Evaluation and projection of precipitation extremes under 1.5°C and 2.0°C GWLs over China using bias-corrected CMIP6 models

Junhong Guo; Yangshuo Shen; Xiuquan Wang; Xi Liang; Zhenlu Liu; Lvliu Liu

doi:10.1016/j.isci.2023.106179

Evaluation and projection of precipitation extremes under 1.5°C and 2.0°C GWLs over China using bias-corrected CMIP6 models

iScience. 2023 Feb 14;26(4):106179. doi: 10.1016/j.isci.2023.106179. eCollection 2023 Apr 21.

Authors

Junhong Guo¹, Yangshuo Shen², Xiuquan Wang³, Xi Liang⁴, Zhenlu Liu¹, Lvliu Liu⁵

Affiliations

¹ MOE Key Laboratory of Resource and Environmental, System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China.
² School of Economics and Management, North China Electric Power University, Beijing 102206, China.
³ School of Climate Change and Adaptation, University of Prince Edward Island, Charlottetown, Prince Edward Island C1A 4P3, Canada.
⁴ Sustainable Finance and Infrastructure Transition, Bartlett School of Sustainable Construction, University College London, London WC1E 6BT, UK.
⁵ Beijing Climate Centre, China Meteorological Administration, Beijing, China.

Abstract

China is facing an increasing challenge from severe precipitation-related extremes with accelerating global warming. In this study, using a bias-corrected CMIP6 ensemble, future responses of precipitation extreme indices at 1.5°C and 2.0°C global warming levels (GWLs) under the SSP245, SSP370 and SSP585 scenarios are investigated. Despite different change magnitudes, extreme precipitation events will be more frequent and more intense over China as a whole under higher emissions and GWLs. The increase in annual total precipitation could attribute to a sharp increase in the intensity and days of very heavy precipitation in future global warming scenarios. Limiting global warming to 1.5°C and low emission pathways (i.e., SSP245) instead of 2°C and high emission pathways (i.e., SSP585) would have substantial benefits for China in terms of reducing occurrences of extreme precipitation events.

Keywords: Atmospheric science; Global change; Meteorology.