Abstract
The microwave scatterometer is one of the most effective instruments in ocean remote sensing, which urges the need for some theoretical models to accurately estimate the scattering coefficient of the sea surface. For the simulation of the scattering from an ocean surface, the sea spectrum, or its inverse Fourier transform, autocorrelation function is essential. Currently, many sea spectral models have been proposed for describing sea waves. However, which spectrum should be adopted during electromagnetic (EM) computations? A systematic comparison of these models is needed to evaluate their accuracies. In this paper, we focus on numerical simulations of scattering from a rough sea surface in monostatic and bistatic configurations by using six different sea spectral models and the first-order small slope approximation (SSA-1). First, sea spectral models proposed by Elfouhaily et al., Hwang et al., Romeiser et al., Apel et al., Fung et al., and Pierson et al., are compared with each other from different points of view, e.g., the omnidirectional parts, the angular spreading functions, the autocorrelation functions, and the slope variances. We find that the spectra given by Elfouhaily and Hwang could reflect realistic wind sea waves more accurately. Then, the scattering coefficients are simulated in fully monostatic and bistatic configurations. Regarding the monostatic scattering, the results simulated using EM scattering models are compared with those obtained from the measured UAVSAR data in the L band and the empirical model CMOD5 in the C band. Comparisons are made for various incident angles, wind speeds, and wind directions. Meanwhile, special attention is paid to low to moderate incident angles. The comparisons show that, it is difficult to find one certain spectral model to simulate scattering coefficient accurately under all wind speeds or wind directions. Accurate estimations will be obtained using different methods according to different situations.
Highlights
The microwave scatterometer is one of the most effective instruments in ocean remote sensing since it can provide valuable measurements at both day and night in spite of the atmospheric conditions
Many microwave radars that operate at various frequencies have been developed for airborne and space-borne platforms, such as the Advanced Synthetic Aperture Radar (ASAR) on the European Space Agency (ESA)’s ENVISAT-1 satellite, which was launched in 2002; the Phased-Array L-Band Synthetic Aperture Radar (PALSAR) on the Advanced Land Observing Satellite (ALOS), which was launched in 2006; synthetic aperture radar on the Canadian Space Agency’s Radarsat-1 and Radarsat-2, which were launched in 1995 and 2007, respectively; and synthetic aperture radar carried on the Sentinel-1 satellite launched in 2014 by the European Space Agency
The small slope approximation proposed by Voronovich [4,5,6] is a unifying model that could reconcile Kirchhoff-Tangent Plane Approximation (KA) and small perturbation method (SPM) without introducing any arbitrary parameters
Summary
The microwave scatterometer is one of the most effective instruments in ocean remote sensing since it can provide valuable measurements at both day and night in spite of the atmospheric conditions. SSA has been proved as an appropriate method for large-, intermediate-, and small-scale roughness surfaces under the condition that the tangent of grazing angles of incident/scattered waves is sufficiently larger than the RMS (root mean square) slopes of the rough surface These approximate methods have been studied and analyzed in the comparisons with the measured radar data [7]. Many spectral models that can be used to describe the small-scale waves have been proposed, for instance, the Pierson spectrum [8,9], Bjerkaas and Riedel spectrum [10], Fung spectrum [11], Donelan and Pierson spectrum [12], Apel spectrum [13], Romeiser spectrum [14], Elfouhaily spectrum [15], and Hwang spectrum [16,17,18,19] These spectral models have been employed in EM computations as they have defined the high-frequency spectra.
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