The necessity for a new parameterization of an empirical model for wind/ocean scatterometry

Abstract

This study reveals that the power‐law form of the Seasat A scatterometer system (SASS) empirical backscatter‐to‐wind model function (SASS 1), when combined with the sum‐of‐squares (SOS) wind retrieval algorithm, does not uniformly meet the instrument performance specification requirements. Analysis indicates that the horizontally polarized (Hpol) and vertically polarized (Vpol) components of the benchmark SASS 1/SOS wind retrieval system relating signal strength (backscatter) to wind speed 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. An approach is presented that differs from previous calibration studies: here the internal Vpol versus Hpol consistency of the model is examined by the use of a set of pairwise collocated SASS‐produced winds, where one member of a wind pair (UVV) derives from only Vpol backscatter measurements and the other (UHH) from only Hpol measurements. This data set was created by extracting from the Seasat mission Geophysical Data Record (GDR) data base all pairs of SASS winds of the form (UVV, UHH) such that UVV and UHH are observations separated by no more than 5 min and 50 km. The set contains 377,289 such pairs. Comparisons of SASS 1/SOS derived wind data with wind data taken off the coast of Scotland during JASIN and with wind data from NDBO buoys off the U.S. Atlantic, Pacific, and Gulf coasts further underscores the shortcomings of the SASS 1/SOS wind retrieval system. These in situ wind comparisons to SASS indicate geographical differences in the retrieved scatterometer winds that are potentially attributable to environmental differences such as sea surface temperature. Taken together, the in situ comparisons to SASS, and the SASS Hpol to Vpol wind intercomparison indicate that the SASS 1/SOS wind retrieval system appears deficient in retrieving some winds, particularly from backscatter measurements made at higher incidence angles. We also find that Hpol backscatter measurements show greater sensitivity than Vpol backscatter measurements to wind speed variations above 10 m s−1, while the reverse holds for wind speeds less than 10 m s−1. It should be emphasized that it is the geophysical algorithms that lead to the errors cited here, not the instrumentation or the principles of scatterometry. In displaying these sources of error we have been obliged to outline the algorithmic methodology in a manner of presentation not previously attempted either in the published literature or in the voluminous code documentations. We hope that this material will be of value in itself to users of scatterometer data who seek to enhance their understanding of how such data are derived.

Radar scattering and equilibrium ranges in wind‐generated waves with application to scatterometry

“…In a recent paper, Woiceshyn et al [1986] have shown that the transfer (or model) functions used for horizontal incidenthorizontal scattered polarization (electric field vector perpendicular to the plane of incidence, abbreviated HH) are inconsistent with those used for vertical-vertical polarization (abbreviated V V). The differences in estimated wind speeds are quite large (up to 9 m s-• for high winds) and imply perhaps that the process of deducing the wind from the backscatter measurements was partially incorrect, that the model functions, avvø(•, Z, 0) and aHHø(•, Z, 0), when combined with the sum of squares (SOS) wind recovery algorithm [Jones et al, 1982;Pierson, 1984] were in error; or that a combination of both caused the discrepancies.…”

A laboratory study of friction-velocity estimates from scatterometry: low and high regimes

“…The Seasat scatterometer wind-retrieval algorithm met system accuracy specifications in an overall sense; however, an error analysis by Woiceshyn et al (1986) reveals systematic biases at low and high winds. Wind-speed estimates apparently did not uniformly meet performance criteria.…”

Dependence of radar backscatter on the energetics of the air-sea interface

“…Observational evidence for the long wave influence has been reported by Keller, et al, (1985Keller, et al, ( ,1989 Figure 2d). Wind Speed for Various Angles of Incidence, 9 ; b) Wind Direction (Jones, et al 1977); c) Long Wave Slope (Keller, et al, 1985); d) Atmospheric Stratification Unstable atmospheric stratification, as indicated by a negative air-sea temperature difference (Figure 2d), results in 1) a slightly higher near-surface (Lamb, 1932) which is an inverse function of water temperature; therefore, this mechanism has been proposed to explain observations which show an increase in the radar backscatter for increasing surface temperature, particularly at low wind speeds (Woiceshyn, et al, 1986;Donelan and Pierson, 1987;Kahma and Donelan, 1988 (Tsanis and Donelan, 1987 (October-December, 1985, the tower was outfitted with instruments to study wave spectra, wind (Huhnerfuss, 1983;Hughes and Gower, 1983), surface currents (Phillips, 1981), and the surface adjustment due to topographic interactions in shallow coastal areas (Valenzuela, 1985). (Geernaert, 1990).…”

“…The determination that o°was in some way proportional to wind speed led to the proposal for a satellite-borne radar, by then known as a scatterometer, to obtain oceanic wind and wave information (Moore and Pierson, 1966 (Woiceshyn, et al, 1986 Reiterating the need for an improved, all-weather oceanic data base, the Navy proposed N-ROSS (Navy Remote Ocean Sensing System), a supposedly "scaled-down" version of NOSS, in April, 1981(Honhart, 1984 December, 1986(Graham, 1987Matthews; With these changes the scatterometer will become a far more attractive instrument in a programmatic sense (Brown and McCandless, 1988) (Rice, 1951;Barrick, 1968;Wright, 1966Wright, , 1968Valenzuela, 1968Valenzuela, , 1978Fung and Chan, 1969;Keller and Wright, 1975;Brown, 1978;Bahar, 1981;Durden and Vesecky, 1985;Plant, 1986;Holliday, 1986;Donelan and Pierso^i, 1987). To date, the three most common approaches to scattering problems are physical optics, small perturbation and two-scale composite surface methods^.…”

“…(1) cross-section dependence on wave slope and wave direction relative to the wind vector (Keller, et al, 1985Li, et al, 1989), (2) cross-section dependence on air-sea temperature difference, and thus on stability of the marine surface layer (e.g., Keller, et al, 1989), (3) a lack of self-consistency of the model between vertical and horizontal polarizations (Wentz, 1984;Woiceshyn, et al, 1986), (4) decreased sensitivity of the model function at low wind speeds (below 7 m/s), (Woiceshyn, et al, 1986), (5) cross-section dependence on surface contaminants and films (Huhnerfuss, et al, 1983), and (6) cross-section dependence on viscosity of the water as a function of temperature (Woiceshyn, 1986;Donelan and Pierson, 1987 If the short waves are tilted towards the radar and modulated in amplitude and frequency by the slope of the longer waves on which they ride, the NRCS will again be increased (Figure 2c). Observational evidence for the long wave influence has been reported by Keller, et al, (1985Keller, et al, ( ,1989 Figure 2d).…”