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Award details

Assessing the Impact of Dynamic Turbulence Modelling on Sub-Kilometric Unified Model Simulations of Convective Storms during WesCon, NERC GW4+ DTP PhD studentship for 2022 Entry, PhD in Mathematics Ref: 4258

About the award

Supervisors

Lead Supervisor

Dr Georgios Efstathiou, University of Exeter, Department of Mathematics

Additional Supervisors

Prof Robert Plant, University of Reading, Department of Meteorology

Prof Robert Beare, University of Exeter, Department of Mathematics

Dr Adrian Lock, 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/

For eligible successful applicants, the studentships comprises:

  • An stipend for 3.5 years (currently £15,609 p.a. for 2021/22) 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

Efstathiou_1

Example simulation of shallow Cu development at high resolutionEfstathiou_2

Dynamically derived sub-grid mixing length (m). The solid lines indicate the cloud base and cloud top.

Project details

Project Background

Convective storms are responsible for many of the most violent meteorological phenomena on Earth. Deep convection is usually highly localised and difficult to accurately predict as it is dependent on interactions across a wide range of scales, from small-scale turbulent motions up to the synoptic-scale environment. A substantial step forward in our ability to forecast convective events has come with the advent of high-resolution Numerical Weather Prediction (NWP) models. However, the improvements from enhancing the model resolution are not always apparent as model results can be very sensitive to the treatment of the unresolved turbulence length scales [1]. We encounter such modelling challenges because the high-resolution NWP grid spacings correspond to the dominant scales of boundary layer turbulence and cloud development, and to scales characterising cloud mixing with its immediate environment. 

Project Aims and Methods

This PhD project aims at improving the representation of convective storms in sub-km NWP by implementing and assessing a dynamic, scale-adaptive turbulence model in the operational Met Office Unified Model (UM). The dynamic turbulence modelling approach has been developed from the Computational Fluid Dynamics community to alleviate the need for an a priori specification of closure parameters in turbulence models. This approach can provide dynamically derived length scales that will adapt to the partially resolved flow field in time and space. The use of dynamic length scales relaxes the strict assumption for a clear scale separation made in conventional turbulence schemes [2]. This can enable NWP models to better resolve convection across a range of sub-kilometric resolutions. 

The PhD student will have the opportunity to examine the performance and behaviour of the dynamic approach in a real-world setting by using data from the Wessex UK 2023 summertime convection measurement campaign (WesCon) to: a) validate individual components of the dynamic procedure and especially the spatial and temporal distribution of turbulence intensity in clouds and the boundary layer, b) improve our understanding of the relationships between boundary layer and convective clouds length-scales and c) explore the ability of the dynamic model to better represent the cloud structure and storm morphology while assessing its impact on forecast rainfall amount and intensity. The PhD project has the potential to shape the development of the Met Office’s next generation modelling system by utilising an intensive measurement campaign to develop, extend and test a new approach in realistic NWP applications.

Candidate requirements

Strong mathematical or physical sciences background is essential. Some coding experience is desirable.

Project partners

This project is co-sponsored by a Met Office CASE studentship. The PhD student will have the opportunity to take a 3-month placement at the Met Office and work closely with staff members.

Training

The DTP offers funding to undertake specialist training relating to the student’s specialist area of research. The Met Office will provide training on the UM and its new modelling system.

Background reading and references

[1] Honnert, R., Efstathiou, G., Beare, R., Ito, J., Lock, A., Neggers, R., et al. (2020). The atmospheric boundary layer and the “gray zone” of turbulence: A critical review. .Journal of Geophysical Research: Atmospheres, 125.

[2] Efstathiou, GA, Plant, RS. (2019) A dynamic extension of the pragmatic blending scheme for scale-dependent sub-grid mixing. Quarterly Journal of the Royal Meteorological Society. 145: 884– 892. 

Useful links

For information relating to the research project please contact the lead Supervisor via g.efstathiou@exeter.ac.uk https://emps.exeter.ac.uk/mathematics/staff/ge235

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 2022 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.
 


 

 

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, 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 1600 hours GMT Friday 10 January 2022. Interviews will be held between 28 February and 4 March 2022.  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:10th January 2022
Value:£15,609 per annum for 2021-2022
Duration of award:per year
Contact: PGR Enquiries pgrenquiries@exeter.ac.uk