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Ensemble data assimilation applied to an adaptive mesh ocean model

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Title: Ensemble data assimilation applied to an adaptive mesh ocean model
Authors: Du, J
Zhu, J
Fang, F
Pain, C
Navon, I
Item Type: Journal Article
Abstract: In this study, a first attempt has been made to introduce mesh adaptivity into the ensemble Kalman fiter (EnKF) method. The EnKF data assimilation system was established for an unstructured adaptive mesh ocean model (Fluidity, Imperial College London). The mesh adaptivity involved using high resolution mesh at the regions of large flow gradients and around the observation points in order to reduce the representativeness errors of the observations. The use of adaptive meshes unavoidably introduces difficulties in the implementation of EnKF. The ensembles are defined at different meshes. To overcome the difficulties, a supermesh technique is employed for generating a reference mesh. The ensembles are then interpolated from their own mesh onto the reference mesh. The performance of the new EnKF data assimilation system has been tested in the Munk gyre flow test case. The discussion of this paper will focus on (a) the development of the EnKF data assimilation system within an adaptive mesh model and (b) the advantages of mesh adaptivity in the ocean data assimilation model.
Issue Date: 25-May-2016
Date of Acceptance: 21-Apr-2016
URI: http://hdl.handle.net/10044/1/38918
DOI: https://dx.doi.org/10.1002/fld.4247
ISSN: 0271-2091
Publisher: Wiley
Start Page: 997
End Page: 1009
Journal / Book Title: International Journal for Numerical Methods in Fluids
Volume: 82
Issue: 12
Copyright Statement: © 2016 John Wiley & Sons, Ltd. This is the accepted version of the following article: Du, J., Zhu, J., Fang, F., Pain, C. C., and Navon, I. M. (2016) Ensemble data assimilation applied to an adaptive mesh ocean model. Int. J. Numer. Meth. Fluids, which has been published in final form at http://dx.doi.org/10.1002/fld.4247.
Sponsor/Funder: Natural Environment Research Council (NERC)
Engineering & Physical Science Research Council (E
Funder's Grant Number: NE/J015938/1
RG80519
Keywords: Science & Technology
Technology
Physical Sciences
Computer Science, Interdisciplinary Applications
Mathematics, Interdisciplinary Applications
Mechanics
Physics, Fluids & Plasmas
Computer Science
Mathematics
Physics
adaptive mesh
supermesh
EnKF
data assimilation
conservative interpolation
ocean modelling
QUASI-GEOSTROPHIC MODEL
KALMAN FILTER
OPTIMIZATION
EQUATION
REGION
POD
01 Mathematical Sciences
02 Physical Sciences
09 Engineering
Applied Mathematics
Publication Status: Published
Appears in Collections:Faculty of Engineering
Earth Science and Engineering



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