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Numericalwavemodels are powerful tools for investigating globalwave climate. Here a global wave hindcast is employed to estimate the global pattern of crossing swells. However, the global patterns of crossing swells derived from the model are different from those derived from the synthetic aperture radar (SAR) wave mode products of quasi-linear inversion, indicating one of them is questionable. The comparison shows that the first two most energetic swells inversed by SAR are often not in accordance with the first two most energetic swells in the model, and this will have a large impact on the statistics of the data. Before this problem is solved, SAR wave products of quasi-linear inversion should be treated with care in wave climate studies. [ABSTRACT FROM AUTHOR]

Modeling the statistical distribution of synthetic aperture radar (SAR) images is essential for sea target detection, which is an important aspect of marine SAR applications. The main goal of this study is to determine the effects of sea states and surface wave texture characteristics on the statistical distributions of sea SAR images. A statistical analysis of the Envisat Advanced Synthetic Aperture Radar (ASAR) wave mode images (imagettes), covering a variety of sea states and wave conditions, was carried out to investigate the suitability of the statistical distributions often used in the literature for sea states parameters. The results revealed the variation in the distribution parameters in terms of their azimuthal cutoff wavelength (ACW) and the peak-to-background ratio (PBR) of the SAR image intensity spectra. The shape parameters of Gamma and Weibull distribution are sensitive and monotonously decreasing with respect to PBR, while the scale parameter is sensitive to ACW. The K distribution was shown to perform well, with both high and stable accuracy. The results of this paper provide a parameterized scheme for sea state classifications and can potentially be used for choosing the most suitable distribution model according to sea state when performing sea target detection. [ABSTRACT FROM AUTHOR]