Modelling wind direction data of Langkawi Island during Southwest monsoon in 2019 to 2020 using bivariate linear functional relationship model with von Mises distribution

Author:

Mokhtar Nurkhairany Amyra,Zubairi Yong Zulina,Hussin Abdul Ghapor,Badyalina Basri,Ghazali Ahmad Faiz,Ya’acob Fatin Farazh,Shamala Palaniappan,Kerk Lee Chang

Abstract

Abstract The weather in Malaysia is characterised by two monsoons, namely, the southwest monsoon from May to September, and the northeast monsoon from November to March. Wind direction is essential in observing the weather patterns and global climate. In this study, our interest is on investigating the relationship of the wind direction data of Langkawi Island in Malaysia during the southwest monsoon from year 2019 to 2020. It is essential to highlight that wind direction data that is circular and this requires different statistical techniques from the techniques that are used to analyse linear data. In this paper, we model the relationship of wind direction data by using the bivariate functional relationship model with von Mises distribution. The magnificence of this model is that the existence of error terms in all variables is considered. When modelling the data, outliers of the wind direction data are identified by using the covratio method that considers row deletion. The covariance matrix of the parameter estimates of the data is obtained by using the Fisher information matrix. Also, the result is supported by the Q-Q plots of the von Mises that indicate the goodness-of-fit of the wind direction data to the von Mises distribution. Then, maximum likelihood estimation is used in obtaining the parameter estimates of the data and hence, the model of the wind direction data is attained. The implications of this study provides an improved comprehension of the behaviour of wind direction and may be used for the prediction of wind energy in future.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Understanding the pattern of wind direction in Peninsular Malaysia;The 5TH ISM INTERNATIONAL STATISTICAL CONFERENCE 2021 (ISM-V): Statistics in the Spotlight: Navigating the New Norm;2023

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