Pei Fang, Taihua Wang, Dawen Yang, Lihua Tang, Yuting Yang
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引用次数: 0
Abstract
Under climate change, China faces intensifying compound extreme events with serious socio-economic ramifications, yet their future variations remain poorly understood. Here, we estimate historical hotspots and future changes of two typical compound events, i.e., sequential heatwave and precipitation (SHP) and concurrent drought and heatwave (CDH) across China, leveraging a bivariate bias correction method to adjust projections from global climate models. Results show substantial future increases in frequency, duration, and magnitude for both events, with the durations projected to double nationwide. The increases are more evident under higher emission scenarios, and could be largely underestimated if neglecting variable dependence during bias correction process. The projected changes will escalate socio-economic exposure across China’s major urban clusters, among which Guangdong-Hong Kong-Macao will face the highest risk. Our findings underscore the necessity of carbon emission controls, and call for adaptive measures to mitigate the threats induced by rising compound hazards in a changing climate.
期刊介绍:
npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols.
The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.