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The University of Southampton

SOES2025 Ocean Data Analysis and Modelling

Module Overview

Aims and Objectives

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Knowledge of physical oceanographic instrumentation and its deployment,
  • Knowledge of key thermodynamic and dynamic concepts in oceanographic modelling
  • Capacity to analyse and interpret raw data and present conclusions from them,
  • Capacity to critically assess datasets available via the Internet,
  • Capacity to use the programming language Matlab in simple models and data analysis.
  • Capacity to appropriately apply thermodynamic and dynamic equations to model ocean phenomena, including application of the equations of motion
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • team working,
  • time management,
  • information retrieval from Internet.
Learning Outcomes

Having successfully completed this module you will be able to:

  • Apply dynamic and thermodynamic principles to describe a range of oceanographic phenomena
  • Apply physical understanding and mathematical analysis to real, observational data sets to a. determine fundamental characteristics of the data: mean/median. b. characterize the seasonality, secular trends, and covariability
  • Identify when and how the equations of motion can be simplified based on the oceanographic phenomena under consideration, producing a usable model to evaluate the phenomena
  • Apply simple numerical models of ocean phenomena in MATLAB
  • Describe the main techniques for making physical measurements in the ocean
  • Analyse raw data acquired by in situ instruments measuring physical properties of the sea, and critically assess the errors and limitations for specific applications
  • Distinguish between the different methods used for satellite remote sensing of the ocean and identify the main ocean data products that each generates
  • valuate the quality and reliability of physical ocean data acquired from data sources through the Internet
  • Write a clear account of the analysis and interpretation of physical, geophysical and environmental ocean data
  • Access and download freely available oceanographic datasets in CSV, ASCII, netCDF and HDF format, and load them into Matlab


- Modelling the ocean using Newton’s laws of motion and Thermodynamic principles - The gravitational force and the concept of geopotential height - The pressure gradient force - The frictional force, velocity shear, viscosity. - Circular motion, the rotating Earth, and the Coriolis force - Summary of forces in oceanography (The Navier-Stokes Equations) - Angular momentum and potential vorticity - The conservation of energy and the ocean heat budget. - Importance and fundamentals of ocean data - Acoustic methods for subsurface oceanography - Acoustic Doppler techniques for water column sounding - Temperature and salinity measurements, CTD etc. - Underway sampling and towed platforms, fluorometry, etc. - Principles of satellite remote sensing techniques to measure sea surface temperature, ocean colour, sea surface height and velocity, and surface winds. - Synergies between different types of data, including between in situ and satellite data sources. - Practical introduction to the use of scientific programming to analyse oceanographic data. - Timescales of variability in the ocean. - Case studies in the ocean, including Sverdrup gyres, eddies, sea level and phytoplankton.

Learning and Teaching

Teaching and learning methods

Formal Lectures: 24 x 45 minute lectures will provide an introduction to the underlying theoretical principles of (1) modelling oceanographic phenomena using dynamical and thermodynamical principles and (2) ocean data collection and processing. The lectures will present factual information about the topics and methods in the syllabus and give explanations of how to put this knowledge into practice. Some lectures will contain interactive elements, including peer to peer instruction and problem solving within groups. Where relevant, lecturers' own research experience in the appropriate fields is brought into the lecturing sessions. References to the applicable chapter of course text and/or other relevant journal articles are provided as useful reading for each lecture. Practical sessions: 12 x 2 hour sessions provide hands-on experience of processing and analysing different types of data using appropriate analytical computer tools. These sessions exemplify the theoretical concepts for data analysis covered during formal lectures allowing you to develop particular skills of relevance to both local and global-scale oceanographic analysis. Support: is provided by staff and/or postgraduate demonstrators. A wide range of support can be provided for those students who have further or specific learning and teaching needs.

Independent Study108
Practical classes and workshops24
Total study time156



MethodPercentage contribution
Coursework 30%
Essay 70%
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