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Predicting Changes in Population Exposure to Precipitation Extremes over Beijing–Tianjin–Hebei Urban Agglomeration with Regional Climate Model RegCM4 on a Convection-Permitting Scale

Author

Listed:
  • Peihua Qin

    (State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China)

  • Zhenghui Xie

    (State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China)

  • Binghao Jia

    (State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China)

  • Rui Han

    (Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China)

  • Buchun Liu

    (Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China)

Abstract

In this study, we have investigated changes in precipitation extremes and the population’s exposure to these extremes during 2091–2099 in China’s Beijing–Tianjin–Hebei (JJJ) region relative to the historical period of 1991–1999. First, the regional climate model RegCM4, with a hydrostatic dynamic core, was run for east Asia, including China, at a 12 km resolution for 1990–1999 and 2090–2099. This model is forced by global climate model (GCM) MPI-ESM1.2-HR under the middle shared socioeconomic pathways (SSP245). The first year was used as a model spinup. Then, the 12 km results were used to force RegCM4 with a non-hydrostatic dynamic core (RegcM4-NH) at a 3 km convection-permitting scale over the JJJ region during the historical and future periods. Future precipitation extremes were predicted to increase over the whole of China and its four subregions, while decreases were predicted over the JJJ region. This may partly be caused by lower increases in specific humidity over the JJJ region. The percentage contributions of the three components of total population exposure, i.e., changes in exposure due to changes in the population, precipitation extremes and the joint impact of the population and extremes, were then analyzed. Changes in the population and wet extremes were closely related to changes in the total exposure over the JJJ region. The population is the dominant factor that most impacts the total exposure to dry extremes. Finally, changes in future population exposure to precipitation extremes per degree of warming were quantified for the JJJ region.

Suggested Citation

  • Peihua Qin & Zhenghui Xie & Binghao Jia & Rui Han & Buchun Liu, 2023. "Predicting Changes in Population Exposure to Precipitation Extremes over Beijing–Tianjin–Hebei Urban Agglomeration with Regional Climate Model RegCM4 on a Convection-Permitting Scale," Sustainability, MDPI, vol. 15(15), pages 1-21, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11923-:d:1209471
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    References listed on IDEAS

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    1. Avantika Gori & Ning Lin & Dazhi Xi & Kerry Emanuel, 2022. "Publisher Correction: Tropical cyclone climatology change greatly exacerbates US extreme rainfall–surge hazard," Nature Climate Change, Nature, vol. 12(5), pages 491-491, May.
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    3. Bryan Jones & Claudia Tebaldi & Brian C. O’Neill & Keith Oleson & Jing Gao, 2018. "Avoiding population exposure to heat-related extremes: demographic change vs climate change," Climatic Change, Springer, vol. 146(3), pages 423-437, February.
    4. Xuebin Zhang & Lisa Alexander & Gabriele C. Hegerl & Philip Jones & Albert Klein Tank & Thomas C. Peterson & Blair Trewin & Francis W. Zwiers, 2011. "Indices for monitoring changes in extremes based on daily temperature and precipitation data," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 2(6), pages 851-870, November.
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