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author:

Xu, Feng (Xu, Feng.) [1] | Bento, Virgílio A. (Bento, Virgílio A..) [2] | Qu, Yanping (Qu, Yanping.) [3] | Wang, Qianfeng (Wang, Qianfeng.) [4]

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EI

Abstract:

Highlights: What are the main findings? The future drought conditions predicted by AWI-CM-1-1-MR and MPI-ESM1-2-HR are relatively reasonable. However, EC-Earth3 tends to underestimate future drought conditions. Drought conditions across much of the globe are expected to become increasingly serious, and the trend is significant. The drought events in much of the world are mainly driven by precipitation. What is the implication of the main finding? We found that the primary reason for the substantial differences in drought predictions among the three models is the overestimation of future precipitation by EC-Earth3. The future drought conditions in most regions around the world are expected to worsen. Due to the complex coupling between drought and climatic factors, the future drought conditions that might occur under climate change is still unclear. In this research, we used the daily SPEI algorithm to project global drought conditions during 2016–2100 based on the data from phase 6 of the Coupled Model Intercomparison Project (CMIP6). We also employed partial correlation analysis to explore the influence of climate factors on drought. Our analyses show the following: (1) Drought conditions projected by CMIP6 under different models are similar; however, they can vary widely across regions. (2) According to the MK trend test, drought conditions in most regions around the world are expected to become increasingly severe in the future, and this trend is significant. (3) Based on the results of the partial correlation analysis results, it is understood that drought events in most regions worldwide are primarily driven by precipitation. This study contributes to the discussion of projecting future drought conditions and expands the application by utilizing the state−of−the−art CMIP6 climate models and scenarios.Highlight. © 2023 by the authors.

Keyword:

Climate change Climate models Correlation methods Drought

Community:

  • [ 1 ] [Xu, Feng]Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection, College of Environmental & Safety Engineering, Fuzhou University, Fuzhou; 350116, China
  • [ 2 ] [Bento, Virgílio A.]Instituto Dom Luiz, Faculty of Sciences, University of Lisbon, Lisbon; 1749-016, Portugal
  • [ 3 ] [Qu, Yanping]China Institute of Water Resources & Hydropower Research, Research Center on Flood & Drought Disaster Reduction, Beijing; 100038, China
  • [ 4 ] [Wang, Qianfeng]Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection, College of Environmental & Safety Engineering, Fuzhou University, Fuzhou; 350116, China
  • [ 5 ] [Wang, Qianfeng]Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education of China, Fuzhou; 350116, China

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Source :

Water (Switzerland)

Year: 2023

Issue: 12

Volume: 15

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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