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A New Ocean SAR Cross‐Spectral Parameter: Definition and Directional Property Using the Global Sentinel‐1 Measurements
Author(s) -
Li Huimin,
Chapron Bertrand,
Mouche Alexis,
Stopa Justin E.
Publication year - 2019
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1029/2018jc014638
Subject(s) - swell , wind wave , synthetic aperture radar , remote sensing , geology , wind speed , wind wave model , parameter space , wavelength , radar , doppler effect , surface wave , wind direction , meteorology , geodesy , computer science , physics , optics , mathematics , telecommunications , oceanography , statistics , astronomy
Space‐borne synthetic aperture radar (SAR) measurements have already been proven to be invaluable in detecting and quantifying properties of ocean swell systems. With the improved spatial resolution, Sentinel‐1 wave mode measurements can further be extended toward shorter‐scale waves, that is, within the surface wave equilibrium range. In this study, a new parameter is derived from filtering SAR image cross‐spectra around range‐traveling intermediate wind waves (wavelengths 15–20 m). This parameter captures both the radar cross‐section variability and its time evolution. Given the dependence of intermediate waves on local wind field, this parameter is statistically documented to confirm its sensitivity to both wind speed and wind direction. Comparable to Doppler estimate, the signed parameter can be used to reduce the wind direction ambiguity in the inversion of high‐resolution wind fields from SAR imagery. In addition, under complex environmental situations over a polar low event, this parameter is expected to better capture the dynamics of the surface wind. Globally, our analysis demonstrates regional and seasonal variations of this parameter, associated with those of wind/wave patterns. In particular, its directionality reveals the seasonal migration of intertropical convergence zone. This parameter is valuable to various further applications, for example, to help develop wind retrieval scheme from SAR measurements or to map space‐time variability of ocean waves at various wavelengths.