Is the global atmospheric model MRI-AGCM3.2 better than the CMIP5 atmospheric models in simulating precipitation over East Asia?
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The reproducibility of precipitation over East Asia (110–150°E, 20–50°N) by the Meteorological Research Institute-Atmospheric General Circulation Model version 3.2 (MRI-AGCM3.2) was investigated and compared with those by global atmospheric models participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The 20, 60 and 180-km grid size version of this model were used to evaluate the dependence of model performance on horizontal resolution. The dependence of cumulus convection scheme on model performance was also investigated. All the MRI-AGCM3.2 models and the CMIP5 models were forced with observed historical sea surface temperatures for the period 1979–2003 (25 years). The reproducibility of the MRI-AGCM3.2 models is higher or comparable to that of the CMIP5 models for seasonal average precipitation, the seasonal March of rainy zone and extreme precipitation events. Especially in summer, the advantage of the MRI-AGCM3.2 models over the CMIP5 models is striking in terms of various skill measures. This is partly due to the higher horizontal resolution of the MRI-AGCM3.2 models, but the performance of models is also sensitive to and depends on cumulus convection scheme. The better simulation of summer precipitation over East Asia by the MRI-AGCM3.2 models can be partly attributed to the better simulation of precipitation, the West Pacific Subtropical High and the local Hadley circulation in the tropics. This study highlights that higher reproducibility of summertime precipitation over East Asia requires proper simulation not only for tropical circulation but also for the strong dynamical linkage between precipitation over East Asia and tropical circulation.
KeywordsPrecipitation East Asia Global atmospheric model High horizontal resolution Cumulus convection scheme The West Pacific Subtropical High
This work was conducted under the framework of “the Development of Basic Technology for Risk Information on Climate Change” supported by the SOUSEI Program of the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan. This study was supported by the Environment Research and Technology Development Fund (2-1503) of the Ministry of the Environment, Japan. We also acknowledge the “Data Integration and Analysis System(DIAS)” Fund for National Key Technology from the MEXT of Japan. We acknowledge the international modeling groups for providing model data for our analysis, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the CMIP5 and CMIP3 multi model data, and the Joint Scientific Committee (JSC)/CLIVAR Working Group on Coupled Modelling (WGCM). The data archive at the Lawrence Livermore National Institute (LLNI) is supported by the Office of Science, U.S. Department of Energy. We also thank the anonymous reviewers whose valuable comments and suggestions greatly improved the manuscript. Thanks are extended to the support and collaboration by Drs. R. Mizuta, K. Yoshida, O. Arakawa, T. Ose, A. Kitoh and I. Takayabu.
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