Original paper

Towards a radar- and observation-based hail climatology for Germany

Junghänel, Thomas; Brendel, Christoph; Winterrath, Tanja; Walter, Andreas

Meteorologische Zeitschrift Vol. 25 No. 4 (2016), p. 435 - 445

65 references

published: Sep 6, 2016
published online: Mar 21, 2016
manuscript accepted: Dec 4, 2015
manuscript revision received: Dec 1, 2015
manuscript revision requested: Oct 21, 2015
manuscript received: Sep 2, 2015

DOI: 10.1127/metz/2016/0734

BibTeX file


Open Access (paper can be downloaded for free)

Download paper for free


In the German Strategy for Adaptation to Climate Change hail is identified as one of the major subjects of concern regarding transport infrastructure. Moreover hailstorms are a major threat to e.g. agriculture and the automobile industry causing significant economical damages and losses. Despite these significant hail-related meteorological risks no comprehensive observation-based hail climatology for Germany exists. In this study we present a new approach to this task, combining radar data with different kinds of hail reports, such as ground observation and agricultural insurance data. Preprocessing ensures the applicability of the radar data for the presented climatological analysis. In this sense a number of detection methods are applied to filter artefacts, especially clutter pixels and spokes that disrupt radar measurements. To construct a reliable hail climatology for Germany we process all information into a 10‑year based annual average number of hail days on a 1km × 1km grid using a two-path hail criterion. While the first path combines a threshold of 50 dBZ with a hail report, the second path is based on a 55 dBZ threshold only. By adding radar data we increase the spatial representativity of the ground based hail reports and gain additional information in regions which lack observational data. Overall, the results are mainly determined by events derived from the first path (68 %). A validation of our dataset at 65 stations of Deutscher Wetterdienst shows that the method slightly underestimates the number of hail days, especially for mountainous regions. This results in a better adaption of the hail criterion to lowlands. The resulting hail frequency map shows an increase in the average number of hail days per year from north to south. In particular, hailstorms occur less frequently in the Central North German Plain and the Mecklenburg Coastal Lowland, whereas the highest number of hail days occurs mostly in the uplands of the Black Forest and the Swabian Jura, but also in the Rhenish Massif, the Alpine Foreland and the Lower Rhine Plain. Moreover, the Feldberg region in the Southern Black Forest shows the highest number of hail days per year.


weather radarhailclimatologyinsurance