{"title":"Long-term changes in spatially coherent extreme precipitation systems over Central India","authors":"Anu Gupta, Hiroshi G. Takahashi","doi":"10.1002/asl.1118","DOIUrl":null,"url":null,"abstract":"<p>The present study examined extreme rainfall events (EREs) in central India during the summer monsoon season, focusing on their spatial characteristics. A station-based gridded and a station-satellite-blended dataset was used to examine long-term and recent variations in precipitation characteristics for 50 years (1951–2000) and 38 years (1981–2018), respectively. A precipitation system approach (PSA) was applied to identify the ERE precipitation systems and categorized spatial sizes of ERE systems into three categories: sporadic, intermediate, and massive ERE precipitation systems. Conventionally, the ERE frequency is equal to the total number of ERE grids, whereas PSA counts ERE systems. The sporadic precipitation grid contributes 42% of all the ERE grids, and sporadic EREs frequency increases in the long-term. The long-term trend of intermediate and massive EREs does not increase and quite sharply increases, respectively, and these EREs are also intensifying. Recent 38 years have shown a reverse in the trends of ERE characteristics, the frequency and intensity of intermediate and massive EREs have decreased, whereas the massive ERE systems are broadening.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"23 11","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/asl.1118","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Science Letters","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/asl.1118","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}
引用次数: 0
Abstract
The present study examined extreme rainfall events (EREs) in central India during the summer monsoon season, focusing on their spatial characteristics. A station-based gridded and a station-satellite-blended dataset was used to examine long-term and recent variations in precipitation characteristics for 50 years (1951–2000) and 38 years (1981–2018), respectively. A precipitation system approach (PSA) was applied to identify the ERE precipitation systems and categorized spatial sizes of ERE systems into three categories: sporadic, intermediate, and massive ERE precipitation systems. Conventionally, the ERE frequency is equal to the total number of ERE grids, whereas PSA counts ERE systems. The sporadic precipitation grid contributes 42% of all the ERE grids, and sporadic EREs frequency increases in the long-term. The long-term trend of intermediate and massive EREs does not increase and quite sharply increases, respectively, and these EREs are also intensifying. Recent 38 years have shown a reverse in the trends of ERE characteristics, the frequency and intensity of intermediate and massive EREs have decreased, whereas the massive ERE systems are broadening.
期刊介绍:
Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques.
We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.