Tom Bayliss White
Areas of interest
- Mathematical Modelling
- Data Assimilation
- Climate Change
- Ecosystems
Research centres and groups
Environmental Science Research DivisionResearch projects
Predicting harmful algal toxins in the ocean through satellite data assimilation into a novel biogeochemical model.
This project aims to integrate earth observation data from satellites into a novel biogeochemical model to predict harmful algal bloom events, at a global scale, with specific case studies on regional scales and over coastal oceans. Harmful algal blooms produce toxins that can be deadly to other organisms, like fish. As such, being able to predict these events accurately could prove useful for communities reliant on fishing as a source of income.
The project is funded by UKRI (United Kingdom Research and Innovation) through the AFESP DTP (Advancing the Frontiers of Earth System Prediction Doctoral Training Programme).
Supervisors:
Professor Shovonlal Roy (University of Reading)
David Ford (UK Met Office)