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海表面盐度SSS(Sea Surface Salinity)是研究大洋环流和海洋对全球气候影响的重要参量、是决定海水基本性质的重要因素之一。卫星微波遥感可以满足盐度研究过程中大范围、连续观测的需要,国际上统一的认识是选择频率为1.413GHz的L波段作为盐度遥感的首选波段。目前,国外发展的海面盐度微波遥感反演算法主要有两种:基于海表发射率估算海表盐度的算法和基于贝叶斯定理提出的反演算法。影响盐度反演精度的因素主要有太空辐射、电离层法拉第旋转、大气、海面粗糙度等。其中,海面粗糙度对盐度反演影响很大,海面粗糙度处理模型可以分为3大类:理论算法(间接发射率模型、直接发射率模型)、经验算法、半经验半理论算法(Hollinger半经验模型、WISE半经验模型、Gabarró模型)。SMOS卫星和Aquarius/SAC-D卫星的成功发射,将海表面盐度遥感的反演精度控制在0.2psu以内,通过改进反演算法,有望得到更高的反演精度。
Sea Surface Salinity (SSS) is an important parameter for studying the effects of ocean circulation and oceans on the global climate. It is one of the important factors that determine the basic properties of seawater. Satellite microwave remote sensing can meet the needs of large-scale and continuous observation in the salinity research process. The international consensus is that the L band with the frequency of 1.413GHz is selected as the preferred band for remote sensing of salinity. At present, there are mainly two algorithms for the retrieval of sea surface salinity by microwave remote sensing: the algorithm of calculating sea surface salinity based on sea surface emissivity and the inversion algorithm based on Bayes’ theorem. The main factors affecting the accuracy of salinity inversion are space radiation, ionospheric Faraday rotation, atmosphere and sea surface roughness. Among them, sea surface roughness has great influence on salinity inversion. Sea surface roughness model can be divided into three categories: theoretical algorithm (indirect emissivity model, direct emissivity model), empirical algorithm, semi-empirical semi-theoretical algorithm Semi-empirical model, WISE semi-empirical model, Gabarró model). The successful launching of SMOS satellite and Aquarius / SAC-D satellite can control the retrieval accuracy of sea surface salinity remote sensing within 0.2psu. By improving the inversion algorithm, higher inversion accuracy is expected.