Mathematics plays a central role in the development and analysis of models for weather prediction and climate research. Controlled physical experiments are out of question, and the only way we can study Earth’s weather and climate is through mathematical models, computational experiments, and data analysis.
Fluctuations in daily weather are tightly connected to turbulence, and turbulence represents a challenge for the predictability of weather. No general solution for the equations of fluid motion is known, and consequently no general solutions to problems in turbulent flows are available. Instead, scientists rely on conceptual models and statistical descriptions to understand the essence of daily weather and how that feeds back on climate behavior.
This course/seminar focuses on techniques of mathematical modeling that assist scientists in exploring the listed issues systematically.
The course will cover a selection from the following topics
1. Conservation laws of geophysical fluid dynamics,
2. Systematic approximation via scale analysis and asymptotics,
3. Numerical methods for geophysical flow simulations,
4. Dynamical systems and bifurcation theory,
5. Data-based characterization of atmospheric flows
Literaturhinweise werden anfangs des Semesters in Abhängigkeit von
der Themenauswahl gegeben.
Interessante Startpunkte, die einen ersten Einstieg in obige drei
Hauptpunkte erlauben, sind
Scale-Dependent Asymptotic Models for Atmospheric Flows,
Ann. Rev. Fluid Mech., vol. 42, 249-274 (2010)
Numerical Methods for Fluid Dynamics with Applications to Geophysics,
Springer, Computational Science and Engineering Series, (2010)
Metzner Ph., Putzig L., Horenko I.,
Analysis of persistent nonstationary time series and applications
Comm. Appl. Math. & Comput. Sci., vol. 7, 175-229 (2012)
Tennekes and Lumley, A first course in Turbulence, MIT Press (1974)
A3/ 024 Seminarraum
wöchentlich, ab 18.10.2022, 14:00 - 16:00 (16 Termine)