Abstract

Sea surface salinity (SSS) is a crucial indicator that is used to monitor the hydrological cycle in the ocean system. In this study, we evaluated the simulation skill of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in reproducing the SSS in the Asian Marginal Seas (AMSs). The results show that the AMSs’ SSS simulated by most CMIP6 models is generally in good agreement with the observations in terms of spatial patterns and seasonal variability. However, these models tend to overestimate the SSS in the Eastern Arabian Sea and the Bay of Bengal by up to 1.3 psu, while they underestimate the SSS in the Bohai Sea, the Yellow Sea, the Southern South China Sea, and the Indonesian Seas, with the bias exceeding −1.5 psu. Additionally, the seasonal variations in the Sea of Okhotsk, the Bay of Bengal, and the Arabian Sea exhibit large biases with phase shift or reversal in some CMIP6 models. Notably, the observed magnitudes in the AMSs are significantly higher than the global average of 0.2 psu, ranging from 0.22 to 1.19 psu. Furthermore, we calculated the projected trends in sea surface salinity under different future scenarios by using the CMIP6 models. The results reveal relatively larger SSS freshening trends in the second half of the 21st century compared to the first half. Specifically, the freshening trends for the Shared Socio-Economic Pathway (SSP) of low- (global radiative forcing of 2.6 W/m2 by the year 2100), medium- (global radiative forcing of 4.5 W/m2 by 2100), and high-end (8.5 W/m2 by 2100) pathways are 0.05–0.21, 0.12–0.39, and 0.28–0.78 psu/century, respectively. The most rapid freshening trends of SSS are observed in the East China Seas and the Indonesian Seas, which are over two times greater than the global mean. On the other hand, the SSS freshening trends in the Arabian Sea are slightly lower than the global mean SSS freshening trend.

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