PhD Studentship Exploiting new observations and data assimilation techniques for improved forecasting of convective precipitation
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PhD Studentship Exploiting new observations and data assimilation techniques for improved forecasting of convective precipitation

Funding Status: Directly Funded Project (Due to funding restrictions, European/UK students only)

Application Deadline: 05 July 2013

Project Description

The Department of Mathematics at the University of Surrey invites applications from enthusiastic well-qualified students for a fully-funded 3.5 year PhD. The successful candidate will join an enthusiastic and friendly department with an excellent international reputation and a lively community of PhD students and postdoctoral researchers.

Research Project

Brief periods of intense rainfall can lead to flash flooding with the potential to cause millions of pounds of damage to property, and to threaten lives. Accurate flood warnings even just a few hours ahead can allow preparations to be made to minimize damage. In order to improve the prediction of these events, more accurate forecasts of heavy rainfall are needed, which can then be used to inform flood prediction and warning systems. The UK Met Office is developing a new numerical weather prediction system with the goal of improving severe weather forecasts. The research project described here is funded by NERC, and it involves collaboration between the universities of Surrey and Reading, and the Met Office.

To reduce error growth in forecasts caused by initial condition errors, effective assimilation at the convective-scale will require ways of treating moist processes and unbalanced flows that are largely absent from present-day systems. Our objectives are to characterise the stability of the Perturbation Forecast model in early stage convection and use the results to design a new set of moist control variables that allow better use of cloud and rain affected observations.

The evolution of a forecast event often involves a sequence of relatively well-defined flow regimes. For example, the diurnal cycle may evolve from a nocturnal stable boundary layer, through a convective boundary layer, a shallow-cumulus-capped boundary layer to the development of deep, moist convection. A change in regime may be identified with a change in the stability properties of the large-scale average atmospheric state, e.g., a change in sign of a Richardson number corresponds to a change in flow regime. In this project, the moist stability of the Unified Model (UM) and Perturbation Forecast (PF) model will be studied. The results may inform work relating to the design of PF model physics and moist control variables.

Entry Requirements

Candidates should normally have a good MMath, MSc degree or a first class honours degree in mathematics, physical sciences or engineering.

Funding Notes 

A NERC-funded PhD project, supervised by Prof Ian Roulstone (Surrey) and co-supervised by Prof Peter Clark (Reading)

How to Apply

Applicants should complete the on-line application form at http://www.surrey.ac.uk/postgraduate/courses/physicalsciences/mathematics-phd/.

For full consideration, applications should be received no later than 5th July 2013.

Informal Enquiries.

Informal enquiries may be addressed to the supervisor, Prof Ian Roulstone ( I.Roulstone@surrey.ac.uk ) For general questions about the PhD programme, please contact the PGR Coordinators, Dr Gianne Derks and Dr Martin Wolf ( maths-phd@surrey.ac.uk ).

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