Testing the ability of RIEMS2.0 to simulate multi-year precipitation and air temperature in China

被引:19
作者
Zhao DeMing [1 ]
Fu CongBin [1 ]
Yan XiaoDong [1 ]
机构
[1] Chinese Acad Sci, Inst Atmospher Phys, Key Lab Reg Climate Environm Temperate E Asia, Beijing 100029, Peoples R China
来源
CHINESE SCIENCE BULLETIN | 2009年 / 54卷 / 17期
基金
中国博士后科学基金;
关键词
RIEMS2.0; precipitation; air temperature; climate and its changes; cumulus parameterization; simulation ability; REGIONAL CLIMATE MODEL; WESTERN UNITED-STATES; INTERANNUAL VARIABILITY; PARAMETERIZATIONS; REGCM3; ASIA;
D O I
10.1007/s11434-009-0178-3
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
RIEMS2.0 (Regional Integrated Environment Modeling System, Version 2.0) is now being developed starting from RIEMS1.0 by the Key Laboratory of Regional Climate Environment Research for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, China. In order to test RIEMS2.0's ability to simulate long-term climate and its changes, as well as provide a basis for further development and applications, we compare simulated precipitation and air temperature from 1980 to 2007 (simulation duration from Jan. 1, 1979 to Dec. 31, 2007) under different cumulus parameterization schemes with the observed data. The results show that RIEMS2.0 can reproduce the spatial distribution of precipitation and air temperature, but that the model overestimates precipitation with the rainfall center moving northwestward and underestimates air temperature for annual simulations. Annual and interannual variations in precipitation and air temperature for different climate subregions are well captured by the model. Further analysis of summer and winter simulations shows that precipitation is overestimated, except for the Jianghuai-Jiangnan subregions in the winter, and the air temperature bias in the summer is weaker than in the winter. There are larger biases for precipitation and air temperature in semiarid subregions. Anomalies in precipitation and air temperature are also well captured by the model. Although a similar distribution can be found between observed data and simulated results under different cumulus parameterization schemes, these show differences in intensity and location. In sum, RIEMS2.0 shows good stability and does well in simulating the long-term climate and its changes in China.
引用
收藏
页码:3101 / 3111
页数:11
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