Estimation of hail frequency in Germany and its trends under climate change

Severe hail events are comparatively rare, yet they contribute a significant portion of the total insured losses each year in Germany and worldwide. Single events with large hailstones in the past have caused major damage, such as the severe Reutlingen hailstorm on July 28, 2013, with hail diameters up to 10 cm, causing costs of more than EUR 1 billion. Additionally, hailstorms with smaller hailstones often cause substantial damage to building facades and roofs, photovoltaic systems, vehicles, and agricultural areas. Given the considerable potential for damage, it is crucial to gain a better understanding of the behavior of hailstorms in the context of a changing climate.

As a data basis for hail, twenty summer half-years (2005 – 2024) of potential hail tracks in different intensity classes over Germany are used. These tracks were derived using a modified version of the TRACE3D tracking algorithm based on 3D radar data from the C-Band radar network of the German Weather Service (DWD). From these hail events, the ambient thermodynamic and dynamic conditions are extracted and compared with ambient conditions of non-events, taken from a similar environment on days without cell activity. This establishes that the most suitable proxy variables for the hail events of different intensity classes can be determined.

Preliminary findings suggest that the use of a combination of a lifted index for atmospheric stability, the moisture content of the layer above the lifted condensation level, and the layer thickness between the equilibrium level and the -10°C isotherm are especially promising. Besides others, these parameters serve as the basis for a logistic regression used for estimating hail occurrence from ERA5 data. We combine the parameters with information about the triggering, such as fronts and anomalies in potential vorticity.

Longer periods than only twenty years are required to determine the extent to which climate change influences hail frequency and intensity. For this purpose, the hail model can also be applied to climate simulations to estimate future changes in hail frequency under various warming scenarios.