摘要
基于1976-2005年淮河流域260个区域站点观测资料及CMIP5中19个全球气候模式模拟的16个极端气候指数格点资料,利用空间相关系数、均方根误差方法对CMIP5各模式和多模式集合模拟的极端气候指数分别进行评估,并研究在RCP4.5情境下CMIP5优选模式的多模式集合预估2016-2045年和2071-2100年的江淮流域极端气候指数变化情况,结果表明:(1)CMIP5中有11个模式与站点观测的空间相关系数较高。其中,CCSM4、CMCC-CM模拟TXx的结果最好,ACCESS1-0、MPI-ESM-LR、MPI-ESM-MR和GFDL-ESM2M对于TNn具有较好的模拟能力,ACCESS1-0、CMCC-CM对Rx1day具有良好的模拟能力。(2)CMIP5多模式集合模拟结果能很好地再现1976-2005年R95p、R99p、CDD的空间分布特点,但是对GSL、CSDI及极端气候强度指数模拟的结果与站点资料偏差较大。(3)在RCP4.5情境下,CMIP5多模式集合模拟的江淮流域极端气候指数中,在2016-2045年的TXx普遍增加了1.0℃左右,TNn在安徽省北部和河南省东部增加了约1.8℃,Rx1day和Rx5day的高增长区集中在河南省北部;2071-2100年,TXx和TNn增长幅度大于2.1℃,Rx1day和Rx5day各站点增长幅度的差异减弱。
Based on the observation data of 260 regional stations in the Yangtze-Huaihe River Basin from 1976 to 2005 and the data of 16 extreme climate index grid points simulated by 19 CMIP5 global climate models,this paper evaluates the extreme climate indices simulated by each model and multi-model ensemble of CMIP5 by using the methods of spatial correlation coefficient and root mean square error.Moreover,changes of extreme climate indices in the Yangtze-Huaihe River Basin in 20162045 and 20712100 projected by CMIP5 model ensemble under RCP4.5 scenario are also studied.The results show that:(1)The simulation results of 11 CMIP5 models have high spatial correlation coefficient with site observation.CCSM4 and CMCC-CM have the best simulation results of TXx;ACCESS1-0,MPI-ESM-LR,MPI-ESM-MR and GFDL-ESM2M have good simulation ability for TNn;ACCESS1-0 and CMCC-CM have good simulation ability for Rx1day.(2)CMIP5 multi-model ensemble can well reproduce the spatial distribution characteristics of R95p,R99p and CDD in 19762005,but their simulation results of GSL,CSDI and extreme climate intensity indices differ greatly from the site data.(3)In the extreme climate indices projected by CMIP5 models under RCP4.5 scenario,TXx will generally rise by about 1℃in 20162045,TNn will rise by more than 1.8℃in northern Anhui and eastern Henan,and the high growth areas of Rx1day and Rx5day will be concentrated in northern Henan.From 2071 to 2100,TXx and TNn will increase by more than 2.1℃,and the difference of the increment between Rx1day and Rx5day stations will get weakened.
作者
吴晶璐
汤剑平
吴建秋
黄文彦
雷正翠
姚丽娜
蒋骏
Wu Jinglu;Tang Jianping;Wu Jianqiu;Huang Wenyan;Lei Zhengcui;Yao Li’na;Jiang Jun(Changzhou Meteorological Office of Jiangsu Province,Changzhou 213022,China;College of Atmospheric Sciences of Nanjing University,Nanjing 210023,China)
出处
《气象与环境科学》
2024年第3期93-103,共11页
Meteorological and Environmental Sciences
基金
常州市气象局科研开发项目(1904)。
关键词
极端气候指数
CMIP5
江淮流域
extreme climate index
CMIP5
Yangtze-Huaihe River Basin
