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Analytic and numerical modelling of oceanic processes. An opportunity to apply mathematics and physics skills to understand a critical part of our climate system.
Many earth science problems are tackled with numerical models. This paper examines how scientists develop models to study the physical characteristics and dynamics of the ocean to understand their connection to ocean biology, chemistry and climate change. The paper is intended for students interested in the quantitative study of the earth oceans, climate and paleoclimate. Assignments cover the fundamentals of numerical methods to study geophysical fluids and develop student programming skills to access and analyse numerical model output. Applications will include waves in the ocean, Newton’s laws on a rotating planet and wind-driven flow.
| Paper title | Ocean Physics and Modelling |
|---|---|
| Paper code | OCEN321 |
| Subject | Oceanography |
| EFTS | 0.15 |
| Points | 18 points |
| Teaching period | Not offered in 2021, expected to be offered in 2022 |
| Domestic Tuition Fees (NZD) | $1,092.15 |
| International Tuition Fees (NZD) | $5,004.75 |
- Prerequisite
- One of (EMAN 204, OCEN 201, PHSI 231 or PHSI 243) and MATH 170
- Recommended Preparation
- MATH 203, (OCEN 201 or PHSI 243), (PHSI 131 or PHSI 132 or PHSI 191) and OCEN 301
- Schedule C
- Science
- Contact
- More information link
- View more information about OCEN 321
- Teaching staff
Course Coordinator: Dr Ata Suanda
- Teaching Arrangements
- Lectures and labs
- Textbooks
There is no required text for this paper.
Lecture notes and supplementary material will be made available.- Graduate Attributes Emphasised
- Global perspective, Interdisciplinary perspective, Scholarship, Communication, Critical
thinking, Information literacy, Research, Self-motivation, Teamwork.
View more information about Otago's graduate attributes. - Learning Outcomes
- Classify differential equations and models based on their type, order and complexity.
- Understand numerical principles behind solving differential equations.
- Be able to determine the appropriate model to use for a given application.
- Understand numerical model uncertainty, the use of approximations and the need for model parameterisation.
- Use analytical and critical-thinking skills to identify and describe numerical methods found in literature.
- Use practical MATLAB-based computer skills: be comfortable running computer codes, create effective visualisations and interpret model output.
