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This paper uses the Argo sea surface salinity (SSS_Argo) before and after the passage of 25 tropical cyclones (TCs) in the Bay of Bengal from 2015 to 2019 to evaluate the sea surface salinity (SSS) of the Soil Moisture Active Passive (SMAP) remote sensing satellite (SSS_SMAP). First, SSS_Argo data were used to evaluate the accuracy of the 8-day SMAP SSS data, and the correlations and biases between SSS_SMAP and SSS_Argo were calculated. The results show good correlations between SSS_SMAP and SSS_Argo before and after TCs (before: SSS_SMAP = 1.09SSS_Argo−3.08 (R² = 0.69); after: SSS_SMAP = 1.11SSS_Argo−3.61 (R² = 0.65)). A stronger negative bias (−0.23) and larger root-mean-square error (RMSE, 0.95) between the SSS_SMAP and SSS_Argo were observed before the passage of 25 TCs, which were compared to the bias (−0.13) and RMSE (0.75) after the passage of 25 TCs. Then, two specific TCs were selected from 25 TCs to analyze the impact of TCs on the SSS. The results show the significant SSS increase up to the maximum 5.92 psu after TC Kyant (2016), which was mainly owing to vertical mixing and strong Ekman pumping caused by TC and high-salinity waters in the deep layer that were transported to the sea surface. The SSS_SMAP agreed well with SSS_Argo in both coastal and offshore waters before and after TC Roanu (2016) and TC Kyant (2016) in the Bay of Bengal.