Abstract

Extreme temperature has been carried out around the world to provide awareness and proper opportunity for the societies to prepare necessary arrangements. In this present paper, the first order Markov chain model was applied to estimate the probability of extreme temperature based on the heat wave scales provided by the Malaysian Meteorological Department. In this study, the 24-year period (1994-2017) daily maximum temperature data for 17 meteorological stations in Malaysia was assigned to the four heat wave scales which are monitoring, alert level, heat wave and emergency. The analysis result indicated that most of the stations had three categories of heat wave scales. Only Chuping station had four categories while Bayan Lepas, Kuala Terengganu, Kota Bharu and Kota Kinabalu stations had two categories. The limiting probabilities obtained at each station showed a similar trend which the highest proportion of daily maximum temperature occurred in the scale of monitoring and followed by the alert level. This trend is apparent when the daily maximum temperature data revealed that Malaysia is experiencing two consecutive days of temperature below 35℃.

Highlights

  • One of the most important climate parameters which affect natural and social phenomena is the temperature

  • The same scale was applied by Hassan and Hasan [9] in the year 2017 to determine the steady-state probability for the daily maximum temperature across Peninsular Malaysia

  • These data are provided by Malaysian Meteorological Department (MMD) with less than 2% missing data

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Summary

Introduction

One of the most important climate parameters which affect natural and social phenomena is the temperature. The temperature that has exceeded the average temperature for a given area is considered as a heat wave. On February 2019, the Malaysian Meteorological Department (MMD) issued a level 1 alert for ten areas in the country amidst the ongoing nationwide heat wave. The ten areas are located in the western region of Peninsular Malaysia including Perlis, Kedah, Perak, Kuala Lumpur and Johor [1]. The level 1 alert was issued as the daily maximum temperature exceeding 35 ̊C for three consecutive days

Background of Study
Data Characteristics
Heat Wave Scales
A Markov Chain Model for Daily Maximum Temperature
Development of Transition Probability Matrix
Development of Limiting State Probabilities
Descriptive Statistics
Count and Transition Probability Matrices
Limiting State Probabilities
Findings
Conclusions
Full Text
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