Selecting the probability distribution of annual maximum temperature in Malaysia

The issues on global warming have become very popular and been discussed both locally internationally. This phenomenon due to the temperature rises will increase variability of climate more natural disasters were expected occur. Increasing affect agricultural sector, some infectious diseases that may lead high mortality rates in humans, demand for electricity, water food which eventually affecting economy Malaysia. Hence, this work aims study best fitted probability distribution describes annual maximum recorded at seventeen meteorological stations Normal, Lognormal, Gamma, Weibull Generalized Skew Logistic distributions are considered using likelihood estimation method estimate parameters. goodness fit test model selection criteria such as Kolmogorov-Smirnov AndersonDarling tests, Corrected Akaike Information Criterion Bayesian used measure accuracy predicted data theoretical distributions. results show most favour distribution. Also, Lognormal well describe temperature.