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CMIP5模式对南海SST的模拟和预估
引用本文:黄传江,乔方利,宋亚娟,李新放.CMIP5模式对南海SST的模拟和预估[J].海洋学报,2014,36(1):38-47.
作者姓名:黄传江  乔方利  宋亚娟  李新放
作者单位:1.First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Key Laboratory of Marine Science and Numerical Modeling, State Oceanic Administration, Qingdao 266061, China
基金项目:中华人民共和国科学技术部全球变化研究重大科学研究计划项目(2010CB950500)。
摘    要:分析了32个CMIP5模式对南海历史海表温度(SST)的模拟能力和不同排放情景下未来SST变化的预估。通过检验各气候模式对南海历史SST增温趋势和均方差的模拟,发现大部分模式都能较好地模拟出南海20世纪历史SST的基本特征和变化规律,但也有部分模式的模拟存在较大偏差。尽管这些模拟偏差较大的模式对SST多模式集合平均的影响不大,但会增加未来情景预估的不确定性。剔除15个模式后,分析了南海SST在RCP26、RCP45和RCP85三种排放情景下的变化趋势,发现在未来百年呈明显的增温趋势,多模式集合平均的增温趋势分别为0.42、1.50和3.30℃/(100a)。这些增温趋势在空间上变化不大,但随时间并不是均匀变化的。在前两种排放情景下,21世纪前期的增温趋势明显强于后期,而在RCP85情景下,21世纪后期的增温趋势强于前期。

关 键 词:SST    南海    气候变化    预估    CMIP5    多模式集合
收稿时间:2013/1/16 0:00:00

The simulation and forecast of SST in the South China Sea by CMIP5 models
Huang Chuanjiang,Qiao Fangli,Song Yajuan and Li Xinfang.The simulation and forecast of SST in the South China Sea by CMIP5 models[J].Acta Oceanologica Sinica (in Chinese),2014,36(1):38-47.
Authors:Huang Chuanjiang  Qiao Fangli  Song Yajuan and Li Xinfang
Institution:1.First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Key Laboratory of Marine Science and Numerical Modeling, State Oceanic Administration, Qingdao 266061, China2.First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China
Abstract:The simulation abilities of 32 CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models to the historical sea surface temperature (SST) in the South China Sea are evaluated by verifying its long-term linear trend and standard deviation. The projections of the SST for the 21st century under different RCP (Representative Concentration Pathway) emission scenarios are analyzed. The results show that most of the models can well reproduce the primary characteristic and change of the historical SST in the South China Sea. However,the simulations of the historical SST are unsatisfactory for 15 climate models. These models are excluded in evaluating the RCP forecasts for minimizing the uncertainty of the forecast results,while their effects to the multi-model ensemble mean are not so significant. Other models show that the SST in the South China Sea will be significant warming in the 21st century,whose linear trends of the multi-model ensemble mean are 0.42,1.50 and 3.30℃/(100 a) under RCP26,RCP45,and RCP85 scenarios,respectively. The changes of these trends are relatively small in space,but not with time. The warming in the early 21st century is significantly stronger than that in the late 21st century under RCP26 and RCP45scenarios,while the opposite under RCP85 scenario.
Keywords:SST  South China Sea  Climate change  forecast  CMIP5  multi-model ensemble mean
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