{"title":"印度东北部特里普拉邦各地潮湿模式和周期的变化","authors":"Saurav Saha, Gulav Singh Yadav, Dhiman Daschaudhuri, Mrinmoy Datta, Debasish Chakraborty, Sandip Sadhu, Bappa Das, Samik Chowdhury, V. Dayal, Anup Das, Basant Kandpal, Ingudam Shakuntala","doi":"10.54302/mausam.v75i1.4536","DOIUrl":null,"url":null,"abstract":"Region wetness variability was assessed across the Tripura state of North east India (1971 to 2016). Multiple Change point detection tests confirmed the high degree of spatiotemporal variability for the identified shifts in wetness pattern over study period. The periodicity of different wetness time-series varied between 2-128 months for the calculated SPI time scales over variable time series for the selected rain gauge stations. The periodicity pattern became more prominent with an increasing temporal domain of calculated SPI time series. Hierarchical clustering and Principle component analysis (PCA) accounted for the variability in randomness, trend and periodicity of all the SPI time series. Our present study identified the homogeneous clusters of raingauge stations suitable for real-time drought monitoring and reversible use of missing dataset on rainfall in near future across the Tripura state.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Shifts in wetness pattern and periodicity across Tripura state in north east India\",\"authors\":\"Saurav Saha, Gulav Singh Yadav, Dhiman Daschaudhuri, Mrinmoy Datta, Debasish Chakraborty, Sandip Sadhu, Bappa Das, Samik Chowdhury, V. Dayal, Anup Das, Basant Kandpal, Ingudam Shakuntala\",\"doi\":\"10.54302/mausam.v75i1.4536\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Region wetness variability was assessed across the Tripura state of North east India (1971 to 2016). Multiple Change point detection tests confirmed the high degree of spatiotemporal variability for the identified shifts in wetness pattern over study period. The periodicity of different wetness time-series varied between 2-128 months for the calculated SPI time scales over variable time series for the selected rain gauge stations. The periodicity pattern became more prominent with an increasing temporal domain of calculated SPI time series. Hierarchical clustering and Principle component analysis (PCA) accounted for the variability in randomness, trend and periodicity of all the SPI time series. Our present study identified the homogeneous clusters of raingauge stations suitable for real-time drought monitoring and reversible use of missing dataset on rainfall in near future across the Tripura state.\",\"PeriodicalId\":18363,\"journal\":{\"name\":\"MAUSAM\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MAUSAM\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.54302/mausam.v75i1.4536\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MAUSAM","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.54302/mausam.v75i1.4536","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Shifts in wetness pattern and periodicity across Tripura state in north east India
Region wetness variability was assessed across the Tripura state of North east India (1971 to 2016). Multiple Change point detection tests confirmed the high degree of spatiotemporal variability for the identified shifts in wetness pattern over study period. The periodicity of different wetness time-series varied between 2-128 months for the calculated SPI time scales over variable time series for the selected rain gauge stations. The periodicity pattern became more prominent with an increasing temporal domain of calculated SPI time series. Hierarchical clustering and Principle component analysis (PCA) accounted for the variability in randomness, trend and periodicity of all the SPI time series. Our present study identified the homogeneous clusters of raingauge stations suitable for real-time drought monitoring and reversible use of missing dataset on rainfall in near future across the Tripura state.
期刊介绍:
MAUSAM (Formerly Indian Journal of Meteorology, Hydrology & Geophysics), established in January 1950, is the quarterly research
journal brought out by the India Meteorological Department (IMD). MAUSAM is a medium for publication of original scientific
research work. MAUSAM is a premier scientific research journal published in this part of the world in the fields of Meteorology,
Hydrology & Geophysics. The four issues appear in January, April, July & October.