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BCC_CSM气候模式对中国区域气候变化模拟能力的检验 被引量:15

Verification of Simulation Ability of BCC_CSM Climate Model in Regional Climate Change in China
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摘要 为了科学评价BCC_CSM气候模式的模拟效果,并为改进和完善此模式提供科学依据,以NCEP/NCAR 1948—2005年逐月再分析资料作为检验模式对应的实况场,利用距平标准化均方根误差、相关系数等方法对国家气候中心发展的BCC_CSM气候模式模拟中国气候变化的能力进行了检验,检验要素包括:对流层高、中、低层各季节的温度场、风场、相对湿度场和加热场等。结果表明,除春季外,其他3个季节实况场与模拟场的距平标准化均方根误差都较小;全年相关性都比较好,全国绝大部分地区均通过了α=0.05显著性水平检验;不同气象要素场的距平标准化均方根误差与相关系数呈现出季节性和区域性特征;模式模拟出了中国不同区域各个气象要素的年变化;与IPCC AR4中的13种模式相比较,BCC_CSM气候模式对中国区域地面温度场的模拟效果较好。 In order to evaluate the simulation results of BCC_CSM climate model scientifically and provide the scientific evidence to improve and perfect the model,using of standardized anomaly of Root Mean Square Error(RMSE),correlation coefficient methods,BCC_CSM climate model which developed by National Climate Center is validated against the NCEP/NCAR monthly reanalysis data in 1948-2005 as observation field to verify the capability to simulate the regional climate change in China.Inspection elements include: Temperature field,wind field,relative humility field and surface heating field in four seasons on the upper,middle and lower troposphere etc.The results show that the standardized anomaly of RMSE in other three seasons between the simulatied and observed fields are smaller except for spring;The correlations of whole year are quite good,which have passed the significant test of significance level at α=0.05 in the most part of the country;RMSE of standardized anomaly and correlations of different meteorological element fields present with regional and seasonal characteristics;the annual variation of every meteorological element in different regional areas in China is simulated by model,the surface temperature simulated by BCC_CSM climate model is very well comparing with the 13 modes of the IPCC AR4.
出处 《高原气象》 CSCD 北大核心 2012年第5期1257-1267,共11页 Plateau Meteorology
基金 国家科技支撑计划课题(2007BAC29B03 2009BAC53B02)资助
关键词 BCC_CSM气候模式 数值模拟 气候变化 相关系数 距平标准化均方根误差 BCC_CSM climate mode Numerical simulation Climatic change Correlation coefficient Standardized anomaly of root mean square error
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