Quantifying Climate-Driven Shifts in the Biological Carbon Pump Using Trends from BGC-Argo Floats
The ocean plays a major role in the global carbon cycle. Through the biological carbon pump, carbon is transferred from the sunlit surface waters to the deep ocean, helping regulate Earth’s climate. Currently, global models suggest that between 5 and 12 Gt of organic carbon is exported to the deep ocean per year. However, there is substantial uncertainty in this estimate, and when projecting into the future, models are unable to determine if more or less carbon will be exported to the deep ocean across 84% of the global ocean.
This PhD project will combine novel autonomous platforms (BGC-Argo floats) with in-situ measurements and global model outputs to examine regional and seasonal patterns in phytoplankton production and carbon export. A key goal of the project is to explore how micronutrients, especially iron, shape productivity and export efficiency, and assess how well CMIP6 models reproduce observed variability and trends.
By bringing observations and models together, the project will identify where models perform well and where they fall short, reducing uncertainty in projections of the ocean carbon sink. You will develop highly transferable skills in time-series analysis, scientific coding, data-model integration and clear communication, while tackling a pressing climate problem.
Training is delivered through one-to-one supervision (Ratnarajah, Wade, Tagliabue), weekly lab meetings and short courses. You will learn to translate methods from the literature into clear, reproducible code, and to read, test and profile existing code. Co-supervision with the University of Liverpool (Prof Tagliabue) provides modelling mentorship, including diagnosing how global models represent primary production and carbon export, and designing robust observation-model comparisons.
Graduates will develop strong, transferable skills in scientific coding, statistics, time-series analysis, and model-data integration. These capabilities are highly relevant whether you remain on an academic path or move into industry roles in environmental data science, climate-tech, consultancy and related sectors.
