Application of Markov chain to wind speed in Northern Peninsular Malaysia
Journal of Applied and Physical Sciences · 2017
This study applied the Markov chain model on the daily average wind speed data recorded at the meteorological stations in northern Peninsular Malaysia.This study aims to investigate the trend of wind speed by obtaining the transition probability matrix and the stationary distribution vector for each of the stations.The ive states of wind speed based on the Beaufort scale ranging from the scale Beaufort 0 up to Beaufort 4 were deined.The stationary distribution vectors obtained revealed that Kota Bharu, Kuala Terengganu and Bayan Lepas demonstrated the highest proportion of daily average wind speed occurring in the scale of Beaufort 2 with the proportion of 69.27%, 63.62% and 61.89% respectively.Meanwhile, Alor Setar and Chuping showed the highest proportion of daily average wind speed occurring in the scale of Beaufort 1 with the proportion of 54.52% and 72.29% respectively.Furthermore, Kota Bharu and Kuala Terengganu also showed 9.30% and 7.13% proportion of daily average wind speed occurring more than 3.3 meter per second (Beaufort 3 and above) while Bayan Lepas station only demonstrates approximately 3.31% of the category.The least proportion displayed for this category is Alor Setar with 0.6% and followed by Chuping with 1.98%.