An 11 year high-quality radar rainfall data set is used to abstract annual maximum rainfall depths for durations of 15 min to 24 h and area sizes of 6 to 1.7 × 103 km2 for the Netherlands. Generalized extreme value (GEV) distributions are fitted to the annual maxima. A new method is presented to describe the distribution of extreme areal rainfall depths by modeling GEV parameters as a function of both duration and area size. This leads to a semiempirical expression from which quantiles of extreme rainfall depths can be obtained for a chosen duration, area size, and return period. The uncertainties in these quantiles are calculated using the bootstrap method. Radar-based areal reduction factors (ARFs) are derived. These ARFs are comparable to those based on high-density rain gauge networks derived from the literature. It is concluded that radar data, after careful quality control, are suitable to estimate extreme areal rainfall depths.@en

This research is intended to improve on existing rainfall estimation algorithms derived from operational radar data as well as to facilitate the study of spatial and temporal variability of rainfall. Using the C-band radar data of the KNMI at De Bilt (the Netherlands) several operational products with a grid of 256 by 256 pixels are produced with a resolution of 2.5km × 2.5km from which precipitation characteristics can be derived. Commonly a single Z-R relation is applied on CAPPI fields to create an estimate of rainfall. The proposed algorithm tries to make a distinction between convective and stratiform precipitation types and therefore will offer a chance to improve upon the estimation of precipitation. First an algorithm based on reflectivity intensity is to provide a first guess of convective and stratiform areas. Secondly separate reflectivity areas (RAs) are identified and tracked in consecutive images to follow their development. Within the first step CAPPI, lightning, echo-top height and Vertically Integrated Liquid (VIL) data can be used to identify more accurately different precipitating areas. Future plans also involve incorporating volume scans directly into the algorithm.@en