A SAR spectral model to retrieve sea state information

2019 Living Planet Symposium, 13-17 May 2019, Milan, ItalyLocal winds and faraway storms ocean waves that can be classified into two categories: wind waves and swell [1]. When wind starts blowing over the ocean, initially short-wavelength waves (capillary waves) are created. As the wind keeps blowing, progressively more energy is added into the system (sea) which generate waves characterized by longer wavelengths. The wave system can be described by a wave spectrum which carries on information about the energy associated with the ocean waves [1]. If the wind blows enough in terms of duration and fetch, a final stage is reached where no more energy can be added by the wind and swell waves generate. The ocean wave spectrum includes both wind waves and swell. The wind-sea part of the spectrum is affected by local wind, while the swell could be generated somewhere else. For a very large fetch and very long wind action time, fully developed sea state conditions are achieved. In this case, the sea is usually defined as stationary or saturated. However, the non-fully developed sea state is the most frequent condition, due to the presence of geographical boundary or any condition that changes the wind speed or the wind direction. Operationally, in order to design simple and effective spectral-based methods aimed at retrieving geophysical parameters (e.g.; significant wave height, wind, etc.) the fully developed sea state conditions is assumed, i.e.; the wind is supposed to blow for such a long time and over such a long distance that an equilibrium state is reached that depends only on the wind speed [2]. From an operational viewpoint, the assumption of fully-developed sea state conditions simplifies significantly the retrieval of geophysical parameters. In fact, under non-fully sea states conditions, sea surface characteristics that are not directly related to the local wind need to be considered [2]. Hence, it is important to characterize sea state conditions to both design retrieval techniques and to correctly interpret the retrieved parameters. In this study, a spectral method, which is based on the peculiarities of Synthetic Aperture Radar (SAR) imaging of ocean surface, is proposed to provide a fine spatial resolution inverse wave age map. To the best of our knowledge, no study related to SAR-based estimation of inverse wave age has been conducted. We propose a novel approach that consists of analyzing the departure of autocorrelation function (ACF) measured from the SAR image to its Gaussian fit. The departure is then related to the inverse wave age using a χ2 test. In particular, the sensitivity of χ2 to inverse wave age (Ω) is discussed by introducing a normalized Ω, ωp = 1.2Ω, which is such that when Ω = 0.84, i.e.; under fully developed sea state conditions, ωp = 1. Preliminary results, obtained processing a large dataset of Sentinel-1A VV polarized Ground Range Detection (GRD) StripMap images collected from November 2014 up to April 2015 in the East Atlantic and off the Hawaii at 10 m resolution, show a good correlation between χ2 estimates and the inverse wave age obtained using European Centre for medium-range weather forecasts (ECMWF) products collocated with the SAR dataset. [1] D. Ganguly, M.K. Mishra, and P. Chauhan, “Deriving sea-state parameters using RISAT-1 SAR data,” Adv. Space Res., vol. 55, no.1, pp. 83-89, 2015. [2] A. Guissard, C.Baufays, and P. Sobieski, “Fully and Nonfully Developed Sea Models for Microwave Remote Sensing Applications,” Remote Sens. Environ., vol. 48, pp. 25-38, 199