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ASSIMILATION OF LAGRANGIAN DATA INTO IDEALIZED MODELS OF THE OCEAN MESOSCALE USING ENSEMBLE-BASED METHODS

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dc.contributor.author Jacobs, Muhammad-Kassiem
dc.date.accessioned 2010-09-09T18:57:25Z
dc.date.available 2010-09-09T18:57:25Z
dc.date.issued 2010-09-09
dc.identifier.uri http://hdl.handle.net/10222/13056
dc.description MSc Thesis en_US
dc.description.abstract It is generally accepted that models of the deep ocean must assimilate observations in order to make realistic forecasts in regions dominated by mesoscale variability (i.e., “ocean weather”). The present study is an attempt to quantify the information on ocean weather that is contained in Lagrangian trajectories, and the best way to extract it. Following a review of ocean data assimilation in a Bayesian framework, including the Ensemble Kalman Filter and the Particle Filter, a new class of idealized models of self advecting vortices is introduced. Through a large number of carefully designed Monte Carlo experiments it is shown when, where and why the Ensemble Kalman Filter will fail. The study concludes with a discussion of a hybrid scheme that takes advantage of the lower computational cost of the Ensemble Kalman Filter and the ability of the Particle Filter to handle highly non-Gaussian probability density functions. en_US
dc.language.iso en en_US
dc.subject Assimilation, Lagrangian, Ensemble en_US
dc.title ASSIMILATION OF LAGRANGIAN DATA INTO IDEALIZED MODELS OF THE OCEAN MESOSCALE USING ENSEMBLE-BASED METHODS en_US
dc.date.defence 2010-08-27
dc.contributor.department Department of Oceanography en_US
dc.contributor.degree Master of Science en_US
dc.contributor.external-examiner Michael Dowd en_US
dc.contributor.graduate-coordinator Dan Kelley en_US
dc.contributor.thesis-reader Allyn Clarke en_US
dc.contributor.thesis-reader Barry Ruddick en_US
dc.contributor.thesis-reader Bruce Smith en_US
dc.contributor.thesis-reader Michael Dowd en_US
dc.contributor.thesis-reader Keith Thompson en_US
dc.contributor.thesis-supervisor Keith Thompson en_US
dc.contributor.ethics-approval Not Applicable en_US
dc.contributor.manuscripts Not Applicable en_US
dc.contributor.copyright-release Not Applicable en_US


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