Universität Wien
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280320 VU Numerical weather forecast (2023S)

5.00 ECTS (3.00 SWS), SPL 28 - Erdwissenschaften, Meteorologie - Geophysik und
Continuous assessment of course work
Moodle

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. 15 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

Room: 5.OG, UZA II, 2F513 (Exner Room)

*MODIFIED TIME SLOTS*
Exercise: Thursday, March 2nd, 2023, 8:30 a.m. - 9:30 a.m.
Lecture: Thursday, March 2nd, 2023, 9:30 a.m. - 11:00 a.m.

  • Thursday 02.03. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 02.03. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 09.03. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 09.03. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 16.03. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 16.03. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 23.03. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 23.03. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 30.03. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 30.03. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 20.04. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 20.04. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 27.04. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 27.04. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 04.05. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 04.05. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 11.05. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 11.05. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 25.05. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 25.05. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 01.06. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 01.06. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 15.06. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 15.06. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 22.06. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 22.06. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 29.06. 08:30 - 09:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II
  • Thursday 29.06. 09:30 - 11:30 Praktikumsraum Meteorologie 2F513 5.OG UZA II

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.
The exercises will cover the following three topics:
* Observations: Data and preprocessing
* Data assimilation: Constructing model initial conditions
* Forecast model: Physics and dynamics

Assessment and permitted materials

Lectures:
Oral exam.
Exam date: 29.06.2023 or 06.07.2023

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 us if computing support is required.

Minimum requirements and assessment criteria

Exam on Lectures: 65 %
Participation in Exercises: 35%

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

Exercises:
Attendance of a minimum of 80% of exercises is required.
Grades will be based on solutions and the presentation of results during the exercises.

Examination topics

The content of lectures and exercises.

Reading list

Kalnay, E.: Atmospheric modelling, data assimilation and predictability. Cambridge University Press, 2003, 341 S.

Association in the course directory

PM-AtmMod

Last modified: Tu 03.12.2024 00:16