This project looks to combine computer science, statistics and meteorology to produce a new set of storm typologies which can be used to enhance our understanding of extreme storms throughout the UK.

Project outline

The impacts of extreme weather across the UK continue to have devastating economic and social consequences. One key mechanism which can lead to a disaster is flooding which is some cases can be caused by extreme rainfall. A prime example of the costs associated with flooding can be seen in December, 2015 where record breaking levels of precipitation caused extensive flooding in Cumbria leading to at least 16,000 homes being flooded. Traditionally, design events are calculated by fitting a statistical distribution to a sample of annual maximum events, assuming this distribution to be constant and that all observed events originate from the same underlying population.

However, recent research has highlighted the importance of better understanding the underlying processes associated with individual events in order to: 1) build more robust models representing the existence of mixed populations, and 2) better understand how global climate change is likely to affect the type, magnitude and frequency of more localised distributions of extreme rainfall and floods. In this context it is important to develop new methods that will allow an objective classification of event types. This project looks to combine computer science, statistics and meteorology to produce a new set of storm typologies which can be used to enhance our understanding of extreme storms throughout the UK.

Science

Combining advanced classification schemes with big data sets from meteorology, hydrology and the atmosphere this project twill produce a new set of storm typologies.

Impact

A classification scheme for storms in the UK will enhance our abilities to assess the expected impacts and change of these extreme events given the changes in global climate.

This PhD project is supervised by Dr. Thomas Kjeldsen from the Department of Civil Engineering and Architecture and Dr. Ilaria Prosdocimi from the Department of Mathematical Sciences.