Improved understanding of hail formation and prediction

The Understanding Large Hail Formation and Trajectories (LIFT) project is a research initiative focused on improving the understanding and prediction of hailstorms. Hailstorms are natural hazards that can cause significant damage to buildings, vehicles, agricultural crops, and photovoltaic systems (Kunz et al., 2018). In particular, the region of Baden-Württemberg and bordering areas in Europe are affected by frequent hail events (Kunz and Puskeiler, 2010).
Although there have been significant advances in computational power, microphysical modeling, and understanding of dynamic and thermodynamic processes in recent years, the prediction of hailstorms remains a challenge. One reason for the lack of forecasting of such thunderstorms is that hail growth and trajectories are not accounted for in the models, compromising their accuracy.

Through a unique combination of advanced observational techniques, new scientific knowledge from the last three decades, and citizen science, the LIFT project aims to gain a better understanding of the processes relevant to hail growth in hailstorms. For this purpose, a radar-based model for better prediction of hail growth will be developed.
The primary objectives of the LIFT project include:

1. Data collection and analysis: comprehensive observational data of hail will be collected by both in-situ measurements and remote sensing to improve the accuracy of radar observations.

2. Hail size and distribution: radar data in different wavelength ranges are used to analyze the size and distribution of hailstones.

3. Sensitivity to environmental conditions: idealized simulations help determine the sensitivity of hailstorm signatures as a function of various dynamic and thermodynamic factors.

4. Development of hail growth indicators: indicators relevant to hail formation and growth will be derived from polar metric C-band radar observations.

5. Implementation in forecast models: the developed hail growth indicators will be integrated into forecast models and combined with radar-based hail trajectory and melt simulations to increase forecast accuracy and warning times.

The development of a radar-based model for hail growth has the potential to significantly improve early warning of severe hail events. This has positive implications for several areas, including emergency response and more accurate damage mapping for hailstorms, which in turn benefits insurance companies and affected communities.

The LIFT project is a collaborative effort between the Karlsruhe Institute of Technology (KIT) and the University of Bonn, with support from scientists at the Australian Meteorological Service and Penn State University (USA). The project will be carried out in 2023 as part of the Swabian MOSES 2.0 campaign and will involve collaboration with various partners and the use of state-of-the-art observational techniques to achieve the above goals.

Kunz, Michael, Ulrich Blahak, Jan Handwerker, Manuel Schmidberger, Heinz Jürgen Punge, Susanna Mohr, Elody Fluck, Kris M. Bedka (2018): The Severe Hailstorm in Southwest Germany on 28 July 2013: Characteristics, Impacts and Meteorological Conditions. Quarterly Journal of the Royal Meteorological Society 144(710):231–50. doi:10.1002/qj.3197.

Kunz, Michael, Marc Puskeiler (2010): High-Resolution Assessment of the Hail Hazard over Complex Terrain from Radar and Insurance Data. Meteorologische Zeitschrift 427–39. doi:10.1127/0941-2948/2010/0452.