Statistical modelling of extreme sea surface temperatures and marine heatwaves.

This project is partnered with EDF Energy Research and Development UK and EDF Group. In the UK, EDF is one of the largest energy companies and largest producers of low-carbon electricity, generating around one-fifth of the UK's electricity. One of their priorities is safety which required that the Nuclear Power Plants (NPP) are resilient to natural hazards. Sea water is used as a coolant for the NPPs, meaning high sea surface temperatures (SST) could reduce the efficiency of cooling systems, increase the risk of overheating leading to heat-related equipment failures and impact marine ecosystems.
The main aim of this project is to use statistical methodologies to improve the understanding of changes in high/low (SST) in coastal regions around the UK before using these findings to develop novel statistical models to predict the future magnitude, extent, and frequency of extreme (high/low) SSTs and marine heat waves. Objectives include making statistical predictions based on the SST data, whilst reducing uncertainty in model inference and improving the accuracy of risk estimates e.g. 1 in 100-year events at a single site and extending this to predicting spatial variability of such events.
The main research areas of focus are time series analysis, extreme value analysis and geospatial modelling.