OEKB301208 Atmospheric and climate modelling

Type
Exercise course
Semester hours
3
Lecturer (assistant)
Maier, Philipp , Kuchar, Ales , Arsenovic, Pavle , Nadeem, Imran
Organisation
Meteorology and Climatology
Offered in
Wintersemester 2025/26
Languages of instruction
Englisch
Content

Numerical models are a core tool of exploration, projection and hypothesis testing in atmospheric and climate research. This course offers an overview of different models routinely used in atmospheric and climate research and their application. The models explored in this course range from idealized models to regional climate models (RCMs) and chemistry-transport models (CTMs) and comprehensive coupled global climate models. The course introduces model architecture, parameterizations, and application as well as the use of shell scripts, high-performance computing (HPC) systems and postprocessing routines (e.g. CDO, python, R). In hands-on exercises students will setup models, design and perform model experiments of different complexity and postprocess and analyze model output fields.
Objective (expected results of study and acquired competences)

On successful completion of this course in terms of knowledge, students will be able to:

- Identify and describe the main families of atmospheric and climate models and their respective applications in research and prediction.

- Explain the general structure of atmospheric transport and climate models, including the role of physical parameterizations in model architecture.

- Summarise the principles of high-performance computing (HPC) relevant to running atmospheric and climate models.



On successful completion of this course in terms of skills, students will be able to:
- Write and apply shell scripts to manage workflows and automate model simulations.
- Operate HPC systems to compile, configure, and run simple to medium-complexity atmospheric and climate model experiments.
- Design and perform model experiments to explore atmospheric processes and climate scenarios.
- Analyse and process model output using CDO and NCO, and analytical scripts in open-source programming languages (e.g. Python).



On successful completion of this course in terms of attitudes, students will be able to:
- Evaluate the strengths and limitations of different model families and experimental setups in climate research.
- Interpret model results in relation to atmospheric dynamics, climate variability, and broader Earth system processes.
- Integrate computational modelling, statistical analysis, and visualization into independent and collaborative climate research projects.
- Demonstrate responsible and reproducible use of computational resources in atmospheric and climate modelling.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.