Robust projection of East Asian summer monsoon rainfall based on dynamical modes of variability

Daokai Xue (), Jian Lu (), L. Ruby Leung, Haiyan Teng, Fengfei Song, Tianjun Zhou and Yaocun Zhang
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Daokai Xue: Nanjing University
Jian Lu: Pacific Northwest National Laboratory
L. Ruby Leung: Pacific Northwest National Laboratory
Haiyan Teng: Lawrence Berkeley National Laboratory
Fengfei Song: Ocean University of China
Tianjun Zhou: Chinese Academy of Sciences
Yaocun Zhang: Nanjing University

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: Abstract The Asian monsoon provides the freshwater that a large population in Asia depends on, but how anthropogenic climate warming may alter this key water source remains unclear. This is partly due to the prevailing point-wise assessment of climate projections, even though climate change patterns are inherently organized by dynamics intrinsic to the climate system. Here, we assess the future changes in the East Asian summer monsoon precipitation by projecting the precipitation from several large ensemble simulations and CMIP6 simulations onto the two leading dynamical modes of internal variability. The result shows a remarkable agreement among the ensembles on the increasing trends and the increasing daily variability in both dynamical modes, with the projection pattern emerging as early as the late 2030 s. The increase of the daily variability of the modes heralds more monsoon-related hydrological extremes over some identifiable East Asian regions in the coming decades.

Date: 2023
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DOI: 10.1038/s41467-023-39460-y

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