The success of weather prediction comes in a large part because we can verify the forecasts every day against observations. But the observations contain errors and recent experiments have shown that even small errors can make the verification unreliable. This project is based on programming a simple statistical forecast model, where the impact of different observation errors can be investigated.
For more detailed information please contact George Craig.
Weather models based on artificial intelligence are now able to produce descent forecasts, but they struggle to represent the butterfly effect: The AI-models Pangu and GraphCast show unrealistic slow error growth when challenged with a small initial perturbation. This bachelor thesis aims to explore the representation of the butterfly effect by another AI model (FourCastNet) and to compare its performance with previous findings.
For more detailed information please contact Tobias Selz.
Topics broadly in the area of stratosphere-troposphere and climate dynamics are available upon request. Recent research topics in our group include: variability and long-term trends in the width of the tropical belt, processes that govern the temperature structure of the tropical tropopause layer, the dynamics of sudden stratospheric warmings and their coupling to the troposphere, transport processes in the upper troposphere / lower stratosphere. Interested candidates are asked to look through research topics on our group's website, in particular our recent publications: https://www.meteo.physik.uni-muenchen.de/~Thomas.Birner/pubs.html.
For more detailed information please contact Thomas Birner.
Bei Interesse an Bachelorarbeiten im Lehrstuhl für Theoretische Meteorologie bitte bei Prof. G. Craig oder Dr. C. Keil nachfragen.