The Generalized Extreme Value (GEV) distribution has often been used to describe the distribution of daily maximum precipitation in observed and climate model data. The model developed in this paper allows the GEV location parameter to vary over the region, while the dispersion coefficient (the ratio of the GEV scale and location parameters) and the GEV shape parameter are assumed to be constant over the region. This corresponds with the index-flood assumption in hydrology. It is further assumed that all three GEV parameters vary with time such that the relative change in a quantile of the distribution is constant over the region. This non-stationary model is fitted to the 1-day summer and 5-day winter precipitation maxima in the river Rhine basin in a simulation of the RACMO regional climate model for the period 1950–2099 and the results are compared with gridded observations. Except for an underestimation of the dispersion coefficient of the 5-day winter maxima by about 35% the GEV parameters obtained from the observations are reasonably well reproduced by RACMO. A positive trend in the dispersion coefficient is found in the summer season, which implies that the relative increase of a quantile increases with increasing return period. In the winter season there is a positive trend in the location parameter and a negative trend in the shape parameter. For large quantiles the latter counterbalances the effect of the increase of the location parameter. It is shown that the standard errors of the parameter estimates are significantly reduced in the regional approach compared to those of the estimated parameters from individual grid box values, especially for the summer maxima.
M Hanel, TA Buishand, CAT Ferro. A non-stationary index-flood model for precipitation extremes in transient Regional Climate Model simulations