<p>Hail is a pronounced natural hazard in Germany. Nevertheless, major hail events are quite rare and there is a lack of information in hail occurrence and size and its spatiotemporal distribution. Measurement sensors that are able to detect hail (e.g. disdrometers) are in principle available in Germany, but the spatial density of those stations is far lower than the typical spatial extent of hail events. Furthermore, sensors for hail size estimation are still in evaluation stage and currently only located at a few selected places. Hail reports based on professional and particularly amateurish eyewitness become increasingly important. But besides a certain degree of subjectivity in the reported hail size, highly populated areas might be overrepresented compared to rural and sparsely populated areas. Areal information from weather radar networks can overcome this issue with a high spatiotemporal resolution. Because of the high update frequency and fast availability of radar data, an automatic hail detection and hail size estimation might provide valuable hints to forecasters and supports the warning decision process.       <br />The Deutscher Wetterdienst (DWD) utilizes a C-Band dual-polarimetric weather radar network consisting of 17 radar stations that provide ten volume scans and a terrain-following low-elevation scan every five minutes. The operationally used hydrometeor classification algorithm HYMEC processes data of reflectivity, differential reflectivity and co-polar correlation coefficient to distinguish between hail and other hydrometeors. With this classification a hail distribution over Germany can already be derived. For the analysis of hail sizes, the Maximum Expected Size of Hail (MESH) and a method based on Vertical Integrated Ice (VII) are used. The latter method is motivated by a linear relation between maximum hail size and VII proposed by our forecasters based on their practical experience.        <br />This contribution will give an overview on the statistics of hail occurrence and hail size using the aforementioned algorithms in Germany during the convective seasons 2021 and 2022. Also, selected case studies are discussed in more detail. The results are compared against hail observations from manned and automatic weather stations, reports from the European Severe Weather Database and user reports from DWD’s WarnWetter-App.</p>

<p>Since major hail events are quite rare in Germany, there is a lack of information in hail occurrence, size and its spatio-temporal distribution. As hailstorms are often locally very limited events, the hail distribution is hard to analyze precisely. Hail reports can only give a first intuition about the amount of hail overall. There might be a bias in the amount of reports towards too many reports in highly populated areas, which could lead to an underrepresentation of reports in rural and sparsely populated areas. Areal information from weather radar networks can overcome this issue with a high spatio-temporal resolution. As an addition, data from the German Insurance Association (GDV) about damages through hail serve as a very certain source for hail occurrence.</p> <p>The German radar network consists of 17 dual-polarimetric radar systems, which cover Germany more or less completely. For the analysis of the hail distribution, the Maximum Expected Size of Hail (MESH) and a method based on Vertical Integrated Ice (VII) are used to estimate the hail size. Those sizes are reduced to thresholds to obtain where hail is reasonable or have a significant large size. The results of MESH and VII are finally compared to the eyewitness reports sent to the European Severe Weather Database and the WarnWetter-App. An important comparison are the loss data by the GDV. It can give further insides into the amount and the size of hail.</p>

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