Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.643415
Title: A dynamical method for assimilation of altimeter data into ocean models
Author: Cooper, Michael
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 1995
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Abstract:
A method is developed here for the assimilation of surface restricted satellite data into three dimensional numerical ocean models. Satellite altimetry provides observations of the dynamic topography i.e. the time variations in sea surface height, which provides some constraints on the three dimensional ocean state, but no unique solution. Traditionally, the surface data is projected into the deeper ocean by statistical methods. Here, the pre-analysis model potential vorticity fields are conserved at each analysis, which provides a unique solution for the vertical structure of each model gridpoint when combined with the local sea surface height. The assimilation method is tested in a series of twin experiments, in which the real ocean is substituted by a numerical model run, and limited datasets from this control run are assimilated into another model run with different initial conditions in an attempt to reconstruct the full three-dimensional state of the control run from the surface information alone. The assimilation run fields are then compared with the full control fields in order to determine the success of the assimilation method. Twin experiments with a four layer quasigeostrophic model, and a 21 level primitive equation model show that the typical amount of information available from a single altimeter is sufficient to constrain the full three-dimensional circulation of the ocean model, within the twin experiment framework. The reliance upon dynamically-based conservation laws rather than pre-calculated statistics makes the method computationally cheap and easily portable between models.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.643415  DOI: Not available
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