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DOI10.1016/j.atmosres.2020.105089
Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models
Wahiduzzaman M.; Yeasmin A.; Luo J.-J.
发表日期2020
ISSN0169-8095
卷号245
英文摘要In this study, the contribution of atmospheric climate variables to the prediction skill of tropical cyclone (TC) activity over the North Indian Ocean (NIO) has been investigated. Statistical forecast models are developed through generalised linear model (GLM) and generalised additive model (GAM) for tropical cyclone trajectories over the NIO using atmospheric climate variables as predictors. TC from the Joint Typhoon Warning Centre and sets of climate predictor data were analysed for a period of 35-year (1979–2013). The velocity field is predicted by fitting GAM in each month and season. Hindcast validation method is applied to assess the reliability of the model. The skill of the GAM model is compared with GLM and found to be more successful in forecasting TC movement over the NIO region. © 2020 Elsevier B.V.
关键词HurricanesMotion estimationStormsTropicsVelocityWeather forecastingAtmospheric climateFORECAST modelGeneralised additive modelsGeneralised linear modelsMovement predictionNorth indian oceansPredictor dataTropical cycloneClimate modelsclimate predictionensemble forecastinghindcastingseasonal variationstatistical analysistropical cycloneIndian OceanIndian Ocean (North)
语种英语
来源机构Atmospheric Research
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/132370
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Wahiduzzaman M.,Yeasmin A.,Luo J.-J.. Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models[J]. Atmospheric Research,2020,245.
APA Wahiduzzaman M.,Yeasmin A.,&Luo J.-J..(2020).Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models.,245.
MLA Wahiduzzaman M.,et al."Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models".245(2020).
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