Project Highlights:

  • Analysis of the natural hazard extreme wind storms and application of the latest diagnostic approaches
  • Assessment of latest state-of-the-art seasonal to decadal prediction systems
  • High relevance for future impact assessments



Severe extra-tropical cyclones are the major natural hazard for the North-Atlantic/European region and especially for the UK. Extreme winter seasons may see up to 15-20 strong, partly damage prone events hitting, e.g. the UK and neighbouring countries. These severe storms are causing damages by extreme wind speeds as well as large precipitation rates. Impacts are manifold and lead to destruction of infrastructure as well as fatalities during the passage of the storm. For example, in 2015, at the end of the year, Winter Storms Desmond and Eva brought wide-scale flooding to the United Kingdom, causing overall losses of almost US$ 3bn, roughly US$ 2bn of which was insured (Munich Re, 2016).

This project will investigate key features of these catastrophic events by analysing state-of-the-art seasonal and decadal predictions. By means of systematic analyses of these forecast ensembles with respect to three major topics, the project will contribute to our wider understanding of drivers of seasonal, interannual to sub-decadal variability of these extreme hazards for Europe. The three main topics are:

  • Seasonal and sub-decadal predictability (e.g., Befort et al., 2018; Walz et al., 2018b; Kruschke et al., 2014, Renggli et al., 2011),
  • Time and spatial clustering of wind storms and their impacts (e.g., Walz et al., 2018a; Walz and Leckebusch, 2019a,b), and
  • Investigations into the signal to noise paradox for extra-tropical cyclone prediction (Scaife & Smith, 2018).
Figure 1: Cyclonic Cloud formation over the City of London: What is driving storm variability and can we predict their frequency, intensity and impacts?


These multi-member ensembles simulations are analysed firstly for the occurrence of extreme events: extreme cyclones and wind storms are objectively identified and tracked with the specific wind and cyclone tracking tools (Leckebusch et al., 2008; Murray & Simmonds, 1991). Latest forecast suites will be tracked (GloSea5 & Decadal Prediction System) and the predictive skill analysed in comparison to observational data sets (e.g. re-analyses). Factors for skill and its variability in time and dependency of the state of the atmosphere will be investigated (Topic 1). Time and spatial clustering of severe events will be diagnosed following Walz et al. (2018a,b) and the potential impact diagnosed via the open access CAT model Climada (Topic 2). The signal to noise paradox (Topic 3) will be investigated for Atlantic storm activity to understand its relationship with the large scale time mean pressure field.

Training and Skills

Specific for this project, the PhD student will gain skills to analyse state-of-the-art seasonal to decadal model data. This training will be in advanced diagnostics of ensemble simulations (e.g. storm tracking) as well as in multivariate statistical techniques, specifically in: extreme value and multi-variate analytical statistics, statistical modelling (multi-linear regression), CAT models and their specific features to model hazards, vulnerabilities and exposure, relevant programming skills to analyse model data, giving the student skills identified as ‘most wanted’ for environmental jobs. This is excellent employment market preparation as scientific research skills, technical analysis and industry related model skills will be practiced and gained.


Year 1: Extreme wind storms and cyclones are tracked in GloSea5 & Met Office Decadal Prediction Systems, first analyses to predictive skill and its variability

Year 2: Spatial and time clustering are derived from the forecast suits and systematically compared to re-analyses and dependencies from large-scale atmospheric variability modes diagnosed

Year 3: Focus in year three will be the work on the signal to noise paradox, based on hindcasts of storms and their relationship to the winter mean North Atlantic Oscillation.


Partners and collaboration (including CASE)

This project is a collaboration between the University of Birmingham’s Meteorology and Climate group and the UK Met Office Hadley Centre, a strategic partner of CENTA. The group of Dr Leckebusch is strongly linked to end-users of the derived climate change information, especially with respect to robust assessments of uncertainties. The group has extensive experience in real-world applications in meteorology, the realisation of interdisciplinary projects, excellent links to end-users and stakeholders, including industry, which sponsored multiple projects of the group. Prof Scaife is head of the world-leading Monthly to Decadal Prediction Group at the Met Office Hadley Centre. A placement at the Met Office and or in industry is planned during the project duration.

Further Details

Further details to the work of the Meteorology and Climate Group at the University of Birmingham can be found here:


Further details to the Met Office Hadley Centre Group for Monthly to Decadal Prediction can be found here:


Any further questions, please contact:

Dr Gregor C. Leckebusch, Reader in Meteorology and Climatology

School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom.

E: G.C.Leckebusch@bham.ac.uk

T: +44 (0)121 41 45518