{"title":"北印度洋季风后月份热带气旋活动的季节性预测","authors":"Neeru Jaiswal, Randhir Singh","doi":"10.1002/joc.8457","DOIUrl":null,"url":null,"abstract":"<p>The frequency and power dissipation index (PDI) of tropical cyclones (TCs) in the North Indian Ocean (NIO) has dramatically grown over the last 10 years, according to our analysis utilizing the European Centre for Medium Range Weather Forecasts reanalysis version-5 (ERA5) dataset and the India Meteorological Department (IMD) best track data over the period 1982–2021. Our findings indicate that the recent increase in the post-monsoon TC PDI over NIO is caused by a reduction in wind shear and an increase in convective available potential energy over the Bay of Bengal. The importance of improving our understanding and developing more accurate predictions of the TCs activity has increased as TCs become more frequent and intense owing to the effects of global warming. This study therefore develops TC prediction models for frequency and PDI over NIO for various lead times that vary from 2 to 8 months in addition to the trend analysis employing the ERA5 and IMD best track data. The potential predictors used in proposed model are surface temperature (2 m temperature over land and sea surface temperature over oceanic regions), vertical wind shear, winds (zonal, meridional), geopotential height and temperature at different pressure levels during January–August. The developed models are remarkably accurate (skill is ~94%) in forecasting TCs frequency and PDI. The proposed models outperform the best performing models that are already in use for long-range TC activity prediction. With a lead-time as long as up to 8 months, this effort is the first to investigate the possibility of forecasting the frequency and PDI of post-monsoon TC activity over the NIO with good accuracy. Therefore, the developed models show an operational potential for seasonal TC activity forecast over the NIO.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Seasonal prediction of tropical cyclones activity in the North Indian Ocean during post-monsoon months\",\"authors\":\"Neeru Jaiswal, Randhir Singh\",\"doi\":\"10.1002/joc.8457\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The frequency and power dissipation index (PDI) of tropical cyclones (TCs) in the North Indian Ocean (NIO) has dramatically grown over the last 10 years, according to our analysis utilizing the European Centre for Medium Range Weather Forecasts reanalysis version-5 (ERA5) dataset and the India Meteorological Department (IMD) best track data over the period 1982–2021. Our findings indicate that the recent increase in the post-monsoon TC PDI over NIO is caused by a reduction in wind shear and an increase in convective available potential energy over the Bay of Bengal. The importance of improving our understanding and developing more accurate predictions of the TCs activity has increased as TCs become more frequent and intense owing to the effects of global warming. This study therefore develops TC prediction models for frequency and PDI over NIO for various lead times that vary from 2 to 8 months in addition to the trend analysis employing the ERA5 and IMD best track data. The potential predictors used in proposed model are surface temperature (2 m temperature over land and sea surface temperature over oceanic regions), vertical wind shear, winds (zonal, meridional), geopotential height and temperature at different pressure levels during January–August. The developed models are remarkably accurate (skill is ~94%) in forecasting TCs frequency and PDI. The proposed models outperform the best performing models that are already in use for long-range TC activity prediction. With a lead-time as long as up to 8 months, this effort is the first to investigate the possibility of forecasting the frequency and PDI of post-monsoon TC activity over the NIO with good accuracy. Therefore, the developed models show an operational potential for seasonal TC activity forecast over the NIO.</p>\",\"PeriodicalId\":13779,\"journal\":{\"name\":\"International Journal of Climatology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Climatology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/joc.8457\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Climatology","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/joc.8457","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Seasonal prediction of tropical cyclones activity in the North Indian Ocean during post-monsoon months
The frequency and power dissipation index (PDI) of tropical cyclones (TCs) in the North Indian Ocean (NIO) has dramatically grown over the last 10 years, according to our analysis utilizing the European Centre for Medium Range Weather Forecasts reanalysis version-5 (ERA5) dataset and the India Meteorological Department (IMD) best track data over the period 1982–2021. Our findings indicate that the recent increase in the post-monsoon TC PDI over NIO is caused by a reduction in wind shear and an increase in convective available potential energy over the Bay of Bengal. The importance of improving our understanding and developing more accurate predictions of the TCs activity has increased as TCs become more frequent and intense owing to the effects of global warming. This study therefore develops TC prediction models for frequency and PDI over NIO for various lead times that vary from 2 to 8 months in addition to the trend analysis employing the ERA5 and IMD best track data. The potential predictors used in proposed model are surface temperature (2 m temperature over land and sea surface temperature over oceanic regions), vertical wind shear, winds (zonal, meridional), geopotential height and temperature at different pressure levels during January–August. The developed models are remarkably accurate (skill is ~94%) in forecasting TCs frequency and PDI. The proposed models outperform the best performing models that are already in use for long-range TC activity prediction. With a lead-time as long as up to 8 months, this effort is the first to investigate the possibility of forecasting the frequency and PDI of post-monsoon TC activity over the NIO with good accuracy. Therefore, the developed models show an operational potential for seasonal TC activity forecast over the NIO.
期刊介绍:
The International Journal of Climatology aims to span the well established but rapidly growing field of climatology, through the publication of research papers, short communications, major reviews of progress and reviews of new books and reports in the area of climate science. The Journal’s main role is to stimulate and report research in climatology, from the expansive fields of the atmospheric, biophysical, engineering and social sciences. Coverage includes: Climate system science; Local to global scale climate observations and modelling; Seasonal to interannual climate prediction; Climatic variability and climate change; Synoptic, dynamic and urban climatology, hydroclimatology, human bioclimatology, ecoclimatology, dendroclimatology, palaeoclimatology, marine climatology and atmosphere-ocean interactions; Application of climatological knowledge to environmental assessment and management and economic production; Climate and society interactions