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Study programme: Geophysics
Study cycle: Master (second)
Module: Meteorology
Core of the programme: Mandatory for meteorology module
Year: 1
Semester: 2

Lectures: 60 hours
Exercises: 15 hours
Seminar: 15 hours

No. of ECTS credits: 7

Language: Slovenian
Specifics: Additional 15 hours for homework assignments and projects

# Weather Analysis and Forecasting

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

The purpose of the course is to learn the principles and methods for numerical weather prediction. The topics covered include atmospheric observations, methods of data assimilation (primarily statistical interpolation and variational method), initial and lateral boundary formulation for limited-area models, model parametrizations, predictability, ensemble forecasting and interpretation of model results.

## Contents (Syllabus outline)

• Global observing systme and observation errors.
• Atmospheric data assimilation: probability calculus, function fitting, statistical interpolation, variational assimilation (3D-Var, 4D-Var).
• Atmospheric predictability: fundaments of theory of chaotic systems, the Lorenz model.
• Forecast error growth and predictability limits.
• Ensemble forecasting: formulation of initial conditions, interpretation and application of ensemble products.
• Monthly, seasonal and long-range forecasts and climate prediction.
• Formulation of numerical forecast models: globale and regional models, initial and lateral boundary conditions, nesting.
• Limited-area modelling: formulation, lateral bounday problem, one- and two-way nesting.
• Model initialization, geostrophic adjustment, relative importance of various observations.
• Subgrid-scale processes: definition of parametrization, Reynolds averaging, planetary boundary layer and turbulent fluxes.
• Parametrization of non-convective condensation and precipitation processes and numerical models. Basics of convection parametrization.

## Basic literature

• E. Kalnay: Atmospheric modelling, data assimilation and predictability. Cambridge university press 2003.
• Selected Lecture Notes from the Training programs of ECMWF, various authors. Available at http://www.ecmwf.int/newsevents/training/
• R. Daley: Atmospheric data analysis. Cambridge university press, 1991.

## Expected achievements

Knowledge and understanding
Atmospheric observations, data assimilation methods, formulation of numerical forecast models, forecast.

Apllicability
Understanding of outputs of weather forecast models, planning of weather observing systems.

Reflection
Connection between theory, model outputs and real weather events.

Transferable skills
Ability to critically judge the data and their use in models, and to judge the model results.

## Teaching methods

Lectures, exercises, seminars; home assignments, students projects.

## Prerequisites

Completed 1 level of Meteorology with Geophysics. Completed exam of Dynamical meteorology I. Oral exam only after successful completion of written exam.

## Assesment methods

The assessment consists of two parts, a theoretical exam and a practical exercises exam. The practical exercises exam (50 % of final grade) can be completed with 2 half-term exams or 1 half-term exam together with a project assignment. A perquisite for theoretical exam is a successfully finished seminar. The theoretical exam together with the seminar is 50 % of final grade. The candidate successfully completes the assessment by obtaining a grade 6 (pass) to 10 (excellent) in both parts.

## Methods of quality assessment

Self-evaluation, anonymous student questionnaire.

## Course coodinator and his references

• Nedjeljka Žagar, assistant professor.