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

缩小尺度 气候学 降水 环境科学 中国 气象学 气候模式 气候变化 地质学 地理 海洋学 考古
作者
Jinge Zhang,Chunxiang Li,Xiaobin Zhang,Tianbao Zhao
出处
期刊:Atmospheric Research [Elsevier BV]
卷期号:303: 107344-107344 被引量:26
标识
DOI:10.1016/j.atmosres.2024.107344
摘要

The recently released NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is a high-resolution 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 model-relative 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.
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