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At least 199 records · Page 11

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NASA NTRS1976

The nature of multiple solutions for surface wind speed over the oceans from scatterometer measurements

The satellite SEASAT-A will carry a radar scatterometer in order to measure microwave backscatter from the sea surface. From pairs of radar measurements at angles separated by 90 deg in azimuth the surface wind speed and direction may be inferred, though not uniquely. In this paper the character of the solutions for wind speed and direction is displayed, as well as the nature of the ambiguities of these solutions. An economical procedure for handling such data is described, plus a criterion for the need for conventional (surface) data in order to resolve the ambiguities of solutions.

Price, J. C.↗

NASA NTRS1975

Scatterometer receiver dynamic range/linearity

Results of an investigation aimed at determining the dynamic range and linearity of the S-193 scatterometer receiver from data acquired during Skylab missions 2 and 3 are summarized.

Rosenkranz, W. A.↗

NASA NTRS1977

Scatterometer results from shorefast and floating sea ice

Multipolarized scatterometer sea ice measurements at 13.3 GHz obtained during the winter and spring of 1975-76 from a number of flight lines off the east coast of Canada were analyzed. Radar scattering coefficients, sigma, were calculated for several regions of sea ice as interpreted from aerial photographs. The variation in sigma which incidence angle is presented for HH (Horizontal transmit - Horizontal receive) and HV (Horizontal transmit - Vertical receive) polarizations for the various ice regions. The depolarization ratio (sigma HH/sigma HV) as a function of incidence angle is also given. The sea ice regions studied included shorefast ice with varying degrees of snow cover and surface roughness and several varieties of floating sea ice with different thicknesses.

Cihlar, J.↗

NASA NTRS1977

A two-scale scattering model with application to the JONSWAP '75 aircraft microwave scatterometer experiment

The general problem of bistatic scattering from a two scale surface was evaluated. The treatment was entirely two-dimensional and in a vector formulation independent of any particular coordinate system. The two scale scattering model was then applied to backscattering from the sea surface. In particular, the model was used in conjunction with the JONSWAP 1975 aircraft scatterometer measurements to determine the sea surface's two scale roughness distributions, namely the probability density of the large scale surface slope and the capillary wavenumber spectrum. Best fits yield, on the average, a 0.7 dB rms difference between the model computations and the vertical polarization measurements of the normalized radar cross section. Correlations between the distribution parameters and the wind speed were established from linear, least squares regressions.

Wentz, F. J.↗

NASA NTRS1978

SeaSat-A Satellite Scatterometer (SASS) Validation and Experiment Plan

This plan was generated by the SeaSat-A satellite scatterometer experiment team to define the pre-and post-launch activities necessary to conduct sensor validation and geophysical evaluation. Details included are an instrument and experiment description/performance requirements, success criteria, constraints, mission requirements, data processing requirement and data analysis responsibilities.

Schroeder, L. C.↗

NASA NTRS1978

Measurement of soil moisture trends with airborne scatterometers

The author had identified the following significant results. Repeated looks at surfaces that maintain constant roughness can provide an estimate of soil moisture in the surface, when appropriate radar look angles are used. Significant influence due to differences in soil moisture can be detected in the 13.3 GHz and 1.6 GHz scatterometer returns. Effects of normal crop densities have little influence on the surface soil moisture estimate, when appropriate look angles are used. It appears that different look angles are optimum for different frequencies to avoid effects from vegetation. Considering the frequency and look angles used on the Seasat-A imaging radar, differences in soil moisture should produce as much as 9 db difference in return on that system.

Blanchard, B. J.↗

NASA NTRS1977

Comparisons of some scattering theories with recent scatterometer measurements

The paper compares the predictions of two different types of sea scatter theories with recent scatterometer measurements which indicate the variations of the backscattering coefficient with polarization, incident angle, wind speed, and azimuth angle. Wright's theory (1968) differs from that of Chan and Fung (1977) in two major aspects: (1) Wright uses Phillips' sea spectrum (1966) while Chan and Fung use that of Mitsuyasu and Honda, and (2) Wright uses a modified slick sea slope distribution by Cox and Munk (1954) while Chan and Fung use the slick sea slope distribution of Cox and Munk defined with respect to the plane perpendicular to the look direction. Satisfactory agreements between theory and experimental data are obtained when Chan and Fung's model is used to explain the wind and azimuthal dependence of the scattering coefficient.

Fung, A. K.↗

NASA NTRS1979

Seasat scatterometer - Results of the Gulf of Alaska workshop

The Seasat microwave scatterometer was designed to measure, globally and in nearly all weather, wind speed to an accuracy of plus or minus 2 meters per second and wind direction to plus or minus 20 deg in two swaths 500 kilometers wide on either side of the spacecraft. For two operating modes in rain-free conditions, a limited number of comparisons to high-quality surface truth indicates that these specifications may have been met.

