Abstract
Extreme climate events can cause large risks to ecosystems and human society in a short period. Investigating the changing trends of such events is essential for regional climate risk management. However, there is limited information on the regional assessment of the history and future trends of extreme climate events in Xinjiang, China. This study investigated the historical changes and projected trends of extreme climate events in Xinjiang based on observational data and Coupled Model Intercomparison Project phase 6 (CMIP6) model simulations. The results showed that the bias correction effectively reduced the bias of the CMIP6 model to the extreme climate indices simulation. During the period 1961–2014, the extreme indices representing warmth showed robust growth, while the extreme indices representing cold showed a robust decline. The intensity and frequency indices of extreme precipitation continued to increase, while consecutive dry days (CDDs) shortened and consecutive wet days (CWDs) lengthened. The changing trend of the extreme temperature indices had strong spatial consistency, while the changing trend of the extreme precipitation indices had obvious spatial heterogeneity. Based on the CMIP6 model simulations, the extreme climate indices in the twenty-first century were projected to continue the changing trend of the historical period (1961–2014). Compared with north Xinjiang (NXJ) and south Xinjiang (SXJ), the cold spell duration index (CSDI), cold nights (TN10p), cold days (TX10p), and extreme precipitation events in the Tianshan Mountains (TSM) were projected to experience stronger changes in the twenty-first century. The response of extreme temperature and extreme precipitation indices to global warming was approximately linear. Compared with SSP585, most extreme climate indices under the SSP245 scenario changed slightly in response to global warming. The superposition of the increase (decrease) in extreme warm (cold) events and the increase in extreme precipitation events will exacerbate the threat of extreme climate events to the agricultural and ecological security of the Xinjiang oasis, especially in the TSM. Given the limited water vapor sources and precipitation and the high rate of evapotranspiration, it is projected that the current situation of water shortages in Xinjiang will not be fundamentally changed.
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Availability of data and material
The daily maximum, minimum temperature and precipitation data simulated by 15 GCMs under the CMIP6 model from 1961 to 2100 were downloaded from the Earth System Grid Federation (https://esgf-node.llnl.gov/search/cmip6/). The daily maximum, minimum temperature, and precipitation observation data of Xinjiang from 1961 to 2014 can be downloaded through the National Meteorological Information Center of the China Meteorological Administration (http://data.cma.cn).
Code availability
The R package for “MBC” is available at https://cran.r-project.org/web/packages/MBC.
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Acknowledgements
The authors would like to thank the Earth System Grid Federation for the CMIP6 model output and the National Meteorological Information Center of the China Meteorological Administration for the meteorological data support. The author also thanks Professor Alex J. Cannon of Environment and Climate Change in Canada for his help in the use of the MBC method. Finally, the author would like to thank the editor and anonymous reviewers for their valuable comments and suggestions on this article.
Funding
This study has been supported by the National Natural Science Foundation of China (41461035 and U1903113) and the Second Tibetan Plateau Scientific Expedition and Research program (2019QZKK0102).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Jingyun Guan, Junqiang Yao, Moyan Li and Dong Li. The first draft of the manuscript was written by Jingyun Guan and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Guan, J., Yao, J., Li, M. et al. Historical changes and projected trends of extreme climate events in Xinjiang, China. Clim Dyn 59, 1753–1774 (2022). https://doi.org/10.1007/s00382-021-06067-2
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DOI: https://doi.org/10.1007/s00382-021-06067-2