CWRF performance at downscaling China climate characteristics
CWRF performance at downscaling China climate characteristics
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DOI：
10.1007/s00382-018-4257-5
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发表时间：
2019-02
期刊：
影响因子：
4.6
通讯作者：
Xin‐Zhong Liang;Chao Sun;Xiaohui Zheng;Yongjiu Dai;Min Xu;H. Choi;Tiejun Ling;F. Qiao;X. Kong-X
中科院分区：
文献类型：
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作者：
Xin‐Zhong Liang;Chao Sun;Xiaohui Zheng;Yongjiu Dai;Min Xu;H. Choi;Tiejun Ling;F. Qiao;X. Kong-X
在ECMWF中期再分析（ERI）的驱动下，利用1980-2015年30 km网格间距的模拟，对区域气候-天气研究与预报模式（CWRF）对中国气候特征降尺度的表现进行了评价。结果表明，CWRF在季风雨带、日温差、地面风、年际降水和温度异常、湿度耦合以及第95个百分点的日降水量等关键特征上优于RegCM4.6。与同化地面观测数据的ERI相比，CWRF更能反映季节平均气候和极端降水的地理分布。这些结果表明，CWRF可以显著增强中国气候模拟能力。
The performance of the regional Climate-Weather Research and Forecasting model (CWRF) for downscaling China climate characteristics is evaluated using a 1980–2015 simulation at 30 km grid spacing driven by the ECMWF Interim reanalysis (ERI). It is shown that CWRF outperforms the popular Regional Climate Modeling system (RegCM4.6) in key features including monsoon rain bands, diurnal temperature ranges, surface winds, interannual precipitation and temperature anomalies, humidity couplings, and 95th percentile daily precipitation. Even compared with ERI, which assimilates surface observations, CWRF better represents the geographic distributions of seasonal mean climate and extreme precipitation. These results indicate that CWRF may significantly enhance China climate modeling capabilities.