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

被引:0
作者
Xinyou Zhang
Yulan Luo
Lin Liu
Xuguang Sun
机构
[1] Nanjing University,School of Atmospheric Sciences
[2] Ministry of Natural Resources,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
[3] Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai),undefined
来源
Journal of Ocean University of China | 2023年 / 22卷
关键词
Indian Ocean; CMIP5; CMIP6; SST; warming trend;
D O I
暂无
中图分类号
学科分类号
摘要
The tropical Indian Ocean is an important region that affects local and remote climate systems, and the simulation of long-term 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.
引用
收藏
页码:897 / 909
页数:12
相关论文
共 187 条
[21]  
Taschetto A S(2001)On the relationship between Indian Ocean SST and Asian summer monsoon Geophysical Research Letters 28 2843-324
[22]  
Santoso A(1999)A study of SST warming trend in the western equatorial Pacific in a coupled Ocean-Atmosphere-Land GCM Advances in Atmospheric Sciences 16 24-16
[23]  
Meissner K J(1985)Correlation between SST over the Indian Ocean and the South China Sea and summer precipitation over the middle and lower reaches of the Yangtze River Journal of Atmospheric Sciences 9 314-16
[24]  
Dong L(1966)Quasi-geostrophic motions in the equatorial area Journal of the Meteorological Society of Japan. Ser II 44 25-8509
[25]  
McPhaden M J(1999)Inter-decadal modulation of the impact of ENSO on Australia Climate Dynamics 15 319-363
[26]  
Du Y(2007)Relationships between SSTA of tropical Indian Ocean and summer rainfall in southern China Journal of Nanjing Institute of Meteorology 30 9-498
[27]  
Xie S P(2016)Can large scale surface circulation changes modulate the sea surface warming pattern in the tropical Indian Ocean Climate Dynamics 46 1-398
[28]  
Eyring V(2003)Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century Journal of Geophysical Research: Atmosphere 108 4407-5136
[29]  
Bony S(2016)The curious case of Indian ocean warming Journal of Climate 27 8501-360
[30]  
Meehl G A(1999)A dipole mode in the tropical Indian Ocean Nature 401 360-480