Equipped with an L-band radiometer, SMOS, and Aquarius provide an unprecedented sea surface salinity (SSS) dataset of the global oceans in days. The sensitivity of Lband brightness temperature (TB) to SSS variation is about 0.3-0.8 K/psu, which means the salinity signal in TB is very weak. Enormous efforts are devoted to the development, evaluation, and improvement of the SSS retrieval algorithm especially under some unfavorable conditions, i.e., the rain. Rain drops inducing freshening and roughness effects on the sea surface have made the SSS retrieval challenging for years. This paper describes a new method to separate the freshening and roughness effects of rainfall based on the combined active/passive observations of Aquarius. The dependence of the sea surface emissivity (sensitive to both roughness and freshening) on the backscatter (only sensitive to roughness) is obtained and the rain-induced roughness is corrected. The method is applied to the salinity retrieval under rain. The retrieval results (SSS,c) are compared with HYCOM data corrected by the rain impact model (SSSHYCOM RIM). The bias of SSSrc shows no clear dependence on rain rate. However, the bias of the standard product of Aquarius (SSSADPS, V4.0) rises sharply with rain rate. Furthermore, the standard deviation of SSSrc is about 0.5 psu, which is also superior to SSSADPS (0.9 psu). The above results confirm the feasibility of this new retrieval algorithm for the SSS remote sensing in rainy weather.