文献类型：期刊文献

英文题名：Effects of Tropical Cyclones on Sea Surface Salinity in the Bay of Bengal Based on SMAP and Argo Data

作者：Xu, Huabing[1];Yu, Rongzhen[1];Tang, Danling[2,3,4];Liu, Yupeng[3,4];Wang, Sufen[3,4];Fu, Dongyang[1]

机构：[1]Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524088, Peoples R China;[2]Southern Marine Sci & Engn Guangdong Lab, Guangzhou 510301, Peoples R China;[3]Chinese Acad Sci, South China Sea Inst Oceanol, Guangdong Key Lab Ocean Remote Sensing, Guangzhou 510301, Peoples R China;[4]Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Guangzhou 510301, Peoples R China

年份：2020

卷号：12

期号：11

起止页码：1

外文期刊名：WATER

收录：SCI-EXPANDED(收录号：WOS:000594344200001)、、EI(收录号：20204609493938)、Scopus(收录号：2-s2.0-85095968864)、WOS

基金：This research was funded by Guangdong Special Support Program (2019BT02H594), scientific research start-up funds of Guangdong Ocean University (R20008), State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences (LTO2015), Guangdong Key Laboratory of Ocean Remote Sensing (South China Sea Institute of Oceanology, Chinese Academy of Sciences) (2017B030301005-LORS2008).

语种：英文

外文关键词：SMAP; tropical cyclone; Bay of Bengal; sea surface salinity

外文摘要：This paper uses the Argo sea surface salinity (SSSArgo) 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 (SSSSMAP). First, SSSArgo data were used to evaluate the accuracy of the 8-day SMAP SSS data, and the correlations and biases between SSSSMAP and SSSArgo were calculated. The results show good correlations between SSSSMAP and SSSArgo before and after TCs (before: SSSSMAP = 1.09SSS(Argo)-3.08 (R-2 = 0.69); after: SSSSMAP = 1.11SSS(Argo)-3.61 (R-2 = 0.65)). A stronger negative bias (-0.23) and larger root-mean-square error (RMSE, 0.95) between the SSSSMAP and SSSArgo 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 SSSSMAP agreed well with SSSArgo in both coastal and offshore waters before and after TC Roanu (2016) and TC Kyant (2016) in the Bay of Bengal.