The course provides an introduction to weather and climate models. It discusses how these models are built addressing both the dynamical core and the physical parameterizations, and it provides an overview of how these models are used in numerical weather prediction and climate research. As a tutorial, students conduct a term project and build a simple atmospheric model using the language PYTHON.
Learning objective
At the end of this course, students understand how weather and climate models are formulated from the governing physical principles, and how they are used for climate and weather prediction purposes.
Content
The course provides an introduction into the following themes: numerical methods (finite differences and spectral methods); adiabatic formulation of atmospheric models (vertical coordinates, hydrostatic approximation); parameterization of physical processes (e.g. clouds, convection, boundary layer, radiation); atmospheric data assimilation and weather prediction; predictability (chaos-theory, ensemble methods); climate models (coupled atmospheric, oceanic and biogeochemical models); climate prediction. Hands-on experience with simple models will be acquired in the tutorials.
Lecture notes
Slides and lecture notes will be made available at Link
Literature
List of literature will be provided.
Prerequisites / Notice
Prerequisites: to follow this course, you need some basic background in atmospheric science, numerical methods (e.g., "Numerische Methoden in der Umweltphysik", 701-0461-00L) as well as experience in programming. Previous experience with PYTHON is useful but not required.
Performance assessment
Performance assessment information (valid until the course unit is held again)
The performance assessment is only offered in the session after the course unit. Repetition only possible after re-enrolling.
Mode of examination
written 120 minutes
Additional information on mode of examination
Students hand in a tutorial report (compulsory performance assessment) shortly after the end of the term. Exact date will be announced (oral and written) in the first lecture. The report will be graded with marks. The grade contributes to 15% to the examination grade. It is possible to pass the course, even if the grade for the report is below 4.
Written aids
10 pages of hand-written notes
This information can be updated until the beginning of the semester; information on the examination timetable is binding.
Performance assessment as a semester course