Projected Changes in Temperature and Precipitation Extremes in China by the CMIP5 Multimodel Ensembles

被引:343
|
作者
Zhou, Botao [1 ,2 ]
Wen, Qiuzi Han [3 ]
Xu, Ying [1 ]
Song, Lianchun [1 ]
Zhang, Xuebin [3 ]
机构
[1] China Meteorol Adm, Natl Climate Ctr, Beijing 100081, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing, Peoples R China
[3] Environm Canada, Div Climate Res, Toronto, ON, Canada
基金
中国国家自然科学基金;
关键词
CLIMATE-CHANGE; INDEXES; GENERATION; SIMULATION; SCENARIOS; DATASET;
D O I
10.1175/JCLI-D-13-00761.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This paper presents projected changes in temperature and precipitation extremes in China by the end of the twenty-first century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations. The temporal changes and their spatial patterns in the Expert Team on Climate Change Detection and Indices (ETCCDI) indices under the RCP4.5 and RCP8.5 emission scenarios are analyzed. Compared to the reference period 1986-2005, substantial changes are projected in temperature and precipitation extremes under both emission scenarios. These changes include a decrease in cold extremes, an increase in warm extremes, and an intensification of precipitation extremes. The intermodel spread in the projection increases with time, with wider spread under RCP8.5 than RCP4.5 for most indices, especially at the subregional scale. The difference in the projected changes under the two RCPs begins to emerge in the 2040s. Analyses based on the mixed-effects analysis of variance (ANOVA) model indicate that by the end of the twenty-first century, at the national scale, the dominant contributor to the projection uncertainty of most temperature-based indices, and some precipitation extremes [including maximum 1-day precipitation (RX1day) and maximum 5-day precipitation (RX5day), and total extremely wet day total amount (R95p)], is the difference in emission scenarios. By the end of the twenty-first century, model uncertainty is the dominant factor at the regional scale and for the other indices. Natural variability can also play very important role.
引用
收藏
页码:6591 / 6611
页数:21
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