University of Exeter funding: NERC GW4+ DTP PhD studentship

Ocean heat waves or frozen seas: can we make seasonal ocean forecasts? PhD in Mathematics (NERC GW4+ DTP) Ref: 3696

About the award

Supervisors

Lead Supervisor

Dr Jennifer Catto, Department of Mathematics, College of Engineering, Mathematics and Physical Sciences, University of Exeter

Additional Supervisors

Dr Jonathan Tinker, Met Office

Dr Jennifer Graham, CEFAS

Location: University of Exeter, Streatham Campus, Exeter, EX4 4QJ

This project is one of a number that are in competition for funding from the NERC GW4+ Doctoral Training Partnership (GW4+ DTP).  The GW4+ DTP consists of the GW4 Alliance of research-intensive universities: the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five unique and prestigious Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology & Hydrology, the Natural History Museum and Plymouth Marine Laboratory.  The partnership aims to provide a broad training in the Earth, Environmental and Life sciences, designed to train tomorrow’s leaders in scientific research, business, technology and policy-making. For further details about the programme please see http://nercgw4plus.ac.uk/

For eligible successful applicants, the studentships comprises:

  • A stipend for 3.5 years (currently £15,009 p.a. for 2019/20) 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.
  • Travel and accommodation is covered for all compulsory DTP cohort events
  • No course fees for courses run by the DTP

We are currently advertising projects for a total of 10 studentships at the University of Exeter.

Eligibility

Students who are resident in EU countries are eligible for the full award on the same basis as UK residents.  Applicants resident outside of the EU (classed as International for tuition fee purposes) are not eligible for DTP funding. Residency rules are complex and if you have not been resident in the UK or EU for the 3 years prior to the start of the studentship, please apply and we will check eligibility upon shortlisting.

Project Background

Seasonal forecasting is at the cutting edge of climate science and is used by many (terrestrial) industries, such as agriculture, the energy sector, and commodity trading. The UK shelf seas support a large diverse ecosystem, and many industries (e.g. fisheries, tourism, off-shore operations, and shipping). All of these are affected by weather and climate variability, with impacts above and below the sea surface. This drives an appetite for predictions and projections over a wide range of timescales. 

While short-term forecasts and long-term climate projections exist for this region, seasonal forecasts are currently lacking. Recent progress in ocean and atmosphere modelling systems at the Met Office provide the potential for seasonal ocean forecasts to be developed. Seasonal forecasts have proved to be valuable in other regions of the world (e.g. U.S.A., Australia, Payne et al. (2017).). Now is the perfect time to develop them for our region. 

Project Aims and Methods 

This project will develop a new seasonal forecasting product for the European Northwest Shelf (NWS). There are various approaches available for designing marine forecasts for this region. These include either use of existing global ocean forecasting systems developed at the Met Office, or “downscaling” these global models to provide more detailed information across the region. 

The student will help develop the key scientific questions of the PhD with the guidance of the supervisory team, based on their existing expertise and interests. However, initial questions may include:

  • Can global models predict seasonality across the NWS; are some properties more predictable than others? 
  • What benefits can be gained from downscaling methods; does increased detail mean increased predictability? 
  • What are the mechanisms behind this predictability?

The student will be expected to spend at least 3 months working on site at Met Office HQ, Exeter, where they will receive hands-on training and experience in running Met Office ocean forecast models. 

Collaboration with partners at CEFAS will provide additional insight into applications of these results. For example, how predicting changes in temperature or salinity may help to predict changes in ocean ecosystems. 

ocean

Regional ocean models are already used to forecast changes in temperature around the North West Shelf on daily to weekly timescales.

Candidate Requirements

The candidate must have achieved, or be expected to achieve, a first class or 2:1 degree in Meteorology, Oceanography, Mathematics, Physics, Environmental Science or related field. A Master’s level qualification with previous experience of conducting independent research is desirable. Knowledge of scientific programming languages (e.g., Python, Matlab, IDL, R) would be advantageous.

CASE or Collaborative Partner

The student will spend approximately 3 months of their time working at Met Office HQ in Exeter with Dr Jonathan Tinker, an expert in the climate of the Northwest European Shelf Seas region, gaining experience with Met Office seasonal forecasting systems.

Dr Jennifer Graham (CEFAS) has expertise in ocean modelling for a wide variety of applications. Collaboration with partners at CEFAS will provide additional insight into broader applications or policy relevance of any results from this project.

Training

The candidate will be based within the internationally recognised Exeter Climate Systems Research Centre. They will receive training on data analysis of large datasets (Big Data), climate modelling, scientific writing and presenting in accordance with the postgraduate programme at the University of Exeter. The candidate will present at both national and international conferences.

The Met Office and CEFAS will provide training in the use and applications of ocean forecast systems. At the Met Office they will receive training in the use of its High Performance Computing facilities for running ocean models.

References / Background reading list 

Tinker, J., et al.. (2018). What are the prospects for seasonal prediction of the marine environment of the NW European shelf?, Ocean Science, 14: 887-909 doi:10.5194/os-14-887-2018.

MacLachlan, C., et al. (2014). Global Seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system, Quarterly Journal of the Royal Meteorological Society, 141(689): 1072-1084 doi:10.1002/qj.2396.

Payne et al. (2017). Lessons from the First Generation of Marine Ecological Forecast Products, Frontiers in Marine Science. doi:10.3389/fmars.2017.00289

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 1600 hours GMT Monday 6 January 2020.  Interviews will be held between 10 and 21 February 2020.  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:6th January 2020
Value:£15,009 per annum for 2019-20
Duration of award:per year
Contact: PGR Enquiries pgrenquiries@exeter.ac.uk