The research group is on focuses on (i) quantifying of the impact of cloud microphysics uncertainty for weather prediction including its projection on atmospheric dynamics, (ii) separating the impact of predictability limits and model errors in forecast failures, and (iii) combining model predictions with field observations. This involves development of novel analysis methods, in particular Lagrangian approaches and feature-based methods, as well as large high-resolution ensemble simulations mainly with the ICON model.
Current research foci are:
- moisture budget and (hail) precipitation generated by supercells
- orographic precipitation
- systematic model biases in operational ensemble forecasting systems
- moisture transport and potential vorticity anomalies associated with warm-conveyor belts
- online-trajectories in the ICON model and applications thereof
- representation of microphysics uncertainty in numerical weather models