首页 | 官方网站   微博 | 高级检索  
     

CMIP6全球气候模式对中国极端降水模拟能力的评估及其与CMIP5的比较
引用本文:王予,李惠心,王会军,孙博,陈活泼.CMIP6全球气候模式对中国极端降水模拟能力的评估及其与CMIP5的比较[J].气象学报,2021,79(3):369-386.
作者姓名:王予  李惠心  王会军  孙博  陈活泼
作者单位:1.南京信息工程大学气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心,南京,210044
基金项目:国家自然科学基金项目(42005015、42088101、41991283、42025502)、江苏省自然科学基金项目(SBK2020040311)、江苏省高等学校自然科学研究面上项目(20KJB170001)、南京信息工程大学优秀毕业论文支持计划
摘    要:对CMIP6全球气候模式在中国地区极端降水的模拟能力进行了综合评估.基于CN05.1观测数据集和32个CMIP6全球气候模式的降水数据,采用8个常用极端降水指数对极端降水进行了定量描述.研究结果表明,在极端降水的气候平均态方面,CMIP6多模式集合对1961—2005年中国地区区域平均的8个极端降水指数模拟的平均相对误...

关 键 词:CMIP6  CMIP5  极端降水  模拟评估
收稿时间:2021/1/8 0:00:00
修稿时间:2021/3/22 0:00:00

Evaluation of CMIP6 model simulations of extreme precipitation in China and comparison with CMIP5
WANG Yu,LI Huixin,WANG Huijun,SUN Bo,CHEN Huopo.Evaluation of CMIP6 model simulations of extreme precipitation in China and comparison with CMIP5[J].Acta Meteorologica Sinica,2021,79(3):369-386.
Authors:WANG Yu  LI Huixin  WANG Huijun  SUN Bo  CHEN Huopo
Affiliation:1.Key Laboratory of Meteorological Disasters,Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science & Technology,Nanjing 210044,China2.Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519080,China3.Nansen-Zhu International Research Centre,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China
Abstract:Based on the 32 global climate models that participated in the phase 6 of the Coupled Model Intercomparison Project (CMIP6), 27 global climate models that participated in CMIP5 and the observational dataset CN05.1, this study evaluates the performances of these CMIP6 and CMIP5 models on the simulation of extreme precipitation index over China for 1961—2005. Eight extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) are used to represent extreme precipitation events. Results indicate that the multi-model ensemble (MME) median of CMIP6 overall has lower relative errors of both climatological mean (with an average of 29.94%, reduced by 2.95%) and relative variability (with an average of 10.10%, reduced by 5.45%) than that of CMIP5. Generally, CMIP6 performs better than CMIP5 in simulating climatological condition of China, especially over the arid region (the error was reduced by 12.15% compared to CMIP5). Further analyses suggest that the MME median of CMIP6 has large spatial correlation coefficients and small root-mean-square errors. Based on the Taylor skill (TS) score, both CMIP6 and CMIP5 models are ranked to evaluate relative model performance. CMIP6 models have higher ranks than CMIP5 models, with an average TS score of 0.78 (0.75) for CMIP6 (CMIP5), and four out of the five highest-scored models are CMIP6 models. Regarding the homologous models, the TS scores of CMIP6 models (an average of 0.91) are larger than their earlier versions in CMIP5 (an average of 0.68), indicating a prominent improvement in CMIP6. Further analyses reveal that the performances of CMIP6 models differ in the simulation of extreme precipitation over different regions of China. Generally, compared to CMIP5, CMIP6 models perform better in simulating extreme precipitation events over China. 
Keywords:CMIP6  CMIP5  Extreme precipitation  Model evaluation
本文献已被 CNKI 等数据库收录!
点击此处可从《气象学报》浏览原始摘要信息
点击此处可从《气象学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号