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Title: A numerical investigation of internal gravity wave phenomena with adaptive mesh techniques
Author: Martin, Benjamin
ISNI:       0000 0004 5354 8336
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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Internal gravity waves in the oceans are a limited scale process capable of providing sufficient energy to activate strong diapycnal mixing near sloping bathymetry. This can account for a significant portion of oceanic vertical mixing. Mixing can be locally intense, transporting colder nutrient-rich bottom water up onto continental margins with implications for coastal marine ecosystems and the carbon cycle. Modelling internal waves is particularly challenging. The strong vertical accelerations present in the overturning and breaking of internal waves necessitates a non-hydrostatic model, and the small-scale processes that result from the interaction of internal waves with bathymetry mean that traditional structured mesh models require high-resolution to adequately capture flow complexity. I present two-dimensional results of numerical simulations of internal waves being generated and interacting with idealised bathymetry, using the Imperial College Ocean Model (Fluidity-ICOM), a non-hydrostatic, finite-element, unstructured mesh model incorporating anisotropic mesh adaptivity. The unstructured nature of Fluidity-ICOM allows the mesh to be optimised to represent complex bathymetries, as well as capturing the vertically inhomogeneous structure of internal waves. Convergence of the model to analytical results has been demonstrated by modelling internal wave propagation in a linearly stratified fluid. Adaptive mesh simulations have been found to adequately capture the dynamics of internal wave breaking at a slope, and the degeneration of interfacial waves into solitary internal waves, with less computational resources than traditional models. However, further work is needed to simulate the internal leewave generation mechanism of flow over topography.
Supervisor: Piggott, Matthew; Pain, Christopher; Allison, Peter Sponsor: Natural Environment Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available