Towards understanding the interannual variability of hail in Switzerland

Abstract

Hailstorms are among the most damaging natural hazards in Switzerland, yet the large-scale processes governing their interannual variability remain poorly understood, limiting the potential for early prediction and risk preparedness. Using a 64-year reconstruction of past hail days (1959–2022) and ERA5 reanalysis data, we identify the dominant atmospheric, oceanic, and land-surface patterns associated with particularly active hail seasons north and south of the Swiss Alps. In both regions, active hail seasons are associated with recurrent large-scale circulation anomalies, characterized by a zonally or meridionally oriented Euro-Atlantic wave train, together with seasonally preconditioned background states in sea-surface temperatures, near-surface temperature, and the mid-tropospheric circulation. These conditions promote repeated occurrences of hail-favorable environments with warm and moist boundary layers, enhanced instability, and moderate convective inhibition. The identified patterns differ significantly from those in hail-sparse seasons and exhibit distinct regional differences: north of the Alps, moisture supply is linked primarily to Atlantic influences and continental evaporation, and the strongest seasonal-scale anomalies occur in temperature, indicating a predominantly temperature-limited regime. South of the Alps, hail activity is associated with frequent elevated dry-layer conditions and a stronger contribution from Mediterranean moisture, occurring in a generally more convection-favorable environment with weaker seasonal-scale anomalies. We further find wintertime precursors of active hail seasons, including continental cooling and Pacific SST anomalies resembling a positive Pacific Decadal Oscillation phase, pointing to low-frequency preconditioning through large-scale teleconnection pathways. Together, these results identify consistent circulation regimes and precursor signals that could underpin (sub-)seasonal hail prediction in Switzerland and Central Europe.