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The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems Part II - Performance and application to the California Current System

Journal

PROGRESS IN OCEANOGRAPHY
Volume 91, Issue 1, Pages 50-73

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pocean.2011.05.003

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Funding

  1. Office of Naval Research [N00014-01-1-0209, N00014-06-1-0406, N00014-08-1-0556, N00014-10-1-0322, 0601153N]
  2. National Science Foundation [OCE-0628690, OCE-0121176, OCE-0121506]
  3. National Ocean Partnership Program [NA05-NOS4731242]

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The Regional Ocean Modeling System (ROMS) 4-dimensional variational (4D-Var) data assimilation systems have been systematically applied to the mesoscale circulation environment of the California Current to demonstrate the performance and practical utility of the various components of ROMS 4D-Var. In particular, we present a comparison of three approaches to 4D-Var, namely: the primal formulation of the incremental strong constraint approach: the dual formulation physical-space statistical analysis system: and the dual formulation indirect representer approach. In agreement with theoretical considerations all three approaches converge to the same ocean circulation estimate when using the same observations and prior information. However, the rate of convergence of the dual formulation was found to be inferior to that of the primal formulation. Other aspects of the 4D-Var performance that relate to the use of multiple outer-loops, preconditioning, and the weak constraint are also explored. A systematic evaluation of the impact of the various components of the 4D-Var control vector (i.e. the initial conditions, surface forcing and open boundary conditions) is also presented. It is shown that correcting for uncertainties in the model initial conditions exerts the largest influence on the ability of the model to fit the available observations. Various important diagnostics of 4D-Var are also examined, including estimates of the posterior error, the information content of the observation array, and innovation-based consistency checks on the prior error assumptions. Using these diagnostic tools, we find that more than 90% of the observations assimilated into the model provide redundant information. This is a symptom of the large percentage of satellite data that are used and to some extent the nature of the data processing employed. This is the second in a series of three papers describing the ROMS 4D-Var systems. (C) 2011 Elsevier Ltd. All rights reserved.

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