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Simulation and estimation of future precipitation changes in arid regions: a case study of Xinjiang, Northwest China

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  • Haoyang Du

    (Nanjing University
    Nanjing University)

  • Chen Zhou

    (Nanjing University
    Nanjing University)

  • Haoqing Tang

    (Nanjing University
    Nanjing University)

  • Xiaolong Jin

    (Nanjing University
    Nanjing University)

  • Dengshuai Chen

    (Nanjing University
    Nanjing University)

  • Penghui Jiang

    (Nanjing University
    Nanjing University)

  • Manchun Li

    (Nanjing University
    Nanjing University)

Abstract

Precipitation is critical for maintaining the stability of an ecosystem, especially in arid regions. This study primarily focuses on climatic changes during present (from 1985 to 2005) and future (from 2040 to 2059) periods in Xinjiang, Northwest China. In this study, the Weather Research and Forecasting model is implemented in Xinjiang to efficiently predict the future climate. Moreover, the National Climate Research Center Community Climate System Model version 4 is employed for the mid-21st century under representative concentration pathways 4.5 and 8.5 (RCP4.5 and RCP8.5, respectively). Our results indicate that the amount of annual precipitation will increase in the future under RCP4.5 and RCP8.5 in Xinjiang, especially in mountainous areas. The increase in precipitation is predicted to be much smaller under RCP8.5 than under RCP4.5, except in Southern Xinjiang. Moreover, the increasing precipitation predicted in Xinjiang implies that the current humid and warm conditions will persist, thereby further indicating that Xinjiang is still currently suffering from a dry climate. The largest increase in seasonal precipitation is predicted to occur in spring and summer in Tianshan and Northern Xinjiang, whereas this phenomenon is predicted to occur in spring and winter in Southern Xinjiang. In addition, it is predicted that daily heavy precipitation events will occur more frequently in various subregions of Xinjiang, although light rain events will remain dominant. Finally, the relative humidity is closely related to the changes in annual and seasonal precipitation.

Suggested Citation

  • Haoyang Du & Chen Zhou & Haoqing Tang & Xiaolong Jin & Dengshuai Chen & Penghui Jiang & Manchun Li, 2021. "Simulation and estimation of future precipitation changes in arid regions: a case study of Xinjiang, Northwest China," Climatic Change, Springer, vol. 167(3), pages 1-21, August.
    • Handle: RePEc:spr:climat:v:167:y:2021:i:3:d:10.1007_s10584-021-03192-z
    DOI: 10.1007/s10584-021-03192-z
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    References listed on IDEAS

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    1. Li, Chaofan & Zhang, Chi & Luo, Geping & Chen, Xi, 2013. "Modeling the carbon dynamics of the dryland ecosystems in Xinjiang, China from 1981 to 2007—The spatiotemporal patterns and climate controls," Ecological Modelling, Elsevier, vol. 267(C), pages 148-157.
    2. Jascha Lehmann & Dim Coumou & Katja Frieler, 2015. "Increased record-breaking precipitation events under global warming," Climatic Change, Springer, vol. 132(4), pages 501-515, October.
    3. Juan Carlos Duque & Raúl Ramos & Jordi Suriñach, 2007. "Supervised Regionalization Methods: A Survey," International Regional Science Review, , vol. 30(3), pages 195-220, July.
    4. Alistair W. R. Seddon & Marc Macias-Fauria & Peter R. Long & David Benz & Kathy J. Willis, 2016. "Sensitivity of global terrestrial ecosystems to climate variability," Nature, Nature, vol. 531(7593), pages 229-232, March.
    5. V. Kharin & F. Zwiers & X. Zhang & M. Wehner, 2013. "Changes in temperature and precipitation extremes in the CMIP5 ensemble," Climatic Change, Springer, vol. 119(2), pages 345-357, July.
    6. Jascha Lehmann & Dim Coumou & Katja Frieler, 2015. "Erratum to: increased record-breaking precipitation events under global warming," Climatic Change, Springer, vol. 132(4), pages 517-518, October.
    7. E. M. Fischer & R. Knutti, 2016. "Observed heavy precipitation increase confirms theory and early models," Nature Climate Change, Nature, vol. 6(11), pages 986-991, November.
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    Cited by:

    1. Tang, Kai, 2024. "Agricultural adaptation to the environmental and social consequences of climate change in mixed farming systems: Evidence from North Xinjiang, China," Agricultural Systems, Elsevier, vol. 217(C).

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    Keywords

    WRF; Projected precipitation; CCSM4; RCP4.5; RCP8.5;
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