phd studentship: statistical post-processing of ensemble forecasts of compound weather risk. mathematics phd studentship (nerc gw4+ dtp funded) ref: 4024
University of Exeter
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State University, Browse similar opportunities
Lead Supervisor
Dr Frank Kwasniok , University of Exeter.
Additional Supervisors
Dr Chris Ferro, University of Exeter.
Dr Gavin Evans, Met Office.
Dr Piers Buchanan, Met Office.
Location: Streatham Campus, University of Exeter, Exeter, Devon.
This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP). The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme, please see http://nercgw4plus.ac.uk/
Project Details
Probabilistic weather forecasts present users with likelihoods for the occurrence of different weather events. Demand for such forecasts is increasing as they provide users with a basis for risk-based decisions. For example, a council may decide to deploy a road gritting service if the probability of widespread ice formation exceeds 50%. It is crucial that probabilistic forecasts are well calibrated. For example, events predicted to occur with probability 70% should subsequently occur 70% of the time. Decisions based on poorly calibrated forecasts, forecasts in which the probability of an event is systematically under- or overestimated, could lead to inappropriate actions and significant losses. This is particularly true for extreme weather events which impact most heavily on society.
While an extreme event at a single location can be damaging to the local area, the consequences may be even more serious if there is a compounding effect due to (i) the event occurring simultaneously at several locations, (ii) several meteorological variables taking extreme values at the same time (e.g., wind speed and precipitation) or (iii) temporal persistence of the event or serial clustering of several events of the same type.
The project will develop novel multivariate statistical techniques for recalibrating forecast ensembles that capture spatial, temporal and cross-variable structure. These will improve probabilistic prediction of compound weather risk. A particular emphasis will lie on high-impact extreme weather events.
Eligibility
Please note that there has been a revision to the eligibility criteria for this award. Details can be found at "https://www.exeter.ac.uk/pg-research/money/phdfunding/fundedcentres/gw4/" .
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