Selection of the best fit probability distributions for daily maximum temperature data in six Australian capital cities

Climate change is the most challenging issue in our time. The study of weather extremes like heatwaves, droughts and flooding is important as they pose a significant threat to life, property and economy. Many deadly natural hazards such as bushfire over the last century in Australia have been caused by the heatwaves, which is directly related to the increase in temperature. This study examines the daily maximum temperature data at Australian capital cities. Statistical and graphical goodness-of-fit (GOF) tests are adopted to identify the best-fit distribution probability distributions for the selection weather stations. The statistical GOF test reveals that Beta, Gamma (3P), Kumaraswamy and Pearson 5 (3P) distributions generally provide best-fit to the daily maximum temperature data of the selected stations. Results obtained from the graphical GOF test are compared with those from statistical GOF tests. The findings of this study would be useful for engineers, scientists and planners to investigate the characteristics of the extreme temperature in Australian capital cities. This will assist in achieving sustainable developments in relation to urban heat island effects and other high temperature related problems.