Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models

doi:10.1016/j.atmosres.2020.105089

GSTDTAP > 地球科学

DOI	10.1016/j.atmosres.2020.105089
	Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models
	Md Wahiduzzaman, Alea Yeasmin, Jing-Jia Luo
	2020-06-09
发表期刊	Atmospheric Research
出版年	2020
英文摘要	In this study, the contributions of atmospheric climate variables to the prediction skill of tropical cyclone (TC) activity over the North Indian Ocean (NIO) have 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 have been used for a period of 35-year (1979–2013). The velocity field has been predicted by fitting GAM where each of the velocity field has been fitted for each month and season. Hindcast validation method has been applied to assess the reliability of the model. The GAM model skill has been compared with GLM and is found to be more successful in forecasting TC movement over the NIO region.
领域	地球科学
URL	查看原文
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/274313
专题	地球科学
推荐引用方式 GB/T 7714	Md Wahiduzzaman, Alea Yeasmin, Jing-Jia Luo. Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models[J]. Atmospheric Research,2020.
APA	Md Wahiduzzaman, Alea Yeasmin, Jing-Jia Luo.(2020).Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models.Atmospheric Research.
MLA	Md Wahiduzzaman, Alea Yeasmin, Jing-Jia Luo."Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models".Atmospheric Research (2020).