Abstract

The future state of drought in China under climate change remains uncertain. This study investigates drought events, focusing on the region of China, using simulations from five global climate models (GCMs) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5) participating in the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b). The daily Standardized Precipitation Evapotranspiration Index (SPEI) is employed to analyze drought severity, duration, and frequency over three future periods. Evaluation of the GCMs’ simulations against observational data indicates their effectiveness in capturing historical climatic change across China. The rapid increase in CO2 concentration under high-emission scenarios in the mid- and late-future century (2040–2070 and 2071–2100) substantially influences vegetation behavior via regulation on leaf stomata and canopy structure. This regulation decelerates the increase in potential evapotranspiration, thereby mitigating the sharp rise in future drought occurrences in China. These findings offer valuable insights for policymakers and stakeholders to develop strategies and measures for mitigating and adapting to future drought conditions in China.

Details

Title
Understanding climate change impacts on drought in China over the 21st century: a multi-model assessment from CMIP6
Author
Xu, Feng 1 ; Qu, Yanping 2 ; Bento, Virgílio A. 3 ; Song, Hongquan 4 ; Qiu, Jianxiu 5   VIAFID ORCID Logo  ; Qi, Junyu 6 ; Wan, Lingling 1 ; Zhang, Rongrong 1 ; Miao, Lijuan 7 ; Zhang, Xuesong 8   VIAFID ORCID Logo  ; Wang, Qianfeng 9   VIAFID ORCID Logo 

1  Fuzhou University, Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection/College of Environmental & Safety Engineering, Fuzhou, China (GRID:grid.411604.6) (ISNI:0000 0001 0130 6528) 
2  Research Center on Flood and Drought Disaster Reduction, China Institute of Water Resources and Hydropower Research, Beijing, China (GRID:grid.453304.5) (ISNI:0000 0001 0722 2552) 
3  Instituto Dom Luiz, University of Lisbon, Faculty of Sciences, Lisbon, Portugal (GRID:grid.9983.b) (ISNI:0000 0001 2181 4263) 
4  Henan University, College of Geography and Environmental Science, Kaifeng, China (GRID:grid.256922.8) (ISNI:0000 0000 9139 560X) 
5  Sun Yat-sen University, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Guangzhou, China (GRID:grid.12981.33) (ISNI:0000 0001 2360 039X) 
6  University of Maryland, College Park, 5825 University Research Court, Earth System Science Interdisciplinary Center, College Park, USA (GRID:grid.509513.b) 
7  Nanjing University of Information Science and Technology, School of Geographical Sciences, Nanjing, China (GRID:grid.260478.f) (ISNI:0000 0000 9249 2313) 
8  USDA-ARS Hydrology and Remote Sensing Laboratory Building 007, Room 104, BARC-West, Beltsville, USA (GRID:grid.507312.2) (ISNI:0000 0004 0617 0991) 
9  Fuzhou University, Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection/College of Environmental & Safety Engineering, Fuzhou, China (GRID:grid.411604.6) (ISNI:0000 0001 0130 6528); Key Lab of Spatial Data Mining & Information Sharing, Ministry of Education of China, Fuzhou, China (GRID:grid.419897.a) (ISNI:0000 0004 0369 313X) 
Pages
32
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
23973722
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41612-024-00578-5
ProQuest document ID
2919982671
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.