摘要
本文基于CN05.1逐月气温观测资料和CMIP6计划中34个模式资料、CMIP5中39个模式资料,利用泰勒图、技能得分(S值)、综合评级指标(M_(r)),系统地评估了相比于CMIP5模式,CMIP6模式对1961—2005年中国东北地区(黑龙江省、吉林省、辽宁省)气温模拟能力.结果表明:1)相较于CMIP5模式,CMIP6中大部分模式能更好地模拟出区域平均气温多年变化、年平均气温气候态空间分布及年平均气温气候倾向率的空间分布的特征,但普遍存在低估的现象;2)经过优选后得到的CMIP5与CMIP6最优模式集合平均(MME5、MME6)对年平均气温的模拟优于大部分单个模式和所有模式的集合平均模拟结果.MME6比MME5能更好地模拟出年平均气温气候态及气温多年变化趋势的空间分布特征,但对区域平均气温多年变化的模拟能力要略低.总体来说,CMIP6模式相对于CMIP5有所进步,MME6对中国东北地区气温的时空变化特征具有一定的模拟能力.
Based on the observational data of CN05.1,this article evaluated and compared the performance of 39 CMIP5(Coupled Model Intercomparison Project phase 5)models and 34 CMIP6(CMIP phase 6)models in simulating surface air temperature of the three provinces in Northeast China(the Heilongjiang,Jilin and Liaoning Province)by Taylor diagram,skill scores(S value)and the composite rating indicators(M_(r)).Results showed that:1)The CMIP6 models possess a relatively higher capability in simulating the temperature from the interannual variations of regionally averaged surface air temperature,spatial distributions of annual mean surface air temperature and its trend than CMIP5 models but shows a negative bias;2)CMIP5 and CMIP6 preferred ensemble mean(MME5 and MME6)generally performs better than the individual models.Compared with the MME5,MME6 shows a significant improvement in simulating the climatological spatial distribution of temperature and its trend,whilst is slightly inferior in simulating the interannual variations of regionally averaged temperature.Generally speaking,CMIP6 models exhibit a significant improvement compared to the CMIP5 models and MME6 has been proven effective at simulating the temperature in Northeast China.
作者
何夏曼
姜超
汪君
王襄平
HE XiaMan;JIANG Chao;WANG Jun;WANG XiangPing(School of Ecology and Nature Conservation,Beijing Forestry University,Beijing 100083,China;Nansen-Zhu International Research Centre,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China)
出处
《地球物理学报》
SCIE
EI
CAS
CSCD
北大核心
2022年第11期4194-4207,共14页
Chinese Journal of Geophysics
基金
国家自然科学基金项目(31870430)资助.
