For the positions in Atmospheric Physics a solid background in natural sciences (e.g. master in physics or atmospheric sciences/meteorology) or in mathematical modelling (e.g master in applied mathematics or computational sciences) is required.
Updated on 30 April 2021 - 1 position is still open
Predictability of difficult weather events (1 position)
The accuracy of numerical weather forecasting has improved dramatically over the last year, especially on larger scales. However, there are still events (especially on the local/regional scale) for which the forecast accuracy is massively reduced. Usually the spectacular events such as storms are more likely to be noticed (e.g. storm Lothar 1999), but in fact forecast busts for other, local phenomena (such as foehn, high fog, heavy precipitation) occur much more frequently, so that one can also ask the question of a fundamental reduction in predictability. In fact, it is very difficult to find the causes of the problems in the forecasts, missing physical processes or even a limited representation of processes in the models can play a major role. In this part of the project, a synthesis of model predictions and meteorological measurement data will be used to investigate the causes of false predictions in certain weather situations, especially missing or insufficiently modelled physical processes. Thereby, simulations with weather models are to be carried out and, if necessary, the parameterizations in the models are to be improved.
- Identification of (maybe unknown) meteorological situations leading usually to incorrect predictions
- Identification of relevant physical processes responsible for incorrect predictions
- Development of new or improved physical parameterisations for relevant processes to improve forecasts