Statistical modelling of maximum temperature in Rwanda using extreme value analysis

Author(s): Edouard Singirankabo1, Emmanuel Iyamuremye1, Alexis Habineza2, Yunvirusaba Nelson2
1Department of Mathematics, College of Education, University of Rwanda, Rwanda.
2Department of Mathematics, Jomo Kenyatta University of Agriculture and Technology, Kenya.
Copyright © Edouard Singirankabo, Emmanuel Iyamuremye, Alexis Habineza, Yunvirusaba Nelson. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This study aims to model the statistical behaviour of extreme maximum temperature values in Rwanda. To achieve such an objective, the daily temperature data from January 2000 to December 2017 recorded at nine weather stations collected from the Rwanda Meteorological Agency were used. The two methods, namely the block maxima (BM) method and the Peaks Over Threshold (POT), were applied to model and analyse extreme temperatures in Rwanda. Model parameters were estimated, while the extreme temperature return periods and confidence intervals were predicted. The model fit suggests that Gumbel and Beta distributions are the most appropriate for the annual maximum daily temperature. Furthermore, the results show that the temperature will continue to increase as estimated return levels show it.

Keywords: Climate Change; Global Warming; Extreme value Theory; Rwanda; Temperature; Generalised Extreme Value Distribution; Generalised Pareto Distribution.