A BAYESIAN-ANALYSIS OF EXTREME RAINFALL DATA

Understanding and quantifying the behaviour of a rainfall process at e xtreme levels has important applications for design in civil engineeri ng. As in the extremal analysis of any environmental process, estimate s often are required of the probability of events that are rarer than those already recorded. As data on extremes are scarce. all available sources of information should be used in inference. Consequently, rese arch has focused on the development of techniques that make optimal us e of available data. In this paper a daily rainfall series is analysed within a Bayesian framework. illustrating how the careful elicitation of prior expert information can supplement data and lead to improved estimates of extremal behaviour. For example. using the prior knowledg e of an expert hydrologist. a Bayesian 95% interval estimate of the 10 0-year return level for daily rainfall is found to be approximately ha lf of the width of the corresponding likelihood-based confidence inter val.