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Modelling the Interannual Variation of Regional Precipitation over China


doi: 10.1007/BF02666549

  • The interannual change of regional precipitation over China during 1979-1988, simulated by the IAP 2-L AGCM (the atmospheric general circulation model) developed in the Institute of Atmospheric Physics and by using the observational monthly sea surface temperature (SST) and sea ice occupations, was analysed and compared with that of observation. Results show that the abilities of the model to simulate the interannual variabilities of precipita-tion are different from one region to another in China Studies indicate that the regional precipitation interannual va-riation which is correlated to the strong sign of sea surface temperature anomalies (SSTA) could be simulated well by the model, strong SSTA is important for the seasonal and extra-seasonal climate predictions through climate models. The results also suggest that the horizontal resolution of the model should be more refined in order to give better rep-resentations of regional details.
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Manuscript History

Manuscript received: 10 April 1994
Manuscript revised: 10 April 1994
通讯作者: 陈斌, bchen63@163.com
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Modelling the Interannual Variation of Regional Precipitation over China

  • 1. LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080

Abstract: The interannual change of regional precipitation over China during 1979-1988, simulated by the IAP 2-L AGCM (the atmospheric general circulation model) developed in the Institute of Atmospheric Physics and by using the observational monthly sea surface temperature (SST) and sea ice occupations, was analysed and compared with that of observation. Results show that the abilities of the model to simulate the interannual variabilities of precipita-tion are different from one region to another in China Studies indicate that the regional precipitation interannual va-riation which is correlated to the strong sign of sea surface temperature anomalies (SSTA) could be simulated well by the model, strong SSTA is important for the seasonal and extra-seasonal climate predictions through climate models. The results also suggest that the horizontal resolution of the model should be more refined in order to give better rep-resentations of regional details.

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