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Professional biography

I've been a lecturer at The Open University since 1st October 2014. Before that I was a postdoctoral researcher at the University of Bristol, and before that I did a PhD in particle physics and an undergraduate physics degree at the University of Manchester.



Research interests

I'm interested in quantifying the uncertainties for our models of the earth system. Since moving into climate science I've done climate modelling (perturbed parameter ensembles with the Met Office Hadley Centre model HadCM3), experimental design and analysis for future sea level projections (Bayesian calibration), and dabbled in vegetation and ice sheet modelling. I've also reviewed and recommended best practice in uncertainty assessment and communication in various areas of earth system science, particularly climate and extreme weather. For example, I wrote two chapters of this book on risk and uncertainty assessment for natural hazards.

Here is my publication list.

Impact and engagement

I do quite a lot of public engagement. Here is a TEDx CERN talk, and here are some news interviews including Newsnight.

Research Activity

Externally funded projects

Quantifying Uncertainty in ANTarctic Ice Sheet instability

RoleStart dateEnd dateFunding source
Lead01/Aug/201531/Jan/2016University of Exeter
Large parts of the Antarctic ice sheet lie on bedrock below sea level and may be vulnerable to a positive feedback known as Marine Ice Sheet Instability (MISI), a self-sustaining retreat of the grounding line triggered by oceanic or atmospheric changes. There is growing evidence MISI may be underway throughout the Amundsen Sea Embayment (ASE) of West Antarctica. If this is sustained the region could contribute up to 1-2 m to global mean sea level, and if triggered in other areas the potential contribution to sea level on centennial to millennial timescales could be two to three times greater. However, physically plausible projections of Antarctic MISI are challenging: numerical ice sheet models are either too low in spatial resolution to explicitly resolve grounding line processes or else too computationally expensive to assess modeling uncertainties. The proposed work brings together and analyses two new datasets that complement each other in model complexity – a large ensemble generated with a low resolution model, and a small ensemble from a high resolution model – by constructing a new emulator of the relationship between them.