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1. Course title

Numeerisen meteorologian laboratoriokurssi
Laborationskurs i numerisk meteorologi
Laboratory Course in Numerical Meteorology

2. Course code


Aikaisemmat leikkaavat opintojaksot 53655 Numeerisen meteorologian laboratoriokurssi, 5 op.

3. Course status: optional

-Which degree programme is responsible for the course?
Master's Programme in Atmospheric Sciences

-Which module does the course belong to?
ATM3006 Advanced Studies in Meteorology
optional for

  • Study Track in Meteorology

TCM300 Advanced Studies in Theoretical and Computational Methods

-Is the course available to students from other degree programmes?

4. Course level (first-, second-, third-cycle/EQF levels 6, 7 and 8)

Master’s level, degree programmes in medicine, dentistry and veterinary medicine = secondcycle
degree/EQF level 7
Doctoral level = third-cycle (doctoral) degree/EQF level 8

-Does the course belong to basic, intermediate or advanced studies (cf. Government Decree
on University Degrees)?
Advanced studies

5. Recommended time/stage of studies for completion

-The recommended time for completion may be, e.g., after certain relevant courses have
been completed.

6. Term/teaching period when the course will be offered

The course will be lectured every year in spring term (III-IV periods).

7. Scope of the course in credits

5 cr

8. Teacher coordinating the course

Prof. Heikki Järvinen

9. Course learning outcomes

At end of the course, students should have

  • basic skills in high-performance computing in meteorology
  • practical experience on using large-scale atmospheric models
  • researcher skills in  thermo-dynamic, synoptic, and numeric reasoning about meteorological research questions
  • transferable skills in scientific problem solving as a research group member and publicly presenting scientific results in a focused research question

At practical level, students should be able to modify, build, compile, and run on a parallel high-performance computer the OpenIFS atmospheric model, as well as post-process, diagnose, and visualize the model results.

10. Course completion methods

The course is a "learning-by-doing" -type course where all lectures are short and introductory. Students are in the focus and well-supervised.

There is a pre-exercise prior attending the course, an elimination step of technical skills before entering the group work phase (to ensure all group members have sufficient skills to contribute to the group task), and a final public seminar. The grading is pass/fail.

11. Prerequisites

It is recommended to take this course during the last year of master studies since rather comprehensive knowledge of meteorology (or, oceanography, hydrology, glaciology, terrestrial ecosystems - or any major Earth system component) is needed. The course has a different topic each year and can be taken more than once, e.g. in doctoral studies.

12. Recommended optional studies

Good understanding of meteorology (or, oceanography, hydrology, glaciology, terrestrial ecosystems - or any major Earth system component) helps to complete the group work phase.

13. Course content

1. Super-computer architectures and operating systems, 2. Linux command line and bash-scripting, 3. Compiling and running the OpenIFS, 4. Post-processing, diagnosing and plotting the output, 5. Group work on selected research topics in dynamic meteorology, 6. Reporting the findings orally in a public seminar

14. Recommended and required literature

The OpenIFS model is used as a prediction tool on the course. It is recommended to familiarize with the OpenIFS documentation before/during the course at

15. Activities and teaching methods in support of learning

There is a weekly meeting in the computer class, and Moodle discussion at other times. All physical meetings are supervised hands-on sessions. In the group work phase, groups are expected to make progress in their assigned research questions.

16. Assessment practices and criteria, grading scale

There is a pre-exercise, elimation test (on Linux command line and bash-scripts), and the final seminar. Grading is pass/fail.

17. Teaching language


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