A C-band cross polarization geophysical model function

Hwang, Paul A.; Stoffelen, Ad; Zadelhoff, Gerd-Jan van; Perrie, William; Zhang, Biao; Li, Haiyan; Shen, Hui

doi:10.1109/igarss.2015.7325989

Cited by 1 publication

(5 citation statements)

References 11 publications

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“…We applied this resistance law to the dependencies of the cross‐polarized NRCS on U 10 from two data sets containing collocated satellite measurements of radar return and ground measurements of wind speed referred by Hwang et al () as BSH (wind data from Buoy, SFMR, and H*Wind sources; Zhang et al, ) and KNMIS (wind data from SFMR measurements assembled at KNMI; van Zadelhoff et al, , 2014). And as a result we obtained the dependence of σ 0VH on u * and θ shown in Figure .…”

Section: Toward the Cross‐polarization Gmf For Retrieval Of Hurricanementioning

confidence: 99%

“…Cross‐polarized radar return in linear units versus u * based on two data sets (BSH and KNMIS) analyzed by Hwang et al () containing collocated satellite measurements of cross‐pol C‐band normalized radar cross section and ground measurements of wind speed for different incident angles.…”

Section: Toward the Cross‐polarization Gmf For Retrieval Of Hurricanementioning

confidence: 99%

“…Figure shows the scatter plot of measured and inverted U 10 and u * for the GMF0 independent on incident angle (top panels) and GMF1 taking into account the dependence on incident angle (bottom panels). The experimental data for comparison were taken from the database (data sets BSH and KNMIS) by Hwang et al (). Obviously, taking into account the dependence on incident angle enables one to reduce the experimental errors.…”

Section: Toward the Cross‐polarization Gmf For Retrieval Of Hurricanementioning

confidence: 99%

“…Comparison of the retrieved with GMF0 (top row) and GMF1 (bottom row) and measured U 10 and u * retrieved by resistance law () from measured U 10 . The experimental data for comparison were taken from the database by Hwang et al (). The dashed curves show ±5‐m/s scattering for U 10 and ±0.25‐m/s scattering for u * .…”

Section: Toward the Cross‐polarization Gmf For Retrieval Of Hurricanementioning

confidence: 99%

“…This problem was recently solved with the use of the novel technology based on registration of the microwave power return from the water surface at cross polarization, which keeps sensitivity to wind speed at high winds (Fois et al, ; Vachon & Wolfe, ; van Zadelhoff et al, ; Zhang & Perrie, ; Zhang et al, ). Using collocated satellite measurements of cross‐polarized C‐band NRCS, σ 0 , and ground measurements of wind speed U 10 , (Hwang et al, ; Vachon & Wolfe, ; van Zadelhoff et al, ; Zhang & Perrie, ; Zhang et al, ) suggested the GMFs, that is, the empirical functions σ 0 ( U 10 ) fitting the data, applicable at high winds. This paper describes construction of GMF comprising the dependence σ 0 ( u * ), which can be used for direct retrieval of wind friction velocity from cross‐polarized NRCS.…”

Section: Introductionmentioning

confidence: 99%

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Cross‐Polarization GMF for High Wind Speed and Surface Stress Retrieval

et al. 2018

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This paper describes the construction of geophysical model function (GMF) for wind speed and surface stress retrieval at high winds from cross‐polarized radar backscatter at the water surface. The starting point is the laboratory experiment designed for the study of X‐band backscattering from water surface. In particular, it was shown that cross‐polarized normalized radar cross section (NRCS) keeps sensitivity to wind friction velocity at high winds alternatively to co‐polarized radar return. Basing on the analysis of the Doppler spectra and simultaneous measurements of parameters of surface waves, we suggest a hypothesis that at high winds the cross‐polarized backscattered signal is formed mainly due to scattering from wave breakers. The hypothesis is supported by the experimentally detected proportionality between the power of the scattered signal at cross polarization and the area swept by wave breakers. These results obtained in the laboratory environment are applied for constructing the similar dependencies for field conditions. Using the phenomenological statistical physics approach, a parameterization of active whitecap coverage fraction dependence on wind friction velocity is suggested. With the use of this parameterization, the empirical function expressing the cross‐polarized NRCS by u* is derived. Using the surface drag parameterization applicable at strong winds, this dependence is verified on the base of available data sets containing collocated satellite measurements of cross‐polarized C‐band NRCS and ground measurements of wind speed. GMFs for u* and U10 retrieval are suggested. Analysis shows that taking into account the angular dependence of cross‐polarized radar backscattered power improves the accuracy of wind speed and wind friction velocity retrieval.

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