PhD Studentship: Statistical Post-Processing of Ensemble Forecasts of Compound Weather Risk

University of Exeter - College of Engineering, Mathematics and Physical Sciences

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 six Research Organisation partners:  British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology, the Met Office, 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/.

The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018, research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students.

Supervisors:

Lead supervisor: Dr Frank Kwasniok
Co-Supervisor: Dr Chris Ferro
Co-Supervisor: Prof Jonathan Rougier
Co-Supervisor: Dr Gavin Evans
Co-Supervisor: Dr Piers Buchannan

Project description:

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.

Project Aims and Methods

The main objectives of the project are:
(i) to develop and explore novel methods for multivariate statistical post-processing of forecast ensembles with a particular view to extreme weather events;
(ii) to improve probabilistic prediction of UK compound weather risk due to temperature, wind speed and precipitation;
(iii) to help implement better techniques in the Met Office's operational post-processing suite in order to improve prediction of UK compound weather risk.

Candidate

We will require at least an upper second class honours degree in a relevant subject such as mathematics, statistics or meteorology. Pre-existing knowledge in statistics and/or numerical weather prediction as evidenced by appropriate module choices will be an advantage.

Case Award Description

The Met Office as CASE partner will contribute £1,000 per year over the duration of the studentship. The student will spend at least three months (probably six to eight weeks per year) working at the Met Office. The Met Office will provide suitable data sets for the project as well as appropriate guidance.

Share this PhD
     
  Share by Email   Print this job   More sharing options
We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

PhD

Location(s):

South West England