Precipitation events can have very different characteristics, from long-lasting light drizzle to short but intense precipitation. For every precipitation event duration, extremes can be defined using extreme value statistics, resulting in intensity-duration-frequency (IDF) relationships. We use a single consistent model based on a duration-dependent Generalized Extreme Value Distribution (d-GEV) to estimate the IDF relationships for all durations simultaneously (Koutsoyiannis, 1998). Building onto our results from climXtreme phase I, we extend the IDF model to a more flexible version that can handle annual block maxima while taking effects from seasonal differences in extreme precipitation into account. The distribution parameters are functions of large scale variables like NAO, temperature and a blocking index. This way, the change of probabilities for an extreme event with a specified intensity can be investigated with respect to the large-scale situation (see figure below). Additionally, since average large-scale variables can be easily extracted from climate projections, this enables an extrapolation of extreme precipitation estimation into the future. Further project targets include a spatial model component with longitude, latitude and altitude as covariates and an approach to combine gridded data sets with station-based data for the estimation of statistical model parameters. The new model shall be made available to the public in an R-library and with an internal freva plugin for possible collaboration within climXtreme.

Website: IDF-AF
Institution: Institute of Meteorology, Freie Universität Berlin
Contact:  Felix Fauer, Prof. Dr. Henning W. Rust