Ocean Salinity as a Precursor of Summer Rainfall over the East Asian Monsoon Region

Author:

Chen Biao1,Qin Huiling2,Chen Guixing3,Xue Huijie4

Affiliation:

1. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, and Graduate School, University of Chinese Academy of Sciences, Beijing, China

2. School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China

3. School of Atmospheric Sciences, and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China

4. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China, and School of Marine Sciences, University of Maine, Orono, Maine

Abstract

Abstract The sea surface salinity (SSS) varies largely as a result of the evaporation–precipitation difference, indicating the source or sink of regional/global water vapor. This study identifies a relationship between the spring SSS in the tropical northwest Pacific (TNWP) and the summer rainfall of the East Asian monsoon region (EAMR) during 1980–2017. Analysis suggests that the SSS–rainfall link involves the coupled ocean–atmosphere–land processes with a multifacet evolution. In spring, evaporation and water vapor flux divergence were enhanced in some years over the TNWP where an anomalous atmospheric anticyclone was established and a high SSS was well observed. As a result, the convergence of water vapor flux and soil moisture over the EAMR was strengthened. This ocean-to-land water vapor transport pattern was sustained from spring to summer and played a leading role in the EAMR rainfall. Moreover, the change in local spring soil moisture helped to amplify the summer rainfall by modifying surface thermal conditions and precipitation systems over the EAMR. As the multifacet evolution is closely related to the large-scale ocean-to-land water vapor transport, it can be well represented by the spring SSS in the TNWP. A random forest regression algorithm was used to further evaluate the relative importance of spring SSS in predicting summer rainfall compared to other climate indices. As the SSS is now monitored routinely by satellite and the global Argo float array, it can serve as a good metric for measuring the water cycle and as a precursor for predicting the EAMR rainfall.

Funder

Strategic Priority Research Program of the Chinese Academy of Sciences

National Natural Science Foundation of China

Publisher

American Meteorological Society

Subject

Atmospheric Science

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