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MN-GM-PM

Core Module: Prognostic Modelling (PM)
Identification number

MN-GM-PM
Workload

180 h
Credits

6
Term

1st (or 2nd) semester
Offered Every

year
Start

WiSe
Duration

1 semester
1 Course types
a) Lectures
b) Exercise
Contact time
30 h
30 h
Private study
60 h
60 h
2 Module objectives and skills to be acquired

Aims: Understanding of prognostic numerical formulation of meteorological and geophysical problems, overview of numerical procedures and their properties and knowledge of model capabilities, limitations and model results interpretations. Acquired skills: skillful applications of meteorological and geophysical models, critical judgment of model simulations and capacity of model development.
3 Module content
  • Concepts and framework of meteorological and geophysical prognostic modeling
  • Numerical methods for ordinary and partial differential equations
  • Numerical methods used in meteorological, geophysical and space-plasma prognostic models
  • Initial and boundary conditions
  • Examples of meteorological (e.g. COSMO, ICON), geophysical and space-plasma models

Literature:
 Haltiner, J. and R.T. Williams, 1980: Numerical Prediction and Dynamic Meteorology, John Wiley & Sons Inc.
 Coiffier, J., 2009: Fundamentals of Numerical Weather Prediction, Cambridge University Press.
 Krishnamurti, T.N., H.S. Bedi, V.M. Hardiker and L. Ramaswamy, 2006: An Introduction to Global Spectral Modelling, Springer-Verlag
 Ames, W.F., 1977: Numerical methods for partial differential equations, Academic Press.
 Fletcher, C. A. J., 1991: Computational Techniques for Fluid Dynamics, Springer-Verlag.
 Hoffmann, J. D., 2001: Numerical Methods for Engineers and Scientists.
 Shearer, P., 2009: Introduction to Seismology, Cambridge University Press.
 Büchner et al., 2003: Space Plasma Simulation (Lecture Notes in Physics), Springer-Verlag.

4 Teaching methods

Lectures and exercises.
5 Prerequisites (for the module)

Formal: None.
The content of the course requires the undergraduate knowledge of geophysical fluid dynamics, linear algebra and basic skills programming in Python (or Matlab, Fortran, C/C++ or similar).
6 Type of examination

The module is concluded with a project work. Successful completion of the exercises is required for admission to the project work; for this, the acquisition of 50% of the points to be achieved is sufficient. For a given task, the students should independently plan, carry out and document the implementation. The project work has a duration of 8 weeks and is submitted in electronic form. A report (not more than 20 pages), the source code, including documentation must be submitted.
7 Credits awarded

The module is passed, and the credit points will be awarded, if
  1. the project work is passed, and
  2. the exercises are passed; the acquisition of 50% of the points to be achieved is sufficient for this
8 Compatibility with other Curricula

N/A
9 Proportion of final grade

Weight of the module grade in the overall grade: 6/150 (4 %)
10 Module coordinator

Yaping Shao, Roel Neggers
11 Further information

Version: 2023-03-23