Application of Climate-Weather Research and Forecasting Model (CWRF) in China: Domain Optimization
气候-天气研究及预报模式（CWRF）在中国的应用：区域优化

A primary issue for applying a regional climate model is the computational domain design,where localization is necessary to optimize the model performance.This study focuses on the domain optimization for application of the Climate-Weather Research and Forecasting Model(CWRF),developed by Illinois State Water Survey,University of Illinois at Urbana-Champaign,in China through physical process understanding and numerical sensitivity study.First,correlation analysis of observational data is conducted to identify the key regions of large-scale circulation processes that govern China precipitation variations,and two observational reanalysis data are compared to determine the poor areas where large forcing data errors or uncertainties occur.The optimal domain is chosen such that the lateral boundary buffer zones contain the key process regions and avoid the poor data areas to accurately integrate the planetary and synoptic forcing signals while enabling the CWRF to realistically generate its own mesoscale circulation within the domain interior.This domain choice is then evaluated by a sensitivity study of the CWRF ability in simulating the 1998 summer extreme flood in China.It is demonstrated that the CWRF using the optimal domain most realistically reproduces the observed precipitation temporal evolutions and spatial patterns.The performance,however,is substantially reduced when the southern buffer zone extends to the Tropics where large driving data errors exist,and further degraded if the western and eastern buffer zones are also positioned away from the key process regions.The result indicates the great importance of the domain design in the regional climate modeling.