Jones, W. L.↗

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 NTRS1981

Verification studies of Seasat-A satellite scatterometer /SASS/ measurements

Two comparisons between Seasat-A satellite scatterometer (SASS) data and surface truth, obtained from the Gulf of Alaska Seasat Experiment and the Joint Air-Sea Interaction program, have been made to determine the behavior of SASS and its algorithms. The performance of SASS was first evaluated irrespective of the algorithms employed to convert the SASS data to geophysical parameters, which was done by separating the backscatter measurements into small bins of incidence and azimuth angles and polarity and regression against wind speed measurements. The algorithms were then tested by comparing their predicted slopes and y intercepts with those derived from the regressions, and by comparing each SASS backscatter measurement with the backscatter derived from the algorithms, and the given wind velocity from the observations. It was shown that SASS was insensitive to winds at high incidence angles for horizontal polarizations. Fairly high correlations were found between backscatter and wind speeds. The algorithms functioned well at mid-ranges of incidence angle and backscattering coefficient.

Halberstam, I.↗

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

AgRISTARS. Supporting research: MARS x-band scatterometer

The design, construction, and data collection procedures of the mobile agricultural radar sensor (MARS) x band scatterometer are described. This system is an inexpensive, highly mobile, truck mounted FM-CW radar operating at a center frequency of 10.2 GHz. The antennas, which allow for VV and VH polarizations, are configured in a side looking mode that allows for drive by data collection. This configuration shortens fieldwork time considerably while increasing statistical confidence in the data. Both internal calibration, via a delay line, and external calibration with a Luneberg lens are used to calibrate the instrument in terms of sigma(o). The radar scattering cross section per unit area, sigma(o), is found using the radar equation.

Ulaby, F. T.↗

NASA NTRS1981

Evaluation of the Seasat wind scatterometer

Surface wind velocities have been derived from backscatter measurements of the ocean surface made by a satellite-borne, microwave sensor. Comparisons with high-quality surface-based measurements obtained during the Joint Air-Sea Interaction experiment are described. The accuracy of the scatterometer winds at this mid-latitude site, + or 1.6 m/s in speed and + or - 18 deg in direction, for winds between 3 and 16 m/s is within the design specification.

Jones, W. L.↗

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 NTRS1982

The Seasat-A satellite scatterometer - The geophysical evaluation of remotely sensed wind vectors over the ocean

A description is given of the algorithm used to convert Seasat-A satellite microwave scatterometer measurements of ocean normalized radar cross section to the neutral stability vector wind at 19.5 m height, as well as to compare these winds with high-quality surface observations. The wind vector algorithm used an empirical normalized radar cross section model function to describe the ocean normalized radar cross section's dependence on the 19.5-m neutral stability wind vector. In addition, two model functions were evaluated by means of an independent set of in situ surface wind observations from the Joint Air Sea Interaction experiment (JASIN). Better results were produced by these comparisons than the stipulated Seasat wind speed and direction accuracy specifications of + or - 2 m/sec and + or - 20 deg, respectively, over the 0-16 m/sec range of winds observed during JASIN.

Jones, W. L.↗

NASA NTRS1982

Evaluation of atmospheric attenuation from SMMR brightness temperature for the Seasat satellite scatterometer

The effect of attenuation in precipitation regions of the sea, which must be considered in order to measure the radar backscatter from the ocean with sufficient accuracy to allow determination of the wind vector, can be ascertained from a knowledge of the brightness temperature observed by a microwave radiometer such as the Seasat multifrequency scanning radiometer. Two algorithms relating radiometric measurements and attenuation, and thereby correcting measured scattering coefficient values, were compared with wind vectors reported by surface observers and those determined by the Seasat scatterometer measurements with and without correction for atmospheric attenuation. Although the attenuation correction yields some improvements, it is constrained by both radiometer footprint differences and different scan patterns.

Moore, R. K.↗

NASA NTRS1981

Microwave scatterometer measurements of oceanic wind vector

Results from Seasat-A scatterometer (SASS) remote sensing of oceanic wind vectors are reviewed, together with the theory of radar backscattering. The SASS was designed to measure the surface wind stress and neutral stability wind vector at 19.5 m altitude. Requirements included windspeeds from 4-24 m/sec to within 2 m/sec or 10%, a 1000 km swath, directions from 0-360 deg to within 20 deg, a 50 km resolution cell, and cross-track and along-track spacing between resolution cells of 100 km. The method was based on Bragg scattering of microwaves from cm-length capillary ocean waves. The strength of the backscatter is proportional to the capillary wave amplitude, which is in equilibrium with the ocean surface wind speed. The measurement grouping, least-squares estimator, and dB deviation model function table for the SASS geophysical algorithm are discussed. Comparisons of SASS, GOASEX, and ground truth wind data are made, and a 0.92 correlation between SASS and ground truth data is determined from regression analysis.

Jones, W. L.↗