MODELLING EXTREME TEMPERATURE BEHAVIOUR IN UPPER EAST REGION, GHANA

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 log quadratic 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. Diagnostic checks of the two models using probability-probability (PP) plot, quantile-quantile (QQ) plot, return level plot and mean residual life plot revealed that the GEV fitted the data well. Return periods of 2, 20 and 100 years also revealed return levels of 0.000015, 0.106150 and 0.142920 respectively. It was therefore concluded that maximum temperature returns showed an increasing trend for long return periods. Based on the outcome of the study, it is recommended that farmers are educated to undertake measures that will help conserve the environment while they engage in farming activities. Also ministries responsible for land and natural resources must design educative programmes on radio and other networks to sensitize the population on climate change treats and how they can combat while they cultivate the land.