Universität Wien

280320 VU Numerical weather forecast (2025S)

5.00 ECTS (3.00 SWS), SPL 28 - Erdwissenschaften, Meteorologie - Geophysik und
Continuous assessment of course work
Moodle
Th 08.05. 09:15-10:15 Ort in u:find Details

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

First lecture and exercises on 13 March 2025.
NOTE: course will be taught in ENGLISH this semester.
Place: Weather discussion room (2G542)

  • Thursday 13.03. 09:15 - 10:15 Ort in u:find Details
  • Thursday 13.03. 10:30 - 12:30 Ort in u:find Details
  • Thursday 20.03. 09:15 - 10:15 Ort in u:find Details
  • Thursday 20.03. 10:30 - 12:30 Ort in u:find Details
  • Thursday 27.03. 09:15 - 10:15 Ort in u:find Details
  • Thursday 27.03. 10:30 - 12:30 Ort in u:find Details
  • Thursday 03.04. 09:15 - 10:15 Ort in u:find Details
  • Thursday 03.04. 10:30 - 12:30 Ort in u:find Details
  • Thursday 10.04. 09:15 - 10:15 Ort in u:find Details
  • Thursday 10.04. 10:30 - 12:30 Ort in u:find Details
  • Thursday 08.05. 10:30 - 12:30 Ort in u:find Details
  • Thursday 15.05. 09:15 - 10:15 Ort in u:find Details
  • Thursday 15.05. 10:30 - 12:30 Ort in u:find Details
  • Thursday 22.05. 09:15 - 10:15 Ort in u:find Details
  • Thursday 22.05. 10:30 - 12:30 Ort in u:find Details
  • Thursday 05.06. 09:15 - 10:15 Ort in u:find Details
  • Thursday 05.06. 10:30 - 12:30 Ort in u:find Details
  • Thursday 12.06. 09:15 - 10:15 Ort in u:find Details
  • Thursday 12.06. 10:30 - 12:30 Ort in u:find Details
  • Thursday 26.06. 09:15 - 10:15 Ort in u:find Details
  • Thursday 26.06. 10:30 - 12:30 Ort in u:find Details

Information

Aims, contents and method of the course


The course introduces the basic aspects of numerical weather prediction (NWP).

Topics covered in the lectures:
* Operational NWP systems and their history;
* Global observing system;
* Data assimilation to construct model initial conditions;
* Parameterization of sub-grid processes;
* Ensemble prediction.

In the exercises, students will work with observational data, apply data assimilation concepts, and evaluate forecast model output.
Students will learn how to process and handle NWP data using python and shell programming.

Assessment and permitted materials

Lecture part: Oral exam. No auxiliary devices allowed.

Exercises:
Solution and presentation of weekly exercises.
A laptop is required for solving the exercises (or access to the Teaching Hub via the Internet).
Please get in touch with Robin Pilch Kedzierski in case computing support is required.

Minimum requirements and assessment criteria

The final grade is a weighted average of the exam on the lecture part (65 %) and the points for the exercise part (35%).
Points for the exercise part will be based on solutions and the presentation of results during the exercises.
Attendance of a minimum of 80% required in the exercise part.

Grade 5: < 50%
Grade 4: 50-62,5%;
Grade 3: 62,5-75%;
Grade 2: 75-87,5%;
Grade 1: > 87,5%

Examination topics

Exam on lecture part: Entire content of the lecture (slides in Moodle)

Reading list

Kalnay, E.: Atmospheric modelling, data assimilation and predictability. Cambridge University Press, 2003, 341 S.
(full list see Moodle)

Association in the course directory

PM-AtmMod

Last modified: Tu 25.02.2025 16:46