About the project or challenge area

Regional numerical models of marine ecosystems provide valuable information on the state of the Northwest European shelf. A limitation of these models is the ability to capture the timing and strength of the spring bloom accurately. Recent research has shown that including a coupled wave model influences the bloom through improved representation of mixing dynamics and nutrient cycles in the upper ocean.

Additionally, coupling the ocean with an atmospheric model would improve the representation of heat and energy exchange at the ocean surface, which has not been tested but could affect bloom dynamics.

This project will capitalise on recent high-resolution simulations run at the Met Office in collaboration with Plymouth Marine Laboratory, analysing the output to identify changes in bloom features in the Northwest European shelf between ocean-only, ocean-wave and ocean-wave-atmosphere runs. The driving forces and mechanisms that influence these changes will be quantified with the opportunity to publish the findings.

If time allows, the successful candidate will also examine ocean phytoplankton colour feedback from the biogeochemistry into the atmosphere. This feedback arises during phytoplankton blooms, where light is trapped closer to the surface, shallowing the mixed layer depth and impacting sea surface warming. This will build upon prior work, adding this feedback into the ocean component.

Why choose this project?

This is a pre-defined project with scope to expand. You will have the opportunity to spend time at both the UK Met Office and Plymouth Marine Laboratory.  

UK Met Office – Support and expertise on weather forecasting and the coupled system that has produced the data.
Plymouth Marine Laboratory – Expertise in coupled biogeochemical models and analysis of phytoplankton blooms.

About you

You will have experience in data analysis; an interest or experience in oceanography, in particular marine biogeochemistry. The University of Bristol provides additional training in Linux commands; Python programming for data analysis and plotting

How to apply

All students can apply using the button below, following the Admissions Statement (PDF, 188kB). This project is not funded, for further details please use this link.

Before applying, we recommend getting in touch with the project's supervisors. If you are interested in this project and would like to learn more about the research you will be undertaking, please use the contact details on this page.