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Journal of Atmospheric and Oceanic Technology

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Article Type:
Research Article

A Three-Dimensional Variational Data Assimilation Scheme for the Regional Ocean Modeling System

Zhijin LiJet Propulsion Laboratory, California Institute of Technology, Pasadena, California

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Yi ChaoJet Propulsion Laboratory, California Institute of Technology, Pasadena, California

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James C. McWilliamsDepartment of Atmospheric and Oceanic Sciences, Institute of Geophysics and Planetary Physics, University of California, Los Angeles, Los Angeles, California

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Kayo IdeDepartment of Atmospheric and Oceanic Sciences, Institute of Geophysics and Planetary Physics, University of California, Los Angeles, Los Angeles, California

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Print Publication:
01 Nov 2008
DOI:
https://doi.org/10.1175/2008JTECHO594.1
Page(s):
2074–2090
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Abstract

A three-dimensional variational data assimilation (3DVAR) scheme has been developed within the framework of the Regional Ocean Modeling System (ROMS). This ROMS3DVAR enables the capability of predicting meso- to small-scale variations with temporal scales from hours to days in coastal oceans. To cope with particular difficulties that result from complex coastlines and bottom topography, unbalanced flows, and sparse observations, ROMS3DVAR includes novel strategies. These strategies include the implementation of three-dimensional anisotropic and inhomogeneous error correlations based on a Kronecker product, application of particular weak dynamic constraints, and implementation of efficient and reliable algorithms for minimizing the cost function. The formulation of ROMS3DVAR is presented here, and its implementation off the West Coast is currently under way.

Corresponding author address: Zhijin Li, Jet Propulsion Laboratory, M/S 300–323, 4800 Oak Grove Drive, Pasadena, CA 91109. Email: zhijin.li@jpl.nasa.gov

Abstract

A three-dimensional variational data assimilation (3DVAR) scheme has been developed within the framework of the Regional Ocean Modeling System (ROMS). This ROMS3DVAR enables the capability of predicting meso- to small-scale variations with temporal scales from hours to days in coastal oceans. To cope with particular difficulties that result from complex coastlines and bottom topography, unbalanced flows, and sparse observations, ROMS3DVAR includes novel strategies. These strategies include the implementation of three-dimensional anisotropic and inhomogeneous error correlations based on a Kronecker product, application of particular weak dynamic constraints, and implementation of efficient and reliable algorithms for minimizing the cost function. The formulation of ROMS3DVAR is presented here, and its implementation off the West Coast is currently under way.

Corresponding author address: Zhijin Li, Jet Propulsion Laboratory, M/S 300–323, 4800 Oak Grove Drive, Pasadena, CA 91109. Email: zhijin.li@jpl.nasa.gov

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