS versus surface windspeed data for comparison with SASS data.

Schroeder, L. C.↗
NASA NTRS1984

A new parameterization of an empirical model for wind/ocean scatterometry

The power law form of the SEASAT A Scatterometer System (SASS) empirical backscatter-to-wind model function does not uniformly meet the instrument performance over the range 4 to 24 /ms. Analysis indicates that the horizontal polarization (H-Pol) and vertical polarization (V-Pol) components of the benchmark SASS1 model function yield self-consistent results only for a small mid-range of speeds at larger incidence angles, and for a somewhat larger range of speeds at smaller incidence angles. Comparison of SASS1 to in situ data over the Gulf of Alaska region further underscores the shortcomings of the power law form. Finally, a physically based empirical SASS model is proposed which corrects some of the deficiencies of power law models like SASS1. The new model allows the mutual determination of sea surface wind stress and wind speed in a consistent manner from SASS backscatter measurements.

Woiceshyn, P. M.↗
NASA NTRS1986

A simple, objective analysis scheme for scatterometer data

A simple economical objective analysis scheme is devised and tested on real scatterometer data. It is designed to treat dense data such as those of the Seasat A Satellite Scatterometer (SASS) for individual or multiple passes, and preserves subsynoptic scale features. Errors are evaluated with the aid of sampling ('bootstrap') statistical methods. In addition, sensitivity tests have been performed which establish qualitative confidence in calculated fields of divergence and vorticity. The SASS wind algorithm could be improved; however, the data at this point are limited by instrument errors rather than analysis errors. The analysis error is typically negligible in comparison with the instrument error, but amounts to 30 percent of the instrument error in areas of strong wind shear. The scheme is very economical, and thus suitable for large volumes of dense data such as SASS data.

Levy, G.↗
NASA NTRS1987

Archival of Seasat-A satellite scatterometer data merged with in situ data at selected, illuminated sites over the ocean

A large data base of Seasat-A Satellite Scatterometer (SASS) measurements merged with high-quality surface-truth wind, wave, and temperature data has been documented. The data base was developed for all times when selected in situ measurement sites were within the SASS footprint. Data were obtained from 42 sites located in the coastal waters of North America, Australia, Western Europe, and Japan and were assembled by correlating the SASS and surface-truth measurements in both time and distance. These data have been archived on a set of nine-track 6250 bpi ASCII coded magnetic tapes, which are available from the National Technical Information Service.

Schroeder, Lyle C.↗
NASA NTRS1988

Scatterometer wind speed bias induced by the large-scale component of the wave field

In order to determine if an environmental bias exists in the winds measured by the Seasat A satellite scatterometer (SASS), the SASS wind speed observations, U(s), colocated with the buoy wind speed data, U(b), were analyzed. There was a trend in the SASS wind speed error, U(b) - U(s), which was found to be related to the degree of the development of wind-generated gravity waves; this trend (estimated to be 0.5 m/sec per 100 km of the generalized wind fetch) is capable of introducing a well-pronounced environmental bias into the scatterometer-produced global distributions of wind.

Glazman, R. E.↗
NASA NTRS1993

Wind field model-based estimation of Seasat scatterometer winds

A model-based approach to estimating near-surface wind fields over the ocean from Seasat scatterometer (SASS) measurements is presented. The approach is a direct assimilation technique in which wind field model parameters are estimated directly from the scatterometer measurements of the radar backscatter of the ocean's surface using maximum likelihood principles. The wind field estimate is then computed from the estimated model parameters. The wind field model used in this approach is based on geostrophic approximation and on simplistic assumptions about the wind field vorticity and divergence but includes ageostrophic winds. Nine days of SASS data were processed to obtain unique wind estimates. Comparisons in performance to the traditional two-step (point-wise wind retrieval followed by ambiguity removal) wind estimate method and the model-based method are provided using both simulated radar backscatter measurements and actual SASS measurements. In the latter case the results are compared to wind fields determined using subjective ambiguity removal. While the traditional approach results in missing measurements and reduced effective swath width due to fore/aft beam cell coregistration problems, the model-based approach uses all available measurements to increase the effective swath width and to reduce data gaps. The results reveal that the model-based wind estimates have accuracy comparable to traditionally estimated winds with less 'noise' in the directional estimates, particularly at low wind speeds.

Long, David G.↗
NASA NTRS1979

Design study for future satellite microwave scatterometers, part 3

A computerized simulation analysis for a number of scatterometer antenna configuration and polarization modes including the Seasat scatterometer (SASS) is presented. The results of the simulations were expressed in terms of performance statistics. These statistics relate to the wind direction alias removal capability and to the rms sensing errors for friction velocity and wind direction X. The statistics are analyzed, and optimum scatterometer configurations are recommended. The accuracy of the SASS in measuring U* and X, and its capability to resolve wind direction aliases are assessed.

Wentz, F. J.↗
NASA NTRS1980

Development and usage of a false color display technique for presenting Seasat-A scatterometer data

A computer generated false color program which creates digital multicolor graphics to display geophysical surface parameters measured by the Seasat-A satellite scatterometer (SASS) is described. The data is incrementally scaled over the range of acceptable values and each increment and its data points are assigned a color. The advantage of the false color display is that it visually infers cool or weak data versus hot or intense data by using the rainbow of colors. For example, with wind speeds, levels of yellow and red could be used to imply high winds while green and blue could imply calmer air. The SASS data is sorted into geographic regions and the final false color images are projected onto various world maps with superimposed land/water boundaries.

