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

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

doi:https://doi.org/10.5194/ascmo-2-171-2016

Articles | Volume 2, issue 2

https://doi.org/10.5194/ascmo-2-171-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Hierarchical and exploratory statistical methods for ocean...

https://doi.org/10.5194/ascmo-2-171-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 2, issue 2

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

Data sets

UCSC CCS 1/10 degree 13-Year Ocean Model Historical Reanalysis Version 0.1 A. M. Moore, C. A. Edwards, H. Arango, E. Neveu, F. Fiechter, and P. Drake http://oceanmodeling.ucsc.edu/reanalccs13

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.