In mid-latitudes, almost every raindrop that reaches the surface, starts as an ice particle in the cloud aloft. Ice microphysical processes are thus key for realistically forecasting the evolution of clouds and precipitation. Besides in-situ observations and laboratory experiments, remote sensing methods, such as modern cloud radars, provide a wealth of information about processes, such as aggregation, riming, and secondary ice production. This talk will provide a compact overview of the measurement principles and application examples of how we can use cloud radars in combination with modern modelling tools to improve our understanding of ice microphysical processes in clouds.

We use a storyline approach to model the impacts of extreme flood events in Switzerland in a warmer climate. We find a non-linear relationship between the increase in precipitation and the increase in discharge, which is, among other factors, due to the increasing precipitation intensity. We find a strongly non-linear relationship between the increase in discharge and the increase in damages, which is due to the geometry of the riverbeds, the relative position of the exposure to the rivers, and the discharge exceeding the upper limit of the protective infrastructure.

(1) tbd (2) Idealized Urban Simulations in ICON-CLM (3) Interplay of orography, aerosol concentration and secondary ice formation in contrasting island environments (4) tbd

(1) tbd (2) Assessing the representation of tropical-extratropical teleconnections in machine learning (ML) and numerical weather prediction (NWP) models for improving the S2S forecast skill (3) Coupling MieAI with RTTOV: Enhancing Radiative Transfer Simulations with AI-Derived Aerosol Properties (4) tbd

Results from PhD Thesis