Seasonal prediction of tropical cyclones activity in the North Indian Ocean during post-monsoon months

被引:1
|
作者
Jaiswal, Neeru [1 ,2 ]
Singh, Randhir [1 ]
机构
[1] Space Applicat Ctr ISRO Ahmedabad, Atmospher & Ocean Sci Grp, EPSA, Ahmadabad, India
[2] Space Applicat Ctr ISRO Ahmedabad, Atmospher & Ocean Sci Grp, EPSA, Ahmadabad, Gujarat, India
关键词
jack-knife; North Indian Ocean; regression; seasonal prediction; trend analysis; tropical cyclone; EL-NINO; INTERANNUAL VARIATION; PACIFIC; INTENSITY; FORECASTS; IMPACTS; ENSO;
D O I
10.1002/joc.8457
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
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 similar to 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.
引用
收藏
页码:2343 / 2362
页数:20
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