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Anthropogenic shift towards higher risk of flash drought over China

Author

Listed:
  • Xing Yuan

    (Nanjing University of Information Science and Technology
    Chinese Academy of Sciences)

  • Linying Wang

    (Chinese Academy of Sciences)

  • Peili Wu

    (Met Office Hadley Centre)

  • Peng Ji

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Justin Sheffield

    (University of Southampton)

  • Miao Zhang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

Abstract

Flash droughts refer to a type of droughts that have rapid intensification without sufficient early warning. To date, how will the flash drought risk change in a warming future climate remains unknown due to a diversity of flash drought definition, unclear role of anthropogenic fingerprints, and uncertain socioeconomic development. Here we propose a new method for explicitly characterizing flash drought events, and find that the exposure risk over China will increase by about 23% ± 11% during the middle of this century under a socioeconomic scenario with medium challenge. Optimal fingerprinting shows that anthropogenic climate change induced by the increased greenhouse gas concentrations accounts for 77% ± 26% of the upward trend of flash drought frequency, and population increase is also an important factor for enhancing the exposure risk of flash drought over southernmost humid regions. Our results suggest that the traditional drought-prone regions would expand given the human-induced intensification of flash drought risk.

Suggested Citation

  • Xing Yuan & Linying Wang & Peili Wu & Peng Ji & Justin Sheffield & Miao Zhang, 2019. "Anthropogenic shift towards higher risk of flash drought over China," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12692-7
    DOI: 10.1038/s41467-019-12692-7
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    Citations

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    Cited by:

    1. Jinhua Wen & Yian Hua & Chenkai Cai & Shiwu Wang & Helong Wang & Xinyan Zhou & Jian Huang & Jianqun Wang, 2023. "Probabilistic Forecast and Risk Assessment of Flash Droughts Based on Numeric Weather Forecast: A Case Study in Zhejiang, China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    2. Xiaoyan Sun & Xiaoyu Gao & Yali Luo & Wai-Kin Wong & Haiming Xu, 2022. "A Comparative Analysis of Characteristics and Synoptic Backgrounds of Extreme Heat Events over Two Urban Agglomerations in Southeast China," Land, MDPI, vol. 11(12), pages 1-18, December.
    3. Julia S. Stoyanova & Christo G. Georgiev & Plamen N. Neytchev, 2023. "Drought Monitoring in Terms of Evapotranspiration Based on Satellite Data from Meteosat in Areas of Strong Land–Atmosphere Coupling," Land, MDPI, vol. 12(1), pages 1-21, January.
    4. Yamin Qing & Shuo Wang & Brian C. Ancell & Zong-Liang Yang, 2022. "Accelerating flash droughts induced by the joint influence of soil moisture depletion and atmospheric aridity," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    5. Jordan I. Christian & Jeffrey B. Basara & Eric D. Hunt & Jason A. Otkin & Jason C. Furtado & Vimal Mishra & Xiangming Xiao & Robb M. Randall, 2021. "Global distribution, trends, and drivers of flash drought occurrence," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    6. Feng Chen & Hadad Martín & Xiaoen Zhao & Fidel Roig & Heli Zhang & Shijie Wang & Weipeng Yue & Youping Chen, 2022. "Abnormally low precipitation-induced ecological imbalance contributed to the fall of the Ming Dynasty: new evidence from tree rings," Climatic Change, Springer, vol. 173(1), pages 1-16, July.
    7. Zhang, Yu & Liu, Xiaohong & Jiao, Wenzhe & Zhao, Liangju & Zeng, Xiaomin & Xing, Xiaoyu & Zhang, Lingnan & Hong, Yixue & Lu, Qiangqiang, 2022. "A new multi-variable integrated framework for identifying flash drought in the Loess Plateau and Qinling Mountains regions of China," Agricultural Water Management, Elsevier, vol. 265(C).
    8. Guga, Suri & Ma, Yining & Riao, Dao & Zhi, Feng & Xu, Jie & Zhang, Jiquan, 2023. "Drought monitoring of sugarcane and dynamic variation characteristics under global warming: A case study of Guangxi, China," Agricultural Water Management, Elsevier, vol. 275(C).

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