Abstract

AbstractPrecipitation extremes over the Indochina and South China (INCSC) region simulated by 40 global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) were quantitatively assessed based on the skill score metrics of four extreme precipitation indices when compared with observational results from a high-resolution daily precipitation dataset for 1958–2014. The results show that it is difficult for most of the CMIP6 models to reproduce the observed spatial pattern of extreme precipitation indices in the INCSC region. The interannual variability of the extreme precipitation indices is relatively better simulated for South China than for Indochina. In general, most of the CMIP6 models perform better in South China compared with Indochina when taking both the simulations of spatial pattern and interannual variability into consideration. Only three models (EC-EARTH3, EC-EARTH3-Veg, and NorESM2-MM) can successfully reproduce both the spatial pattern and the interannual variability for the INCSC region. Through model ranking, the multimodel ensemble generated by a selection of the most skillful models leads to a more realistic simulation of the extreme precipitation indices both in South China and Indochina. Better simulation of the meridional wind component over South China and the water vapor convergence over Indochina can partly reduce the wet biases, resulting in a more realistic simulation of extreme precipitation indices over the INCSC region.

Highlights

  • Evidence has shown that the global climate has undergone a significant change characterized by warming over the past century (IPCC 2007, 2013)

  • We quantitatively evaluated and ranked CMIP6 models based on their performance in simulating the spatial pattern and temporal variability of extreme precipitation indices in South China and Indochina for the period 1958–2014

  • The wet bias over Indochina that exists in CMIP5 models still exists in CMIP6 models

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Summary

15 SEPTEMBER 2021

Chinese Academy of Sciences, Beijing, China b University of Chinese Academy of Sciences, Beijing, China (Manuscript received 9 December 2020, in final form 20 May 2021)

Introduction
Model evaluation
Performance of optimal models
Findings
Conclusions and discussion

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