Gengxi Zhang, Hongkai Wang, Wenfei Liu, Huimin Wang
{"title":"中国各地在 1.5℃和 2.0℃升温水平下社会经济受复合干热事件影响的预测和不确定性分析","authors":"Gengxi Zhang, Hongkai Wang, Wenfei Liu, Huimin Wang","doi":"10.1007/s00704-024-05085-4","DOIUrl":null,"url":null,"abstract":"<p>Climate change is expected to intensify compound dry and hot events (CDHEs) in China, exacerbating socioeconomic exposure to CDHEs. Based on 23 global climate models (GCMs) data from Coupled Model Intercomparison Project 6 (CMIP6), this study analyzes and projects the socioeconomic exposure to CDHEs and its influencing factors under 1.5℃ and 2.0℃ global warming levels. The results show that the frequency of CDHEs is expected to be higher under 2.0℃ warming levels than that under 1.5℃ warming levels. Population exposures to CDHEs are projected to increase by 160 × 10<sup>6</sup> persons-months (about 280%) and 210 × 10<sup>6</sup> persons-months (310%) under 1.5℃ and 2.0℃ warming levels, respectively. The region with the highest increase in population exposure to CDHEs is East China, followed by Central China and South China; and the regions with the smallest increase in population exposure are Tibet, Inner Mongolia, and Xinjiang. GDP exposures are expected to increase by 24 times and 20 times under 1.5 °C warming levels for SSP2-4.5 and SSP5-8.5 scenarios, while the values would be up to 38 times and 28 times under 2.0 °C warming levels. The climate effect (accounting for 80%) is the determinate factor that triggers the change of population exposure to CDHEs, followed by the interaction between the population and climate changes, while the influence of the population factor is the least. Interactive effect contributes the most to GDP exposure whereas climate change contributes the least. Across most regions of China, the warming level is the main uncertainty source, accounting for 46.1% and 70.5% of the population and GDP exposure, respectively. The results are beneficial for identifying hotspots of vulnerable regions exposed to CDHEs and provide beneficial information for conducting climate change mitigation and adaptation strategies.</p>","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":"36 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Projections and uncertainty analysis of socioeconomic exposure to compound dry and hot events under 1.5℃ and 2.0℃ warming levels across China\",\"authors\":\"Gengxi Zhang, Hongkai Wang, Wenfei Liu, Huimin Wang\",\"doi\":\"10.1007/s00704-024-05085-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Climate change is expected to intensify compound dry and hot events (CDHEs) in China, exacerbating socioeconomic exposure to CDHEs. Based on 23 global climate models (GCMs) data from Coupled Model Intercomparison Project 6 (CMIP6), this study analyzes and projects the socioeconomic exposure to CDHEs and its influencing factors under 1.5℃ and 2.0℃ global warming levels. The results show that the frequency of CDHEs is expected to be higher under 2.0℃ warming levels than that under 1.5℃ warming levels. Population exposures to CDHEs are projected to increase by 160 × 10<sup>6</sup> persons-months (about 280%) and 210 × 10<sup>6</sup> persons-months (310%) under 1.5℃ and 2.0℃ warming levels, respectively. The region with the highest increase in population exposure to CDHEs is East China, followed by Central China and South China; and the regions with the smallest increase in population exposure are Tibet, Inner Mongolia, and Xinjiang. GDP exposures are expected to increase by 24 times and 20 times under 1.5 °C warming levels for SSP2-4.5 and SSP5-8.5 scenarios, while the values would be up to 38 times and 28 times under 2.0 °C warming levels. The climate effect (accounting for 80%) is the determinate factor that triggers the change of population exposure to CDHEs, followed by the interaction between the population and climate changes, while the influence of the population factor is the least. Interactive effect contributes the most to GDP exposure whereas climate change contributes the least. Across most regions of China, the warming level is the main uncertainty source, accounting for 46.1% and 70.5% of the population and GDP exposure, respectively. The results are beneficial for identifying hotspots of vulnerable regions exposed to CDHEs and provide beneficial information for conducting climate change mitigation and adaptation strategies.</p>\",\"PeriodicalId\":22945,\"journal\":{\"name\":\"Theoretical and Applied Climatology\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theoretical and Applied Climatology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s00704-024-05085-4\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical and Applied Climatology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s00704-024-05085-4","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Projections and uncertainty analysis of socioeconomic exposure to compound dry and hot events under 1.5℃ and 2.0℃ warming levels across China
Climate change is expected to intensify compound dry and hot events (CDHEs) in China, exacerbating socioeconomic exposure to CDHEs. Based on 23 global climate models (GCMs) data from Coupled Model Intercomparison Project 6 (CMIP6), this study analyzes and projects the socioeconomic exposure to CDHEs and its influencing factors under 1.5℃ and 2.0℃ global warming levels. The results show that the frequency of CDHEs is expected to be higher under 2.0℃ warming levels than that under 1.5℃ warming levels. Population exposures to CDHEs are projected to increase by 160 × 106 persons-months (about 280%) and 210 × 106 persons-months (310%) under 1.5℃ and 2.0℃ warming levels, respectively. The region with the highest increase in population exposure to CDHEs is East China, followed by Central China and South China; and the regions with the smallest increase in population exposure are Tibet, Inner Mongolia, and Xinjiang. GDP exposures are expected to increase by 24 times and 20 times under 1.5 °C warming levels for SSP2-4.5 and SSP5-8.5 scenarios, while the values would be up to 38 times and 28 times under 2.0 °C warming levels. The climate effect (accounting for 80%) is the determinate factor that triggers the change of population exposure to CDHEs, followed by the interaction between the population and climate changes, while the influence of the population factor is the least. Interactive effect contributes the most to GDP exposure whereas climate change contributes the least. Across most regions of China, the warming level is the main uncertainty source, accounting for 46.1% and 70.5% of the population and GDP exposure, respectively. The results are beneficial for identifying hotspots of vulnerable regions exposed to CDHEs and provide beneficial information for conducting climate change mitigation and adaptation strategies.
期刊介绍:
Theoretical and Applied Climatology covers the following topics:
- climate modeling, climatic changes and climate forecasting, micro- to mesoclimate, applied meteorology as in agro- and forestmeteorology, biometeorology, building meteorology and atmospheric radiation problems as they relate to the biosphere
- effects of anthropogenic and natural aerosols or gaseous trace constituents
- hardware and software elements of meteorological measurements, including techniques of remote sensing