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 the future of these catasprophic events by analysing state-of-the-art climate model simulation. Atmosphere-Ocean Coupled climate models are the core tool to understand in an experimental set-up anthropogenic impacts on our climate system. Previous climate model experiments revealed a regional increase of extreme cyclones over the Northeast Atlantic, affecting large parts of the UK and western central Europe (e.g., Leckebusch et al., 2006; Zappa et al., 2013). Based on a comparison between the two multi-model ensembles from the IPCC Climate Model Intercomparison Projects’ (CMIP5 and the latest CMIP6) AOGCM simulations, unceratinties of future projections will be diagnosed in a new systematic way. A core aspect is the identification of the trajectory of changes and uncertainties under future conditions from CMIP5 to CMIP6 experiments (Eyring et al., 2016).
USETA will utilise the CMIP5 and CMIP6 multi-model ensemble experiments. The latter are the latest set of core experiments for the next IPCC report and the first CMIP6 datasets are expected to be ESGF published around mid of 2018.
These multi-model ensembles are analysed in two steps: Firstly, 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). Secondly, robust measures of uncertainties are derived via the Multi-Model Combinatorics Approach (MMCA, Donat et al., 2011) by means of a newly developed tool at the University of Birmingham.
This will allow for the systematic assessment of uncertainties with respect to different model validation metrics.
Training and Skills
CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to the student's projects and themes.
Specific for this project, the PhD student will gain skills to analyse state-of-the-art model data. This training will be in advanced diagnostics of AOGCM models data 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: Identification of extreme cyclones and wind storms in CMIP5 & CMIP6 AOGCM simulations for different emission scenarios.
Year 2: Assessment of the anthropogenic climate change signal and its uncertainties following the MMCA approach.
Year 3: Detailed analysis of factors influencing the uncertainty of ACC signals depending on process-based AOGCM evaluation and application to uncertainties in potential damage estimates.
Partners and collaboration (including CASE)
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 of meteorology, the realisation of interdisciplinary projects, excellent links to end-users and stakeholders, including industry, which sponsored multiple projects of the group. The expected results will be discussed with partners from other universities, Met Services as well as from industry (CAT modellers, reinsurance, science-industry fori and brokers). A longer internship in industry is planned during the project duration.
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.
T: +44 (0)121 41 45518