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June 2013
Message 36

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[Met-jobs] NERC CASE PhD Studentship in data assimilation at the University of Exeter, UK

From Frank Kwasniok <F.Kwasniok@exeter.ac.uk>
To "met-jobs@lists.reading.ac.uk" <met-jobs@lists.reading.ac.uk>
Date Thu, 13 Jun 2013 23:12:40 +0100

NERC CASE PhD Studentship at Exeter Climate Systems in collaboration
with the Met Office

Project:
Efficient data assimilation to correct non-Gaussian forecast errors in
numerical weather prediction

Supervisors:
Dr Frank Kwasniok (University of Exeter) and Dr Gordon Inverarity (Met
Office, Exeter)

Duration:
Three and a half years

Exeter Climate Systems
(http://emps.exeter.ac.uk/mathematics/research/xcs/) is a growing centre
of excellence in the application of mathematics and statistics in
weather and climate science. It is located within the College of
Engineering, Mathematics and Physical Sciences at the University of
Exeter, UK. The centre has close working affiliations with the Met
Office and the Hadley Centre.

We are inviting applications for a PhD studentship in the area of data
assimilation to start in September 2013. The award covers all tuition fees (UK/EU) and a maintenance stipend at research council rate (currently £13,726 per year). As part of the CASE award the student receives an additional £1,200 per year from the Met Office, plus £1,400 on completion of the thesis. A travel and subsistence allowance is also included.

This award is available for UK students. EU candidates must have been
resident in the UK for the three years leading up to the PhD to be
eligible. International candidates are not eligible.

Project description:
---
Data assimilation allows for the systematic combination of observational
data and dynamical models and is a crucial component of numerical
weather prediction. A key assumption of standard variational data
assimilation techniques is that the forecast errors to be corrected are
Gaussian. However, this assumption becomes increasingly invalid as the
time between assimilation cycles increases and as the forecast model
becomes more nonlinear at higher resolutions. An example of a quantity
with non-Gaussian characteristics is visibility, which is an important
element of fog and air quality forecasting.

In summary, this project aims to investigate how non-Gaussian forecast
errors can be better handled in variational data assimilation. More
specifically, it aims to improve the assimilation of visibility data in
numerical weather prediction and help implement better techniques in the
Met Office's operational data assimilation system which improve the
efficiency and accuracy of the computationally expensive assimilation
and forecasting process.

The project will make use of ideas and techniques from statistics,
dynamical systems and numerics.

The student will profit from work placements at the Met Office working
with their operational data assimilation system.
---

For informal enquiries contact Dr Frank Kwasniok at F.Kwasniok@exeter.ac.uk

Application criteria:
Applicants should have or expect to achieve at least a 2:1 Honours
degree, or equivalent, in a relevant subject such as mathematics,
statistics, physics or meteorology. Candidates should have a keen
interest in the application of mathematics and statistics in weather and
climate science, and preferably some experience of programming in Matlab
and/or Fortran.

How to apply:
To apply, go to
http://www.exeter.ac.uk/studying/funding/award/index.php?id=1203 and
complete the online web form. You should choose "Mathematics PhD
Studentship in weather and climate science" from the drop-down menu. You
will be asked to submit some personal details and upload a full CV,
covering letter and details of two academic referees. Your covering
letter should outline your academic interests, prior research experience
and reasons for wishing to undertake this project.

For general enquiries please contact Liz Roberts at emps-pgr@exeter.ac.uk

The application deadline is Monday 1 July 2013.

--
Dr Frank Kwasniok
Senior Lecturer in Applied Mathematics
College of Engineering, Mathematics and Physical Sciences
University of Exeter
Harrison Building
North Park Road
Exeter EX4 4QF
United Kingdom

E-mail: F.Kwasniok@exeter.ac.uk
Tel.: +44 (0)1392 72-3978
Fax:  +44 (0)1392 217965
Web: http://empslocal.ex.ac.uk/people/staff/fk206/




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