A depth-duration-frequency model for analysis of extreme precipitation events, with application to past and projected future climates in Ireland

A simple depth-duration-frequency (DDF) model is proposed to reveal the asymptotic characteristics of extreme but short-lived precipitation events that satisfy a peak over threshold (POT) size criterion. Our objective is to reliably estimate the return periods for events of a given intensity (as measured by rainfall depth and duration). For each depth threshold and duration period, the number of qualifying POT events is simply counted over multi-year periods, whether from observations or model output. The distribution of events as a function of their size above the threshold is modelled by a generalized Pareto distribution (GPD), following standard extreme value theory. Those exceedance distributions are shown, to a good approximation, to be independent of location. This justifies the aggregation of exceedances from multiple locations, which is a key feature of the model. Aggregation acts as a data multiplier, enabling more reliable estimation of GPD fits and return periods. The model is applied to intense precipitation observations spanning 30–64 years at 23 stations in Ireland. Three-hourly output from an ensemble of global climate simulations, downscaled to high-resolution over Ireland, were also used to compute both historical and projected future intense event return periods under two different emission scenarios. Future numbers of events per time-period are projected to increase by 20-80%, depending on event threshold and duration, location, emission scenario and time-period. Return periods are projected to shorten by factors of 2 or more for the most intense events, as illustrated by return period maps for events of any given size. • Peak-over-threshold event counts are most natural for modeling extreme rainfall • Exceedances are well modeled by generalized Pareto distributions • Our simple depth duration frequency model is intuitive, general, and robust • Return-periods for extreme rainfall events will shorten significantly • Return periods of past and future extreme rainfall events can be mapped