Multi-year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM NCC). Part I: Sensitivity Study
Multi-year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model （RegCM_NCC）. Part Ⅰ： Sensitivity Study

A modified version of the NCAR/RegCM2 has been developed at the National Climate Center (NCC), China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP (Institute of Atmospheric Physics) T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year (2001 to 2004) prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process parameterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme (MFS) and Betts-Miller scheme (BM) for convective precipitation, the LPMI (land surface process model I) and LPMII (land surface process model II) for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE (turbulent kinetic energy) scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 (RegCM NCC) has been set up for climate simulations and seasonal predictions.