Universität Wien

280353 VU Advanced Data Assimilation (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: English

Lecturers

Classes (iCal) - next class is marked with N

Room:
UZA II: 2G542 (Weather discussion room)

Time/date:
Fridays, 9 -11 a.m. (lecture) and 11-12 a.m. (exercise)

The first lecture will take place on 03.03.2023 and start slightly earlier, at 8:55 a.m.
We will jointly watch half of the live session of ISDA-Online (9-10 a.m., Topic: Operational Data Assimilation, https://isda-online.univie.ac.at/)
Afterward, we introduce the course plan/schedule and discuss the presentation of Florence RABIER (Director-General, ECMWF)

  • Friday 03.03. 09:00 - 11:00 Ort in u:find Details
  • Friday 03.03. 11:15 - 12:15 Ort in u:find Details
  • Friday 10.03. 09:00 - 11:00 Ort in u:find Details
  • Friday 10.03. 11:15 - 12:15 Ort in u:find Details
  • Friday 17.03. 09:00 - 11:00 Ort in u:find Details
  • Friday 17.03. 11:15 - 12:15 Ort in u:find Details
  • Friday 24.03. 09:00 - 11:00 Ort in u:find Details
  • Friday 24.03. 11:15 - 12:15 Ort in u:find Details
  • Friday 31.03. 09:00 - 11:00 Ort in u:find Details
  • Friday 31.03. 11:15 - 12:15 Ort in u:find Details
  • Friday 21.04. 09:00 - 11:00 Ort in u:find Details
  • Friday 21.04. 11:15 - 12:15 Ort in u:find Details
  • Friday 28.04. 09:00 - 11:00 Ort in u:find Details
  • Friday 28.04. 11:15 - 12:15 Ort in u:find Details
  • Friday 05.05. 09:00 - 11:00 Ort in u:find Details
  • Friday 05.05. 11:15 - 12:15 Ort in u:find Details
  • Friday 12.05. 09:00 - 11:00 Ort in u:find Details
  • Friday 12.05. 11:15 - 12:15 Ort in u:find Details
  • Friday 19.05. 09:00 - 11:00 Ort in u:find Details
  • Friday 19.05. 11:15 - 12:15 Ort in u:find Details
  • Friday 26.05. 09:00 - 11:00 Ort in u:find Details
  • Friday 26.05. 11:15 - 12:15 Ort in u:find Details
  • Friday 02.06. 09:00 - 11:00 Ort in u:find Details
  • Friday 02.06. 11:15 - 12:15 Ort in u:find Details
  • Friday 09.06. 09:00 - 11:00 Ort in u:find Details
  • Friday 09.06. 11:15 - 12:15 Ort in u:find Details
  • Friday 16.06. 09:00 - 11:00 Ort in u:find Details
  • Friday 16.06. 11:15 - 12:15 Ort in u:find Details
  • Friday 23.06. 09:00 - 11:00 Ort in u:find Details
  • Friday 23.06. 11:15 - 12:15 Ort in u:find Details
  • Friday 30.06. 09:00 - 11:00 Ort in u:find Details
  • Friday 30.06. 11:15 - 12:15 Ort in u:find Details

Information

Aims, contents and method of the course

This course consists of weekly two-hour lectures plus one-hour exercises on advanced data assimilation.

>>> Content:
* Ensemble data assimilation
* Covariance modeling and localization in different systems
* Satellite data assimilation
* Hybrid Ensemble-Variational (EnVar)
* Observation impact
* Ensemble sensitivity
* Parameter estimation
* Hands-on modeling with WRF-DART
* Exercises will focus on selected topics

>>> Goals:
Students...
* understand fundamental concepts of data assimilation.
* are familiar with important methods (localization, inflation, ...) in ensemble data assimilation.
* can perform data assimilation using a state-of-the-art numerical modeling system.
* can analyze data assimilation output using Python.
* are able to interpret and critically evaluate data assimilation processes.

>>> Methods:
* Lectures on data assimilation
* Discussion of state-of-the-art research (via ISDA-Online)
* Conduct, analyze, and discuss numerical experiments.

Assessment and permitted materials

Lectures: Oral exam (date t.b.a.)
Exercises: Presenting results of hands-on exercises

Minimum requirements and assessment criteria

The weighting of lecture and exercise in final grade:
Lectures: 65%
Exercises: 35%

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

Attendance of a minimum of 80% of exercises is required.

Examination topics

The entire content of lectures and exercises.

Reading list

Eugenia Kalnay - Atmospheric Modeling, Data Assimilation and Predictability
Anderson, J., et al. (2009) - The Data Assimilation Research Testbed: A Community Facility

Association in the course directory

WM-AdvWea

Last modified: Th 11.05.2023 11:28