Extreme climate events and future population exposure under climate change in the Huaihe River basin of China based on CMIP6 multimodel ensembles projections

IF 3.5 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Tian Yao, Chuanhao Wu, Pat J.-F. Yeh, Jiayun Li, Xuan Wang, Jiahao Cheng, Jun Zhou, Bill X. Hu
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Abstract

The Huaihe River basin (HRB) of China located in the climate transition zone between warm temperate and subtropical areas is highly sensitive to climatic change. However, the changes in future climate extreme events under anthropogenic warming and the population exposure to these climate extremes in HRB remain unexplored. Here, using the eight commonly used extreme climate indices and based on the bias-corrections of 16 global climate models (GCMs) in CMIP6, we present a projection and uncertainty analysis of extreme events and investigate the corresponding population exposure risk in HRB under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5). The 16-GCM ensemble mean projects an evident warming trend under all three scenarios with a total increase of 25.6–68.0 days in summer days (>25°C) by the end of the century in HRB. Larger increases (decreases) in maximum and minimum temperatures (frost days) are projected in the western HRB. Very heavy rain days (R20mm), maximum 5-day precipitation (RX5day) and simple daily intensity index (SDII) will experience intensification across most of HRB (especially in southern and western HRB). The consecutive dry days is projected to decrease in northwestern HRB and increase in southern HRB. However, there is a large spatial variability in GCM uncertainty with a higher SSP scenario generally having higher uncertainty. Increases in summer days and R20mm exacerbate population exposure in HRB in near future (2030–2059), but in far future (2070–2099) although summer days (R20mm) continues to rise, population exposure is expected to decrease due to the rapid decline in population density.

基于 CMIP6 多模型集合预测的中国淮河流域极端气候事件和未来人口在气候变化下的暴露程度
中国淮河流域位于暖温带和亚热带之间的气候过渡带,对气候变化高度敏感。然而,淮河流域在人为气候变暖条件下未来极端气候事件的变化以及人口对这些极端气候事件的暴露程度仍未得到研究。在此,我们利用八个常用的极端气候指数,基于 CMIP6 中 16 个全球气候模式(GCMs)的偏差校正,对极端事件进行了预测和不确定性分析,并研究了在三种共同的社会经济路径(SSP1-2.6、SSP2-4.5、SSP5-8.5)下人力资源局相应的人口暴露风险。根据 16 个大气环流模型的集合平均值预测,在所有三种情景下都会出现明显的变暖趋势,到本世纪末,HRB 的夏季总天数将增加 25.6-68.0 天(25°C)。预计人力资源局西部的最高气温和最低气温(霜冻日)将有较大幅度的增加(减少)。特大暴雨日(R20 毫米)、5 天最大降水量(RX5 天)和简单日降水强度指数(SDII)将在人力资源局的大部分地区(尤其是人力资源局南部和西部)加剧。预计西北部地区连续干旱日数将减少,南部地区将增加。然而,GCM 的不确定性存在很大的空间差异,SSP 较高的情景通常具有较高的不确定性。在近期(2030-2059 年),夏季日数和 R20mm 的增加加剧了 HRB 的人口暴露,但在远期(2070-2099 年),虽然夏季日数(R20mm)继续增加,但由于人口密度的快速下降,人口暴露预计会减少。
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来源期刊
International Journal of Climatology
International Journal of Climatology 地学-气象与大气科学
CiteScore
7.50
自引率
7.70%
发文量
417
审稿时长
4 months
期刊介绍: The International Journal of Climatology aims to span the well established but rapidly growing field of climatology, through the publication of research papers, short communications, major reviews of progress and reviews of new books and reports in the area of climate science. The Journal’s main role is to stimulate and report research in climatology, from the expansive fields of the atmospheric, biophysical, engineering and social sciences. Coverage includes: Climate system science; Local to global scale climate observations and modelling; Seasonal to interannual climate prediction; Climatic variability and climate change; Synoptic, dynamic and urban climatology, hydroclimatology, human bioclimatology, ecoclimatology, dendroclimatology, palaeoclimatology, marine climatology and atmosphere-ocean interactions; Application of climatological knowledge to environmental assessment and management and economic production; Climate and society interactions
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