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Assimilation of glider and mooring data into a coastal ocean model


Jones, EM and Oke, PR and Rizwi, F and Murray, LM, Assimilation of glider and mooring data into a coastal ocean model, Ocean Modelling, 47 pp. 1-13. ISSN 1463-5003 (2012) [Refereed Article]

Copyright Statement

Crown Copyright 2012 Published by Elsevier Ltd

DOI: doi:10.1016/j.ocemod.2011.12.009


We have applied an ensemble optimal interpolation (EnOI) data assimilation system to a high resolution coastal ocean model of south-east Tasmania, Australia. The region is characterised by a complex coastline with water masses influenced by riverine input and the interaction between two offshore current systems. Using a large static ensemble to estimate the systems background error covariance, data from a coastal observing network of fixed moorings and a Slocum glider are assimilated into the model at daily intervals. We demonstrate that the EnOI algorithm can successfully correct a biased high resolution coastal model. In areas with dense observations, the assimilation scheme reduces the RMS difference between the model and independent GHRSST observations by 90%, while the domain-wide RMS difference is reduced by a more modest 40%. Our findings show that errors introduced by surface forcing and boundary conditions can be identified and reduced by a relatively sparse observing array using an inexpensive ensemble-based data assimilation system.

Item Details

Item Type:Refereed Article
Keywords:data assimilation, coastal ocean modelling, Tasmania, gliders, SHOC
Research Division:Earth Sciences
Research Group:Oceanography
Research Field:Physical oceanography
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the environmental sciences
UTAS Author:Oke, PR (Dr Peter Oke)
ID Code:119739
Year Published:2012
Web of Science® Times Cited:33
Deposited By:Oceans and Cryosphere
Deposited On:2017-08-04
Last Modified:2017-09-29

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