Improving simulations of extreme precipitation events in China by the CMIP6 global climate models through statistical downscaling

被引:2
|
作者
Zhang, Jinge [1 ]
Li, Chunxiang [1 ]
Zhang, Xiaobin [2 ]
Zhao, Tianbao [1 ,3 ]
机构
[1] Hohai Univ, Coll Oceanog, Nanjing 210044, Peoples R China
[2] State Grid Gansu Elect Power Co, Lanzhou 730000, Gansu, Peoples R China
[3] Chinese Acad Sci, Inst Atmospher Phys IAP, Key Lab Reg Climate Environm Res Temperate East As, Beijing 100029, Peoples R China
关键词
Statistical downscaling; CMIP6; models; NEX-GDDP; Precipitation extremes; DENSE NETWORK; RESOLUTION; DATASET;
D O I
10.1016/j.atmosres.2024.107344
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The recently released NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is a highresolution daily downscaled dataset derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) model simulations. We comprehensively evaluated the performance of the NEX-GDDP dataset in simulating the characteristics of the climatological precipitation and extreme precipitation events across China from 1960 to 2014. We present here the projected changes in precipitation at the end of the 21st century (2070-2099) with respect to a reference period (1985-2014). We compared the NEX-GDDP dataset with both a state-of-the-art gauge data analysis system and the CMIP6 global climate models. The NEX-GDDP dataset significantly outperformed the CMIP6 simulations in replicating the climatological patterns of precipitation. It showed a closer alignment with the observed data, as evidenced by notably increased correlation coefficients and reduced modelrelative errors. The NEX-GDDP dataset exceled in accurately reproducing the spatial distribution of indices of extreme precipitation, surpassing the performance of the CMIP6 simulations. The projections show an increased frequency of heavy precipitation under higher emission scenarios in both datasets, with the CMIP6 simulations consistently estimating a higher probability of heavy rain than the NEX-GDDP dataset.
引用
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页数:12
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