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Matthew Lewis

CAMS Role: Research Officer

Room: 324 Nautilus

Telephone: 01248 38 8114



My connection with Bangor University began as an undergraduate in Marine Biology/Oceanography. Later I studied here as an MSc student in Applied Physical Oceanography, where I made direct observations of internal waves with Prof. John Simpson. Afterwards, I worked as a modelling technician for NIWA, where I helped develop computational grids (such as the RiCOM computational grid for tidal prediction around New Zealand), as well as running numerous regional 2D and 3D hydrodynamic models, including Lagrangian particle tracking simulations of larval dispersal. I studied for a PhD at Bristol University and the National Oceanographic Centre (Liverpool), investigating the uncertainties within modelling future coastal flood risk; such as the difficulties within coupling future climate predictions from Regional Circulation Models, shelf sea hydrodynamic models, and local-scale inundation models. Here at Bangor University, I am now interested in characterising the natural climate variability within shelf sea models of SWAN (waves) and ROMS (tide), as well as cascading this information into local scale models such as UNIBEST-TC.

Research Interests

I am currently a Sêr Cymru Research Fellow, working on the NRN-LCEE QUOTIENT project. I use computer simulations of earth system processes to understand oceanographic processes, such as waves and tides. I am particularly interests in simulating the interaction of processes; for example the effect of tides on waves, and waves on tides. My research predominantly focuses on marine renewable energy; where best to install marine renewable energy devices, what electricity contributions to the grid would look like when including large amounts of renewable energy development, and what are the likely conditions the industry faces to inform resilient and efficient designs. I am also interest in coastal hazards, such as flood risk and estuarine water quality, and simulating changes to coastal processes in the future (i.e. how to cascade climate model information down to local-scale impact).


Shelf Sea Modelling Group

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