Abstract
Climate change is considered to be one of the biggest crisis which affects human life and nature. The anthropogenic or human factors such as land conversion, industrialization and transportation release greenhouse gasses amplify warming in air temperature. The objective of this study is to analyze the extreme temperature events at nine selected states in Peninsular Malaysia using Generalized Extreme Value (GEV) distribution. It also aims to predict the return level of the maximum temperature at different selection period. The estimation of parameters is determined using Maximum Likelihood Estimator (MLE) method. In this study, stationary and non-stationary GEV models are considered. Mann-Kendall trend test is applied to detect stationarity in a series of maximum temperature data. The result indicates that non-stationary model is preferred for Kuala Terengganu, Muadzam Shah and Senai stations. By evaluating the return period of T-years for each station, the result of the estimated return levels showed that the temperatures for all stations are increasing over 125 years except for the non-stationary stations.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Mohd Salleh, Nur Hanim nurhanim_sh@yahoo.com Hasan, Husna husnahasan@usm.my |
Subjects: | T Technology > TD Environmental technology. Sanitary engineering > Environmental auditing T Technology > TD Environmental technology. Sanitary engineering > Environmental auditing > Environmental reporting T Technology > TD Environmental technology. Sanitary engineering > Environmental auditing > Environmental reporting > Malaysia |
Divisions: | Universiti Teknologi MARA, Pulau Pinang > Permatang Pauh Campus |
Journal or Publication Title: | ESTEEM Academic Journal |
UiTM Journal Collections: | UiTM Journal > ESTEEM Academic Journal (EAJ) |
ISSN: | 1675-7939 |
Volume: | 13 |
Page Range: | pp. 107-117 |
Keywords: | extreme maximum temperature, generalized extreme value, return level, maximum likelihood estimation, Mann-Kendall. |
Date: | August 2017 |
URI: | https://ir.uitm.edu.my/id/eprint/28791 |
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