Hail suppression effectiveness for different populations of cloud condensation nuclei

A cloud-resolving model with a two-moment bulk microphysical scheme was used to investigate the indirect impact of three cloud condensation nuclei (CCN) parameters – the mean radius (rm), the standard deviation of the CCN spectrum (lnσ), and their solubility in water (εm)—on surface hail accumulation under various aerosol conditions. A sensitivity study was conducted using numerical simulations. Different combinations of these three CCN parameters were tested in continental and maritime environments for both unseeded (control) and seeded cases. The spatial distributions of surface rain and hail were analysed. Continental conditions characterised by extremely low CCN solubility in water were not suitable for hail suppression. Hail suppression was favourable (–26.2% and –8.7%) over continents with typical CCN concentrations (100–1000 cm–3). A highly polluted continental environment showed the greatest reduction in surface hail due to cloud seeding (–84.7%). Over maritime areas, a surplus of rain was observed in all seeded simulations. The effectiveness of hail prevention was discouraging (136.3%) under certain maritime conditions (εm = 1; lnσ = 1; rm = 0.1 μm). An extreme maritime condition resulted in very little hail suppression (–0.3%). It can be concluded that different CCN characteristics strongly affect surface amounts of rain and hail, as well as operational decisions on whether to conduct cloud seeding to prevent damaging hail on the ground.Acknowledgement: This research was supported by the Science Fund of the Republic of Serbia, No. 7389, Project: "Extreme weather events in Serbia - analysis, modelling and impacts” - EXTREMES and by the Ministry of Science, Technological Development and Innovations of Serbia under Grant No. 451-03-136/2025-03/200162.