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An Assessment on the Performance of IPCC AR4 Climate Models in Simulating Interdecadal Variations of the East Asian Summer Monsoon
Author(s): 
Pages: 472-488
Year: Issue:  4
Journal: Acta Meteorologica Sinica

Keyword:  climate models East Asian summer monsoon model evaluation;
Abstract: Observations from several data centers together with a categorization method are used to evaluate the IPCC AR4 (Intergovernmental Panel on Climate Change, the Fourth Assessment Report) climate models' performance in simulating the interdecadal variations of summer precipitation and monsoon circulation in East Asia. Out of 19 models under examination, 9 models can relatively well reproduce the 1979-1999 mean June-July-August (JJA) precipitation in East Asia, but only 3 models (Category-1 models) can capture the interdecadal variation of precipitation in East Asia. These 3 models are: GFDL-CM2.0, MIROC3.2 (hires), and MIROC3.2 (medres), among which the GFDL-CM2.0 gives the best performance. The reason for the poor performance of most models in simulating the East Asian summer monsoon interdecadal variation lies in that the key dynamic and thermal-dynamic mechanisms behind the East Asian monsoon change are missed by the models, e.g., the large-scale tropospheric cooling and drying over East Asia. In contrast, the Category-1 models relatively well reproduce the variations in vertical velocity and water vapor over East Asia and thus show a better agreement with observations in simulating the pattern of "wet south and dry north" in China in the past 20 years.It is assessed that a single model's performance in simulating a particular variable has great impacts on the ensemble results. More realistic outputs can be obtained when the multi-model ensemble is carried out using a suite of well-performing models for a specific variable, rather than using all available models. This indicates that although a multi-model ensemble is in general better than a single model, the best ensemble mean cannot be achieved without looking into each member model's performance.
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