Articles | Volume 2, issue 2
https://doi.org/10.5194/ascmo-2-171-2016
https://doi.org/10.5194/ascmo-2-171-2016
14 Dec 2016
 | 14 Dec 2016

Weak constraint four-dimensional variational data assimilation in a model of the California Current System

William J. Crawford, Polly J. Smith, Ralph F. Milliff, Jerome Fiechter, Christopher K. Wikle, Christopher A. Edwards, and Andrew M. Moore

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Cited articles

Bennett, A.: Inverse Modeling of the Ocean and Atmosphere, Cambridge University Press, 2002.
Broquet, G., Edwards, C., Moore, A., Powell, B., Veneziani, M., and Doyle, J.: Application of 4D-variational data assimilation to the California Current System, Dyn. Atmos. Oceans, 48, 69–91, 2009a.
Broquet, G., Moore, A., Arango, H., Edwards, C., and Powell, B.: Ocean state and surface forcing correction using the ROMS-IS4DVAR data assimilation system, Mercator Ocean Quarterly Newsletter, 34, 5–13, 2009b.
Broquet, G., Moore, A., Arango, H., and Edwards, C.: Corrections to ocean surface forcing in the California Current System using 4D-variational data assimilation, Ocean Model., 36, 116–132, 2011.
Carton, J. and Giese, B.: A reanalysis of ocean climate using simple ocean data assimilation (SODA), Mon. Weather Rev., 136, 2999–3017, 2008.
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Short summary
We present a method for estimating intrinsic model error in a model of the California Current System. The estimated model error covariance matrix is used in the weak constraint formulation of the Regional Ocean Modeling System, four-dimensional variational data assimilation system, and comparison of the circulation estimates computed in this way show demonstrable improvement to those computed in the strong constraint formulation, where intrinsic model error is not taken into account.