Structures and applications of marine hydrodynamic models

Duration

15h Th, 15h Pr

Number of credits

Lecturer

Alexander Barth

Language(s) of instruction

English language

Organisation and examination

Teaching in the first semester, review in January

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The course begins with an overview of the different approximations of the hydrodynamical equations which are at the heart of numerical ocean models. The range of applications and their limitations is discussed. The interactions between the ocean and atmosphere, rivers, sea bed and topography are presented and formalized by deriving appropriate boundary conditions. The choice of the vertical coordinate in an ocean model is an important aspect and the different options are discussed. The complex coastline and bottom topography of the ocean often require a careful design of the horizontal grid of the ocean model. Different time stepping approaches in ocean models are introduced to account for the broad range of resolved processes with different time scales. An overview of different discretization schemes is also given.

Learning outcomes of the learning unit

The aim of this course is to give an overview of different ocean models and to understand to which problems the ocean models can be applied. The course should also give the necessary basis to correctly implement an ocean model.

Prerequisite knowledge and skills

Physical oceanography
Programming skills in Julia, Matlab/Octave, Python or similar programming languages
 

Planned learning activities and teaching methods

The practical work is integrated into the oral theory class.

Mode of delivery (face to face, distance learning, hybrid learning)

Blended learning


Additional information:

Ten 3-hour courses

Recommended or required readings

Course notes are available at

https://github.com/gher-uliege/OCEA0036

 

Written work / report


Additional information:

Written work on a proposed subject.

If a Large Language Model (LLM, like ChatGPT, LLaMa, GitHub Copilot...) is used to generate or rewrite some part of the report or some computer code, these parts should be clearly marked in the report. You should consult with the lecturer beforehand if the use of LLMs is appropriate.

This provision does not apply to the use of translation tools and spell checkers. 

In any case, it is the student's responsibility to ensure that the content of the report is accurate and is not plagiarism (including unintended plagiarism).

  

 

Work placement(s)

Organisational remarks and main changes to the course

Contacts

Alexander Barth (a.barth@ulg.ac.be)

Association of one or more MOOCs

There is no MOOC associated with this course.

Items online