Modelling Extreme Temperature Behaviour In Upper East Region, Ghana.

ABSTRACT

The impacts of extremely high temperatures on plants, human beings and animals’ health have been studied in several parts of the world. However, extreme events are uncommon and have only attracted attention recently. In this study, extreme temperature behaviour was modelled through the application of extreme value theory using maximum monthly temperatures over a 32 years period. Data on monthly maximum temperature from the Upper East Region were modelled using generalized extreme value (GEV) and generalized Pareto distributions (GPD) models. A trend analysis revealed that the maximum temperature returns followed a logquadratic trend model. The results revealed that the GEV model was better in modelling extreme temperature behaviour because it had the least AIC and BIC values of -1003.6050 and -991.7600 respectively. Two comparative tests, namely, Anderson-Darling and Kolmogorov-Smirnov confirmed the GEV model to be adequate for the data.