**Study programme:** Geophysics

**Study cycle:** Master (second)

**Module:** Meteorology

**Core of the programme:** Mandatory for Meteorology module

**Year:** 1

**Semester:** 2

**Lectures:** 30 hours

**Exercises:** 30 hours

**Seminar:** 0 hours

**No. of ECTS credits:** 7

**Language:** Slovenian

**Specifics:** 14 weekly projects

# Models I

## Objectives of the course and intended learning outcomes (competences)

Acquainting with basic modelling approaches and basic mathematical tools. Each weekly project is a combination of a model type and a tool.## Contents (Syllabus outline)

- Kinematic models (variational approach, linear programming, nonlinear minimization).
- Population models and chemical kinetics (phase space analysis, modelling of data and parameter estimates, normal matrix, singular value decomposition).
- Stochastic models (pseudorandom generators, basic probability distributions, Monte Carlo integration, simulation, Metropolis algorithm).
- Harmonic analysis (FFT, convolution, data filtering, noise removal).

## Basic literature

- I. Kuščer, A. Kodre: Mathematik in Physik und Technik, Springer 1993.
- W.H. Press, B.P.Flannery, S.A.Teukolsky, W.T.Vetterling: Numerical Recipes, Cambridge Univ. Press, 1986.
- J.W. Demmel: Uporabna numerična linearna algebra, DMFA, Ljubljana 2000.
- M.H.Kalos, P.A.Whitlock: Monte Carlo methods.

## Expected achievements

**Knowledge and understanding**

The knowledge of basic modelling aproaches, understanding of individual modelling tools.

**Apllicability
**The skill of data modelling and methods of stochastic analysis.

**Reflection
**Understanding of the phenomenon-model relation, the reflection of complexity.

**Transferable skills
**Presenting of data and results of analysis – advanced graphic tools. Mastering of time- and memory-extensive computational algorithms.

## Teaching methods

Lectures, discussion of projects, consultations.## Prerequisites

First cycle.## Assesment methods

The assessment consists of two parts, successful completion of all weekly assignments and successful completion of the final project assignment. The candidate successfully completes the assessment by obtaining a grade 6 (pass) to 10 (excellent) in both parts.## Methods of quality assessment

Selfevaluation, student questionaires.## Course coodinator and his references

- Prof. Dr. Alojz Kodre.