Evidence for Non‐Stationarity in the GEV Shape Parameter When Modeling Extreme Rainfall

Abstract It is now well established that climate change is increasing the intensity of extreme rainfall. What is less well established is how best to model these changes. Most literature considers non‐stationarity in extreme rainfall using a Generalized Extreme Value (GEV) model with either the location, or scale, or both parameters varying with either time or some climatic covariate, and it is assumed that the shape parameter will not vary. Here we present evidence that the rainfall quantile increases for rare events are greater than those for frequent events, and these relative changes increase with shorter rainfall durations. Further, we demonstrate that this behavior can only be correctly captured if the shape parameter is non‐stationary. We do this by considering annual rainfall maxima at 48 stations in Australia with durations varying from 6 min to 7 days, for events up to the 1 in 100 Annual Exceedance Probability. The results show that a GEV model with non‐stationarity in all parameters is able to capture the variation in changes across both duration and frequency, whereas a model with a constant shape parameter is not. Finally, we apply this approach to calculate non‐stationary intensity‐duration‐frequency curves and their associated uncertainty. We conclude that while a non‐stationary GEV shape parameter is required to capture the greater relative increase in the rainfall depths for rare events compared to frequent events, this increase in model flexibility comes at the expense of considerably larger uncertainty.