Internal Solitary Waves in Ice-Covered Waters

": Internal solitary waves (ISWs) propagate along density interfaces within stably- stratified fluids. They are ubiquitous in the ocean and their properties are influenced strongly by the nature and form of the upper and lower bounding surfaces of the containing basin(s) in which they propagate. As the Arctic Ocean evolves to a seasonally more ice-free state, the ISW field will be affected by the change. The relationship between ISW dynamics and ice is important in understanding
(i) the general circulation and thermodynamics in the Arctic Ocean, (ii) local mixing processes that supply heat and nutrients from depth into upper layers, (iii) how tidal energy is dissipated in the Arctic Ocean, (iv) flexure of sea-ice and (v) formation of ice bands in the marginal ice zone. There is clear interplay between ISWs and sea ice and motivation to study the topic is wide ranging yet very few dedicated investigations exist. The effect of diminishing sea ice cover on the ISW field (and vice versa) is not well established. A better understanding of ISW dynamics in the Arctic Ocean and, in particular, how the ISW field is affected by changes in both ice cover and stratification, is central in understanding how the rapidly changing Arctic will adapt to climate change.

In this PhD research project, the fluid dynamics of ISWs propagating under varying surface conditions will be studied through laboratory experiments. The PhD student will be trained in the generation, visualisation and measurement of ISWs in a new purpose-built wave flume at Newcastle University. In addition, there will be opportunities for the candidate to undertake (i) numerical simulation of the flow (in collaboration with Prof D G Dritschel, St Andrews University) and/or (ii) field work in the Arctic (in collaboration with Prof Tom Rippeth, Bangor University). The student will gain valuable skills in experimental fluid dynamics including flow visualisation and measurement via Particle Image Velocimetry, micro-conductivity sensors and time series analysis. They will also have the opportunity to broaden their training into areas of numerical analysis (using contour advection and pseudo spectral techniques) and field work; giving them a broad skill set and training across disciplines.
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