Assessment of Sea Surface Temperature Warming in the Tropical Indian Ocean Simulated by CMIP Models

查看全文 作　　者：ZHANG [1,2]Xinyou;LUO [2]Yulan;LIU [2,3]Lin;SUN [1]Xuguang

机构地区：[1]School of Atmospheric Sciences,Nanjing University,Nanjing 210023,China;[2]Laboratory for Regional Oceanography and Numerical Modeling,Pilot National Laboratory for Marine Science and Technology,First Institute of Oceanography,and Key Laboratory of Marine Science and Numerical Modeling,Ministry of Natural Resources,Qingdao 266061,China;[3]Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 511458,China

出　　处：《Journal of Ocean University of China》索引2023年第22卷第4期,共13页

基　　金：supported by the Taishan Scholars Programs of Shandong Province(No.tsqn201909165);the Global Change and Air-Sea Interaction Program(Nos.GASI-04-QYQH-03,GASI-01-WIND-STwin);the Natural Science Foundation of China Grants(No.41876028);the Taishan Scholars Programs of Shandong Province(No.20190963). 摘　　要：The tropical Indian Ocean is an important region that affects local and remote climate systems,and the simulation of longterm trends in sea surface temperature(SST)is a major focus of climate research.This study presents a preliminary assessment of multiple model simulations of tropical Indian Ocean SST warming from 1950 to 1999 based on outputs from the 20 Coupled Model Intercomparison Project(CMIP)Phase 5(CMIP5)models and the 36 CMIP 6(CMIP6)models to analyze and compare the warming patterns in historical simulations.Results indicate large discrepancies in the simulations of tropical Indian Ocean SST warming,especially for the eastern equatorial Indian Ocean.The multimodel ensemble mean and most of the individual models generally perform well in reproducing basin-wide SST warming.However,the strength of the SST warming trends simulated by the CMIP5 and CMIP6 models are weaker than those observed,especially for the CMIP6 models.In addition to the general warming trend analysis,decadal trends are also assessed,and a statistical method is introduced to measure the near-term variability in an SST time series.The simulations indicate large decadal variability over the entire tropical Indian Ocean,differing from observations in which significant decadal trend variability is observed only in the southeastern Indian Ocean.In the CMIP model simulations,maximum decadal variability occurs in boreal autumn,but the observations display the minimum and maximum variability in boreal autumn and spring,respectively. 关键词：Indian Ocean CMIP5 CMIP6 SST warming trend

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Assessment of Sea Surface Temperature Warming in the Tropical Indian Ocean Simulated by CMIP Models

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