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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/16393
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dc.contributor.advisorKevlahan, Nicholas K.-R.-
dc.contributor.authorAechtner, Matthias-
dc.date.accessioned2014-11-17T20:54:19Z-
dc.date.available2014-11-17T20:54:19Z-
dc.date.issued2014-
dc.identifier.urihttp://hdl.handle.net/11375/16393-
dc.description.abstractIn this thesis the development of a dynamically adaptive wavelet method for geophysical applications is described. Being targeted at geophysical applications, a discrete shallow water model is derived in a way to retain mimetic properties of the continuous setting. Based on an investigation of properties of second generation wavelets, wavelet transforms for the sphere are designed for height and non-separable velocity that provide conservation of mass and consistent advection of vorticity. The model has been implemented in Fortran-95 with careful choice of data-structure and algorithms with the result that the computational cost per grid point of the adaptive method is only three times as large as for an optimized non-adaptive method. The Message Passing Interface (MPI) has been used to enable the model to run on 100 to 1000 of computer cores with generally high parallel efficiency (above 80%), but depending on the test-case. Standard tests by Williamson (1992) and a more recent test-case by Galewsky (2004) have verified numerical accuracy and convergence of the adaptive method. A simulation of homogeneous shallow water turbulence demonstrates that the model is capable of compression ratios of 20-50 even in a challenging setting. Finally the 2004 tsunami in the Indian ocean is computed as a real application to ocean simulation.en_US
dc.language.isoenen_US
dc.titleAdaptive wavelet modelling of geophysical flows on the sphereen_US
dc.typeThesisen_US
dc.contributor.departmentComputational Engineering and Scienceen_US
dc.description.degreetypeDissertationen_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
Appears in Collections:Open Access Dissertations and Theses

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