Projects and ongoing research

Convective events, characterized by extreme precipitation, wind, lightning, and hail, consistently account for a significant portion of insured natural hazard damages, particularly affecting the agricultural, vehicle, and building sectors. In recent years, record-breaking hailstone sizes (up to 19 cm in Europe), substantial damage costs (e.g., 2021 in Switzerland), and prolonged, intense convective storms have been observed. The increase in temperatures due to global warming enhances the air's saturation vapor pressure, thereby intensifying convective processes through moisture supply and increased latent heat release. Many of the most intense convective events in Europe occur around the Alps, where large-scale atmospheric flow is significantly influenced by the complex topography of mountain ridges and valleys and interacts with regional to-local processes. Recent climatologies of hail and lightning indicate distinct hotspots of convective activity around the Alps. However, a comprehensive analysis of these hotspots, their spatio-temporal variability, and the underlying processes has not yet been conducted across multiple Alpine countries and convective hazards. The objective of CROSCEA is to systematically classify and characterize convective hotspots in the greater Alpine region. Subsequently, the regional-to-local processes driving increased convection will be analyzed in greater depth using high-resolution observational and model data. CROSCEA is associated with the European-scale TIM field campaign initiative (Thunderstorm Intensification from Mountains to Plains) spearheaded by the European Severe Storms Laboratory ESSL and is committed to contributing its findings to advance the overarching goals of TIM.

Schröer K, Jentsch H
Email: katharina.schroeer@geographie.uni-freiburg.de

Hail is one of the hazards associated with extreme convective events. It is one of the most expensive atmospheric hazards, and recent events have demonstrated this repeatedly with costly damage to vehicles, buildings, and agriculture. Hail is still one of the biggest challenges in forecasting, which is mainly due to the insufficient amount and quality of available data, together with the short spatio-temporal process scales. HAIPI aims to improve this situation integrating novel data sources to develop a product that estimates expected hail stone sizes through state-of-the-art machine learning algorithms. The focus is on crowd-sourced hail reports from the DWD WarnWetter-App as well as new dual-pol radar products, and existing products used in the DWD seamless forecast chain, e.g. KONRAD3D. As a first step, a routine for plausibility testing and quality control for the crowd-sourced data will be developed. The radar products will then be systematically evaluated, and uncertainties quantified. Using comparative machine learning analysis, an approach will be developed to predict expected hail stone sizes based on preprocessed input data. If proven skilful, a hail climatology for Germany will be derived from the resulting data product and the potential for impact assessments be evaluated. The outcomes will significantly advance the systematic observation and thus the prediction and warning of hail.

Schröer K
Email: katharina.schroeer@geographie.uni-freiburg.de

DWD EMF (extramurale Forschung)

Socio-economic impacts of weather phenomena in a changing climate are a concern for government agencies, industry and the public, on time scales from hours (warnings) to decades (adaptation, long-term strategic planning). This project focuses on thunderstorm-related severe weather, in particular hail, one of the main weather-related damage drivers in Central Europe for agricultural crops and infrastructure, and related impacts today and in future. For further information see https://c2sm.ethz.ch/research/scclim.html.

SNF (Swiss National Science Foundation), Funding Scheme: Sinergia Grant