Incorporating machine learning methods and post-processing to produce optimal weather forecasts, NERC GW4+ DTP PhD studentship for September 2025 Entry Ref: 5407

Supervisors

Lead Supervisor Frank Kwasniok, University of Exeter, Mathematics and Statistics

Additional Supervisors

Peter Challenor, University of Exeter, Mathematics and Statistics 

Location:  Streatham Campus, University of Exeter

About the Partnership

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 £19,237 p.a. for 2024/25) 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 £1,000 for specialist training courses and expenses.

Project details

For information relating to the research project please contact the lead Supervisor via f.kwasniok@exeter.ac.uk

Project Aims and Methods

Weather forecasts are usually generated by ensembles of numerical weather prediction models, each with different initial conditions to quantify the uncertainty present in atmospheric phenomena. While nowadays errors are small in large-scale synoptic variables such as geopotential height, there are still significant biases and errors in dispersion in smaller-scale local weather elements, thus necessitating the application of statistical post-processing techniques to alleviate these issues and produce accurate and well-calibrated probabilistic forecasts. 
This project will develop and explore novel statistical and machine learning approaches for turning raw ensembles into probabilistic forecasts. The main interest will be on non-Gaussian variables such as precipitation, wind speed and wind gusts. Relationships between large-scale weather regimes and local scale forecast errors may be investigated and harnessed for forecast improvement. Emphasis will be on multivariate methods which consider and preserve cross-site, cross-temporal and cross-variable correlations. The project may also look at the efficient blending of forecasts from different sources and in particular combinations of physics-based models and machine learning models. General forecast performance will be assessed with a particular focus on high-impact extreme events. 
This studentship will include the opportunity of a work placement for the student at the Met Office as CASE partner. 

 Project partners

The Met Office will contribute through (i) Providing co-supervision by the Met Office supervisor Dr Gavin Evans for the duration of the project. (ii) Providing the opportunity for the student to spend time physically located at the Met Office (at least three months) during their PhD including gaining an insight into the day-to-day concerns of the post-processing teams at the Met Office. (iii) The work undertaken by the student will also have the potential to influence the operational post-processing of weather forecasts at the Met Office. 

 Training

The DTP offers funding to undertake specialist training relating to the student’s specialist area of research. 

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.  For further details please see the NERC GW4+ website.

Those not meeting the nationality and residency requirements to be treated as a ‘home’ student may apply for a limited number of full studentships for international students. Although international students are usually charged a higher tuition fee rate than ‘home’ students, those international students offered a NERC GW4+ Doctoral Training Partnership full studentship starting in 2025 will only be charged the ‘home’ tuition fee rate (which will be covered by the studentship). 

International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. More information on this is available from the universities you are applying to (contact details are provided in the project description that you are interested in.

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.
 

Equality, Diversity and Inclusion

The University of Exeter is committed to promoting and supporting equality, diversity, and inclusion within our working environments and is at the heart of all our activities.  With over 27,000 students and 6,400 staff from 180 different countries we offer a diverse and engaging environment where our diversity is celebrated and valued as a major strength. 
We actively encourage applicants with varied experiences and backgrounds and from all sections of the community regardless of age, race, ethnicity, sexual orientation, gender, religion, or disability status.  We are committed to creating an inclusive culture where all members of our community are supported to thrive.
Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented within our postgraduate research student community.  Reasonable adjustments are available for interviews and workspaces.
 

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

Apply now

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
• Personal Statement (Please use the template in the link provided)
• 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, please see the entry requirements for details.
• Two references

Reference information
You will be asked to submit two references as part of the application process.  If you are not able to upload  your reference documents with your application please ensure you provide details of your referees.  If you provide contact details of referees only, 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 pgradmissions@ex.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 Midnight 13th January 2025. Interviews will be held between 24 February and 7 March 2025.  

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 pgrapplicants@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