Our projects

In the Young Investigator Group “Meteorological Data Science”, we aim at improving our understanding of atmospheric processes and predictability through the deployment of statistical models and machine learning. Our research mostly focuses on weather forecasts provided by numerical weather prediction models and fully AI-based models on the medium-range to sub-seasonal time-scale. The group is to a large extent funded through the ERC Starting Grant “Advancing sub-seasonal predictions at reduced computational effort (ASPIRE) and individual DFG grants. To best possibly combine domain knowledge and data science, we conduct research in collaboration with other institutes facilitated by the KIT Center MathSEE and the KIT Graduate School Computational and Data Science.