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Award details

University of Exeter funding: NERC GW4+ DTP PhD studentship

Statistical modelling of extreme weather events: combining multiple data sources and quantifying estimate uncertainty. Mathematics PhD studentship (NERC GW4+ DTP funded) Ref: 3998

About the award

Supervisors

Lead Supervisor

Ben Youngman, University of Exeter.

Additional Supervisors

Simon Brown, Met Office - Hadley Centre

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/

For eligible successful applicants, the studentships comprises:

  • An stipend for 3.5 years (currently £15,285 p.a. for 2020-21) in line with UK Research and Innovation rates
  • Payment of university tuition fees;
  • A research budget of £11,000 for an international conference, lab, field and research expenses;
  • A training budget of £3,250 for specialist training courses and expenses.
  • Up to £750 for travel and accomodation for compulsory cohort events.


Project details

Project Background:

The UK experiences various types of extreme weather event, such as heatwaves and storms. Understanding the frequency and severity of such events from a probabilistic perspective today is important so that we can be protected against them. However, structures built to withstand extreme weather are typically expected to last decades or even centuries. Over such periods of time, just like the climate can change, so too can the probabilistic properties of extreme weather events. Therefore, our understanding of extreme weather events not only needs to cover their frequency and severity, but also how these features will change in future.

Project Aims and Methods:

This project will develop statistical methodology based on extreme value theory (EVT) for quantifying the probabilistic properties of extreme weather events in the UK in the present day and in the future. Tackling this problem is likely to be a two-stage process: addressing present day estimation, and then allowing for the additional uncertainty of what will happen in the future.

We can use models based on EVT with suitable data to quantitatively understand extreme weather events, such as storms, heavy rainfall and heatwaves. However, the inevitable rarity of such events make scarce the data that we might want for precise estimates, for example from weather stations. UKCP18 offers a new and rich source of high-resolution (~2km) simulated data for the UK. Its provision in gridded form provides spatial completeness. Gridding, however, means that weather events can only be captured at the grid’s resolution; sub-grid-scale features, such as localised thunderstorms, will be missed. Hence we want to somehow downscale any gridded data. This project there aims to develop methodology to simultaneously use multiple sources of extreme weather data, in an attempt to overcome data scarcity, while allowing for the different properties of each data source.

The ability to reliably estimate extremes from gridded data is particularly important when wanting to understand their behaviour in the future, as this is typically the only format in which future projections arrive. Downscaling, however, is not enough. Estimates of rare events, such as at 1-in-100 or 1-in-1000 year levels, are inevitably accompanied by relatively large uncertainty, which must be reported to provide an honest representation. These uncertainties exists in present-day estimates, but future estimates must also allow for uncertainty in projections of the future. UKCP18 provides ensembles or projections for different RCP scenarios. This project will develop methodology to incorporate these data when estimating future extreme weather events and their uncertainty.

Candidate requirements:

The ideal candidate for this project will have a strong background in mathematics, and statistical modelling at undergraduate – and preferably Master’s – level and experience in computer programming in R, Python or similar.

Collaborative partner:

Supervision meetings will be shared between the Met Office and University of Exeter. Visits to the Met Office for project-related matters, such as data collection and processing, will also be facilitated.

Training:

The successful applicant will be encouraged to attend four Academy for Postgraduate Training in Statistics (APTS) courses. Funding will also be available for other courses and summer schools or workshops and conferences relevant to the project, such as on statistics (e.g. EVA2021), programming or meteorology (e.g. EGU2021).

Background reading and references:

Coles, SG (2001) An Introduction to Statistical Modeling of Extreme Values, Springer.
Youngman, B. D. (2019). Generalized additive models for exceedances of high thresholds with an application to return level estimation for US wind gusts. Journal of the American Statistical Association 114(528), 1865–1879.

Useful links:

For information relating to the research project please contact the lead Supervisor via b.youngman@exeter.ac.uk or see http://www.exeter.ac.uk/youngman.

Prospective applicants:

For information about the application process please contact the Admissions team via pgrenquiries@exeter.ac.uk.

Each research studentship project advertisement has an ‘Apply Now’ button linking to an application portal. Please note that applications received via other routes including a standard programme application route will not be considered for the studentship funding.

Eligibility

NERC GW4+ DTP studentships are open to UK and Irish nationals who, if successful in their applications, will receive a full studentship including payment of university tuition fees at the home fees rate.

A limited number of full studentships are also available to international students which are defined as EU (excluding Irish nationals), EEA, Swiss and all other non-UK nationals.

Studentships for international students will only cover fees at the UK home fees rate. However, university tuition fees for international students are higher than the UK home fees rate therefore the difference will need to be funded from a separate source which the student or project supervisor may have to find. Unfortunately, the NERC GW4+ DTP cannot fund this difference from out studentship funding Further guidance on how this will work will be issued in November.

The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.


 

Entry requirements

Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK.   Applicants with a Lower Second Class degree will be considered if they also have Master’s degree.  Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply.

All applicants would need to meet our English language requirements by the start of the  project http://www.exeter.ac.uk/postgraduate/apply/english/.

 

How to apply

In the application process you will be asked to upload several documents.  Please note our preferred format is PDF, each file named with your surname and the name of the document, eg. “Smith – CV.pdf”, “Smith – Cover Letter.pdf”, “Smith – Transcript.pdf”.

  • CV
  • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project.
  • Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim transcript if you are still studying.
  • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English.

Reference information
You will be asked to name 2 referees as part of the application process, however we will not expect receipt of references until after the shortlisting stage. Your referees should not be from the prospective supervisory team.

If you are shortlisted for interview, please ensure that your two academic referees email their references to the pgr-recruitment@exeter.ac.uk, 7 days prior to the interview dates.  Please note that we will not be contacting referees to request references, you must arrange for them to be submitted to us by the deadline.

References should be submitted by your referees to us directly in the form of a letter. Referees must email their references to us from their institutional email accounts. We cannot accept references from personal/private email accounts, unless it is a scanned document on institutional headed paper and signed by the referee.

All application documents must be submitted in English. Certified translated copies of academic qualifications must also be provided.

The closing date for applications is Friday 8 January 2021 2359 GMT .  Interviews will be held between 8th and 19th February 2021.  For more information about the NERC GW4+ DPT please visit https://nercgw4plus.ac.uk

If you have any general enquiries about the application process please email pgrenquiries@exeter.ac.uk.  Project-specific queries should be directed to the lead supervisor.


Data Sharing
During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

  • the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
  • administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.

Summary

Application deadline:8th January 2021
Value:£15,285 per annum for 2020-21
Duration of award:per year
Contact: PGR Enquiries pgrenquiries@exeter.ac.uk