Accurate and homogeneous high resolution precipitation datasets are needed for many advanced weather and climate applications. A new automatic system for generating such a climatological product has been developed for Belgium. It is based on radar volumetric data from Belgium, France and Germany. This means that the data are quite heterogeneous with different scanning strategy, sampling resolution, signal filtering and post processing. The precipitation estimation is obtained after a complex processing of the volumetric data. This begins with a careful quality control of the radar data. Each radar is dynamically recalibrated based on the average of the daily median bias over 2 months. The reflectivity level with systematic contamination by non-meteorological signals is identified for each measurement bin. The remaining clutter is identified by comparing with satellite images and looking at the reflectivity field texture or vertical gradient of reflectivity. Ground rainfall estimation is obtained by a dynamic model of vertical profile of reflectivity including the identification of melting snow. Single radar rain rates are combined into a composite by taking the maximum value of the three closest radars in the convective season (May–August). In the other months, the composite is based on all values weighted based on the distance to the radar. In a last step the radar estimation is combined with measurements from dense automatic rain gauge networks. The radar-gauge merging is obtained by a single bias correction or by kriging with external drift. The method is based on the operational realtime product, which benefits from many years of quality control and continuous improvement. An independent verification is performed for the years 2013-2021 with the computation of various scores for different applications. The product is also analysed for the July 2021 extreme flood event.
How to cite: Goudenhoofdt, E. and Delobbe, L.: Generation of a high resolution climatological precipitation product for Belgium, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-580, https://doi.org/10.5194/ems2022-580, 2022.