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Significant Increase in Population Exposure to Extreme Precipitation in South China and Indochina in the Future

Bin Tang, Wenting Hu

2022Sustainability11 citationsDOIOpen Access PDF

Abstract

Extreme precipitation events cause severe economic losses and can seriously impact human health. Therefore, it is essential to project possible future changes in the population’s exposure to precipitation extremes against the background of global warming. On the basis of model outputs from phase 6 of the Coupled Model Intercomparison Project, our study shows that both the frequency and intensity of extreme precipitation are likely to increase in the South China and Indochina region in the coming century, especially under the business-as-usual Shared Socioeconomic Pathway (SSP) scenario, SSP5-8.5. The largest population exposure can be expected under the SSP2-4.5 scenario, both in South China and Indochina. If early adoption of mitigation measures via the SSP1-2.6 scenario can be achieved, it may be possible to limit the average population exposure in South China to a relatively low level, while Indochina’s may even be smaller than it is currently. In terms of spatial distribution, the maximum population exposure is most likely to be centered in southern South China. This study also reveals that the contribution of the population–climate interaction to population exposure is likely to increase in the future, and different contributions from the factors of climate and population correspond to different emission policies. Under SSP2-4.5, the importance of climate change and the population–climate interaction is more likely to increase.

Topics & Concepts

ChinaPopulationPrecipitationClimate changeClimatologyCoupled model intercomparison projectGeographyGlobal warmingEnvironmental sciencePopulation growthClimate modelSocioeconomic statusPopulation sizeClimate extremesPhysical geographyNatural resource economicsDemographyMeteorologyEcologyEconomicsGeologySociologyArchaeologyBiologyClimate Change and Health ImpactsClimate variability and modelsAir Quality and Health Impacts
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