Jackson, C. B.↗
NASA NTRS1980

Some considerations in the evaluation of Seasat-A scatterometer /SASS/ measurements

A study is presented of the geophysical algorithms relating the Seasat-A scatterometer (SASS) backscatter measurements with a wind parameter. Although these measurements are closely related to surface features, an identification with surface layer parameters such as friction velocity or the roughness length is difficult. It is shown how surface truth in the form of wind speeds and coincident stability can be used to derive friction velocity or the equivalent neutral wind at an arbitrary height; it is also shown that the derived friction velocity values are sensitive to contested formulations relating friction velocity to the roughness length, while the derived values of the equivalent neutral wind are not. Examples of geophysical verification are demonstrated using values obtained from the Gulf of Alaska Seasat Experiment; these results show very little sensitivity to the type of wind parameter employed, suggesting that this insensitivity is mainly due to a large scatter in the SASS and surface truth data.

Halberstam, I.↗
NASA NTRS1980

Seasat-A satellite scatterometer instrument evaluation

The Seasat-A satellite scatterometer (SASS) was designed to measure ocean surface wind speed and direction in twenty-four independent cells over a 1000-km swath. It operated in the interrupted CW mode at a frequency of 14.6 GHz with four fan beam antennas and used Doppler filtering in the receiver for resolving the cells on the surface. The instrument began operating in space on July 6, 1978, and gathered normalized radar cross section data for approximately 2290 h. The purpose of this paper is to describe the in-orbit evaluation of the SASS hardware and its compatibility with the spacecraft. It has been determined that the scatterometer operated flawlessly throughout the mission, met all design requirements, and established a good data base for geophysical processing.

Johnson, J. W.↗
NASA NTRS1981

Seasat SAR cross-section modulation by surface winds - GOASEX observations

Seasat radar observations of the Gulf of Alaska by the Synthetic Aperture Radar (SAR) and the Wind Speed Scatterometer (SASS) indicate that L-band backscatter is modulated by wind speed and possibly by wind direction. It is noted that the L-band backscatter is approximately proportional to the square root of surface winds and that upwind/crosswind differences in backscatter can be as large as 10% in the range of these wind speeds. It is suggested that Seasat SAR images, in conjunction with Seasat Scatterometer data may provide fine-scale mapping of ocean winds and directions. The need for further Seasat SAR-SASS comparisons in order to extend the range of wind speeds is stressed.

Thompson, T. W.↗
NASA NTRS1982

SEASAT: A satellite scatterometer illumination times of selected in situ sites

A list of times that the SEASAT A Satellite Scatterometer (SASS) illuminated from directly above or directly abeam, selected surface sites where in situ winds were measured is provided. The list is ordered by the Greenwich Mean Time (GMT) of the midpoint of the illumination period (hit time) for a given surface site. The site identification, the orbit number and the direction from the subtrack in which the truth lies are provided. The accuracy of these times depends in part upon the ascending node times, which are estimated to be within +.1 sec, and on the illumination time relative to the ascending node, which is estimated to be within +6 seconds. The uncertainties in the times provided were judged to be sufficiently small to allow efficient and accurate extraction of SASS and in situ data at the selected surface sites. The list contains approximately six thousand hit times from 61 geographically dispersed sites.

Schroeder, L. C.↗
NASA NTRS1981

Interactive processing of SEASAT scatterometer data

The Man-computer Interactive Data Access System (McIDAS), adapted for the interactive processing of satellite-derived temperature soundings and cloud-track winds for the FGGE Special Effort, was adapted for the processing and evaluation of SEASAT data. The implementation of the McIDAS SEASAT processing system required (1) extensive modifications to the data base structure to store and display SASS winds, as well as corroborative level II data, model first guess fields and level III analyses, and (2) the development of software to dealias and analyze SASS wind vectors interactively.

Atlas, R.↗
NASA NTRS1981

Anomalous wind estimates from the Seasat scatterometer

The Seasat-A Satellite Scatterometer (SASS) measured the radar backscatter intensity from the sea surface using a four-beam microwave antenna. Estimates of wind speed and direction derived from these data agree well with surface measurements made during the Joint Air-Sea Interaction experiment, but there are occasions (3 out of 23 satellite passes) when the results are anomalous. One such occasion when the satellite measurements differed substantially from those at the surface of the sea has been studied, and it has been concluded that the interpretation of the SASS measurements may have been vitiated by a mid-level convective system deep enough to produce thunderstorms and lightning.

Guymer, T. H.↗
NASA NTRS1983

Evaluation of Seasat SMMR wind speed measurements

The Seasat scanning multichannel microwave radiometer (SMMR) is able to measure the wind speed at the ocean surface through the change in ocean surface microwave emissivity caused by the wind. In this paper the SMMR-derived wind speeds are compared to the wind speeds derived from an active microwave scatterometer also aboard the Seasat, the Seasat A scanning scatterometer (SASS). Four orbits that passed over the severe storm that damaged the Queen Elizabeth II are examined in detail. These orbits and five others were used to investigate effects which degrade the SMMR wind retrievals. When the data are filtered for such effects, it is found that the SMMR winds agree with the SASS winds with a scatter (1 sigma) of less than 2 m/s about a bias of 1 to 2 m/s.

Cardone, V.↗