Non-stationary temperature extremes in a changing climate: A Bayesian extreme value analysis
Date
2019-08
Authors
Chukwudum, Queensley
Journal Title
Journal ISSN
Volume Title
Publisher
Strathmore University
Abstract
The main focus of this study is to analyze the trends in extreme temperature over the East
African region in order to aid a deeper understanding of the inherent risks associated with such
extremes. Four countries' (Kenya, Ethiopia, Sudan and Somalia) maximum annual temperature
datasets are considered under the stationary and non-stationary assumptions. For the nonstationary
form of the Generalized Extreme Value distribution, only the location parameter is
allowed to vary with time. The Maximum likelihood and Bayesian estimation techniques are
used. Although both estimation techniques produce similar parameter estimates they differ when
it comes to the suggested model (linear or quadratic) to use in modelling the variations through
time for each country's maxima. This difference is further, deeply reflected in the forecasted
non-stationary return levels for future time horizons. The Bayesian results are adopted as it takes
into account prior knowledge.
Description
Paper presented at the 5th Strathmore International Mathematics Conference (SIMC 2019), 12 - 16 August 2019, Strathmore University, Nairobi, Kenya
Keywords
Non-stationary, Extreme temperatures, Bayesian estimation