Assessment of the Sea Surface Salinity Simulation and Projection Surrounding the Asian Waters in the CMIP6 Models

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.

[1]  L. Cheng,et al.  How Well Do CMIP6 and CMIP5 Models Simulate the Climatological Seasonal Variations in Ocean Salinity? , 2022, Advances in Atmospheric Sciences.

[2]  P. Lin,et al.  Interannual variability of the sea surface salinity and its related freshwater flux in the tropical Pacific: A comparison of CMIP5 and CMIP6 , 2022, Atmospheric and Oceanic Science Letters.

[3]  C. Harvey,et al.  Future Temperature and Salinity in Puget Sound, Washington State, Under CMIP6 Climate Change Scenarios , 2020, Journal of Water and Climate Change.

[4]  N. Reul,et al.  Satellite Observations of the Sea Surface Salinity Response to Tropical Cyclones , 2020, Geophysical Research Letters.

[5]  J. Boutin,et al.  Tropical Instability Waves in the Atlantic Ocean: Investigating the Relative Role of Sea Surface Salinity and Temperature From 2010 to 2018 , 2020, Journal of Geophysical Research: Oceans.

[6]  S. Xie,et al.  Climate impacts of a weakened Atlantic Meridional Overturning Circulation in a warming climate , 2020, Science Advances.

[7]  T. Boyer,et al.  Halosteric Sea Level Changes during the Argo Era , 2017 .

[8]  Haiyan Jin,et al.  Composition of algal pigments in surface freshen layer after ice melt in the central Arctic , 2017, Acta Oceanologica Sinica.

[9]  G. Reverdin,et al.  A new record of Atlantic sea surface salinity from 1896 to 2013 reveals the signatures of climate variability and long‐term trends , 2017 .

[10]  Veronika Eyring,et al.  Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization , 2015 .

[11]  Tong Lee,et al.  SMOS Sea Surface Salinity signals of tropical instability waves , 2014 .

[12]  Arun Kumar,et al.  Salinity anomaly as a trigger for ENSO events , 2014, Scientific Reports.

[13]  T. Qu,et al.  ENSO indices from sea surface salinity observed by Aquarius and Argo , 2014, Journal of Oceanography.

[14]  V. Menezes,et al.  Aquarius sea surface salinity in the South Indian Ocean: Revealing annual‐period planetary waves , 2014 .

[15]  Robert Marsh,et al.  Salinity changes in the World Ocean since 1950 in relation to changing surface freshwater fluxes , 2014, Climate Dynamics.

[16]  Nick Rayner,et al.  EN4: Quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates , 2013 .

[17]  W. Collins,et al.  Evaluation of climate models , 2013 .

[18]  A. Phillips,et al.  Variability of the Atlantic meridional overturning circulation in CCSM4 , 2012 .

[19]  Simon Yueh,et al.  Aquarius reveals salinity structure of tropical instability waves , 2012 .

[20]  G. Vecchi,et al.  Simulated Climate and Climate Change in the GFDL CM2.5 High-Resolution Coupled Climate Model , 2012 .

[21]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[22]  Young‐Oh Kwon,et al.  Stochastically-driven multidecadal variability of the Atlantic meridional overturning circulation in CCSM3 , 2012, Climate Dynamics.

[23]  R. Schmitt,et al.  The Ocean and the Global Water Cycle , 2010 .

[24]  Nathaniel L. Bindoff,et al.  Changes in the global hydrological‐cycle inferred from ocean salinity , 2010 .

[25]  S. Wijffels,et al.  Fifty-Year Trends in Global Ocean Salinities and Their Relationship to Broad-Scale Warming , 2010 .

[26]  A. Busalacchi,et al.  Freshwater Flux (FWF)-Induced Oceanic Feedback in a Hybrid Coupled Model of the Tropical Pacific , 2009 .

[27]  Raymond W. Schmitt,et al.  Salinity and the global water cycle , 2008 .

[28]  Jialin Lin,et al.  The Double-ITCZ Problem in IPCC AR4 Coupled GCMs: Ocean–Atmosphere Feedback Analysis , 2007 .

[29]  John F. B. Mitchell,et al.  THE WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research , 2007 .

[30]  Claude Frankignoul,et al.  Surface salinity in the Atlantic Ocean (30°S–50°N) , 2007 .

[31]  R. Murtugudde,et al.  On the potential impact of sea surface salinity observations on ENSO predictions , 2002 .

[32]  Christophe Maes,et al.  Salinity barrier layer and onset of El Niño in a Pacific coupled model , 2002 .

[33]  K. Taylor.  Summarizing multiple aspects of model performance in a single diagram , 2001 .

[34]  G. Meehl,et al.  The Coupled Model Intercomparison Project (CMIP) , 2000 .

[35]  T. Delcroix,et al.  Observed surface oceanic and atmospheric variability in the tropical Pacific at seasonal and ENSO timescales: A tentative overview , 1998 .

[36]  G. Meehl,et al.  Intercomparison makes for a better climate model , 1997 .

[37]  P. Arkin,et al.  Precipitation and sea-surface salinity in the tropical Pacific Ocean , 1996 .

[38]  D. Roemmich,et al.  Fresh Equatorial Jets , 1994 .

[39]  Syukuro Manabe,et al.  Interdecadal Variations of the Thermohaline Circulation in a Coupled Ocean-Atmosphere Model , 1993 .

[40]  A. Manda,et al.  Evaluation of CMIP5 models on sea surface salinity in the Indian Ocean , 2017 .

[41]  F. Estrada,et al.  Statistical evidence about human influence on the climate system , 2012 .