Various branches of mathematics contribute to XCS with our staff being members of research teams such as Geophysical and Astrophysical Fluid Dynamics, Dynamical Systems and Analysis, Statistics and Data Science, and Weather and Climate Science.
Specific long-running themes in our research interest include:
- Improving weather and climate models
- Understanding and quantifying storm risk
- Interpretation and post-processing of forecasts
- Forecast verification
- Uncertainty quantification
- Modelling of climate tipping points
If you wish to get in touch with us about any aspects of our research then please contact Prof. David Stephenson who is the director of XCS.
Exeter Storm Risk group
The Exeter Storm Risk group is part of the Exeter Climate Systems research centre. Since 1998, members of the group have established a world-renowned track record in the quantification of risk due hydro-meteorological hazards responsible for large insurance losses and in the visualisation and communication of the associated uncertainty.
The main topics of our research are:
- windstorms (intense extratropical cyclones)
- hurricanes and tyhoons (intense tropical cyclones)
- extreme rainfall
Our interdisciplinary approach is based on concepts and techniques from dynamical systems theory, extreme value theory, climate science, and spatial statistics. The aim of our research activity is to help improve fundamental understanding and prediction of severe weather and its interaction with society.
Prediction and Evaluation
Our research aims to improve weather and climate predictions by developing better ways of constructing probabilistic predictions and of evaluating the performance of prediction systems. A notable feature of our research is our focus on predictions of rare events, which often have the most severe impacts on the world.
Our prediction work focuses on generating and post-processing ensembles of projections from numerical weather and climate models. Our evaluation work includes methods for assessing predictions ranging from short-term weather forecasts to decadal climate predictions, for predicting how changing a prediction system will affect its performance, and for understanding the physical processes underlying predictive performance.
The methods that we develop rely on exploiting patterns in the relationships between model projections, predictions and observations, which means that statistical modelling underpins all of our research.
Improving Weather and Climate Models
The Improving Weather and Climate Models area is focused on studying the atmospheric boundary layer and dynamical meteorology and links closely to work in the Geophysical and Astrophysical Fluid Dynamics.
Members of this group have been collaborating with the Met Office Dynamics Research group for over ten years, helping to develop and improve the numerical methods for a new weather and climate model dynamical core known as ENDGame.
Recently there has been renewed interest worldwide in alternatives to the latitude-longitude gridding of the sphere, driven largely by developments in supercomputer architecture, and the expectation that the resolution clustering near the poles of the latitude-longitude grid will lead to a communication bottleneck and poor performance on massively parallel computers. In collaboration with the US NCAR and LANL laboratories, and also under a new Met Office NERC/STFC initiative in the UK called Gung-Ho, Prof. Thuburn has been developing numerical methods for some of the candidate alternative grids. See here.
The boundary layer is the layer of the atmosphere in which we live and ranges between 100 m and 1 km in depth. It is often turbulent, that is to say the winds fluctuate on timescales of minutes. The gusts of wind that we experience daily are evidence of these turbulent fluctuations. The turbulent fluctuations are responsible for transporting important physical properties such as moisture, heat and momentum to and from the surface. The boundary layer's transport properties play a fundamental role in both the short range (weather- days) and long range (climate- years) evolution of the atmosphere. Currently, there are projects on:
- The use of balance in understanding how the boundary layer couples with the larger scale (in collaboration with Mike Cullen, Met Office).
- The dispersion of pollution by the early evening boundary layer (PhD student, Alex Taylor, CASE partner David Thomson, Met Office)
- Modelling the observed Antarctic boundary layer for Astrophysical applications (PhD student, Kieran Walesby, in collaboration with Phil Anderson, British Antarctic Survey and University of Exeter Astrophysics).
- Modelling the boundary layer in the grey-zone (when the eddies are partially resolved), in collaboration with Adrian Lock, Met Office.
- Dr Bob Beare - Associate Professor
- Professor John Thuburn - Professor
- Professor Geoffrey Vallis - Professor
- Professor Beth Wingate - Professor
We have been developing a radically new approach to the representation of convection in weather and climate models - the 'multi-fluid' approach, based on solving a set of conditionally filtered governing equations. The multi-fluid approach is conceptually related to the widely used mass flux approach, but avoids the simplifying assumptions that limit its applicability. The figure shows that a single-column two-fluid model can capture the initiation, growth, and decay of the cloud field in a standard test case (ARM); a Large-Eddy Simulation provides a reference solution.
To be efficient on future generations of supercomputers, weather and climate models must use more uniform spherical grids such as the 'cubed sphere' or 'hexagonal-icosahedral' grids. We have been working with the Met Office to develop novel numerical methods for
these new grids that are as accurate as current operational schemes. A key idea is that the numerical methods must mimic fundamental mathematical properties of the underpinning mathematical equations, for example, the fact that curl of a gradient must vanish.