Supervisors: Dr Hakase Hayashida, Assoc Prof Peter Strutton

Numerical ocean models describe the circulation of seawater with a set of mathematical equations. These models also describe the physical and biogeochemical properties of seawater, such as temperature, salinity, pH, nitrate, and phytoplankton biomass, that determine the conditions for marine ecosystems and biogeochemical cycling of key elements (e.g., carbon and nitrogen). Because the ocean is vast, observations are limited spatially as well as temporally. Numerical models are a particularly useful tool to fill in this observational gap, help interpret the observed variability, and therefore, improve our understanding of the ocean.

In this project, the selected student will use a one-dimensional numerical ocean model to simulate and understand the physical and biogeochemical processes in the ocean near Australia. The student will utilise the long-term oceanographic measurements conducted at one of the National Reference Stations maintained by the Australian Integrated Marine Observing System (i.e., the Maria Island, the Port Hacking, and the Rottnest Island).

The main objective of this project is to study the physical and biogeochemical processes governing the variability on seasonal, interannual, and decadal time scales using a numerical model. Depending on the interest and the progress of the student, this project can be further expanded to:

  1. Compare and contrast the oceanographic conditions at different stations.
  2. Assess the model response to perturbations (e.g., hurricanes, heatwaves, biological rates, or invasion of new species).
  3. Forecast the future oceanographic conditions in response to global warming.
  4. Evaluate the performance of existing data products (e.g., satellite-derived sea surface temperature and chlorophyll).

This project may be suitable for students who are interested in oceanography and programming. An introductory level of previous experience in programming is essential, and the student is expected to be self-motivated to learn three languages (Bash, Fortran, and Python/Matlab) during the appointment of the project (don’t worry, the supervisor will provide support as needed). A moderate level of educational background in Mathematics and Physics (e.g., ordinary differential equations) is also desirable.