{"title":"评估印度次大陆极端降雨变化的气候区划","authors":"Chandrani Chatterjee, Saurabh Das","doi":"10.23919/AT-AP-RASC54737.2022.9814196","DOIUrl":null,"url":null,"abstract":"Climate change and resulting increase in extreme events have become major sources of concern for the society today. Rainfall cycle and lightning extremities are among the most evidenced effects of recent climatic changes. However, quantifying the climate change effect over a region is challenging especially for a country like India with such enormous topographic and climatic variabilities. The current work attempted to regionalize Indian subcontinent based on the major climatic factors using machine learning techniques. The resulting regions have showed distinct interrelationship between the climate variable. Two regions showed significant increasing trend in number of extreme rainfall days(>40 mm) whereas, two other showed decreasing trends.","PeriodicalId":356067,"journal":{"name":"2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Climate regionalization to assess change in extreme rainfall over Indian subcontinent\",\"authors\":\"Chandrani Chatterjee, Saurabh Das\",\"doi\":\"10.23919/AT-AP-RASC54737.2022.9814196\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Climate change and resulting increase in extreme events have become major sources of concern for the society today. Rainfall cycle and lightning extremities are among the most evidenced effects of recent climatic changes. However, quantifying the climate change effect over a region is challenging especially for a country like India with such enormous topographic and climatic variabilities. The current work attempted to regionalize Indian subcontinent based on the major climatic factors using machine learning techniques. The resulting regions have showed distinct interrelationship between the climate variable. Two regions showed significant increasing trend in number of extreme rainfall days(>40 mm) whereas, two other showed decreasing trends.\",\"PeriodicalId\":356067,\"journal\":{\"name\":\"2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/AT-AP-RASC54737.2022.9814196\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/AT-AP-RASC54737.2022.9814196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Climate regionalization to assess change in extreme rainfall over Indian subcontinent
Climate change and resulting increase in extreme events have become major sources of concern for the society today. Rainfall cycle and lightning extremities are among the most evidenced effects of recent climatic changes. However, quantifying the climate change effect over a region is challenging especially for a country like India with such enormous topographic and climatic variabilities. The current work attempted to regionalize Indian subcontinent based on the major climatic factors using machine learning techniques. The resulting regions have showed distinct interrelationship between the climate variable. Two regions showed significant increasing trend in number of extreme rainfall days(>40 mm) whereas, two other showed decreasing trends.