Analysis of extreme rainfall at East London, South Africa

Summary: The aim of the extreme value analysis is to quantify and analyze the stochastic behaviour of extreme values. The estimation of the best appropriate distribution for extreme rainfall is done using the extreme value theory by applying the generalized extreme value (GEV) distribution with a block-maxima. The GEV distribution was also modified to take into account the temporal non-stationary trend in the annual maxima. Since the extreme rainfall observations are naturally scarce it is expected that the use of a Bayesian inference may improve the efficiency of the parameters estimates of the distribution compared to the maximum likelihood method. Therefore, the Bayesian approach was also applied in the paper using the Markov Chain Monte Carlo for the GEV distribution. However the expected improvement in efficiency is not fully achieved in this study using the non-informative and informative priors. The block-maxima method for extreme value analysis is often wasteful of data, specially when more data on the extremes are available, leading to large uncertainties on return level estimates. Therefore, rather than using annual maxima it may be better to consider the daily rainfall data because these data lead to less wastage of information.