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Ocean Science An interactive open-access journal of the European Geosciences Union
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Volume 5, issue 4
Ocean Sci., 5, 495–510, 2009
https://doi.org/10.5194/os-5-495-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: The MERSEA Project

Ocean Sci., 5, 495–510, 2009
https://doi.org/10.5194/os-5-495-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

  03 Nov 2009

03 Nov 2009

Application of the Gaussian anamorphosis to assimilation in a 3-D coupled physical-ecosystem model of the North Atlantic with the EnKF: a twin experiment

E. Simon and L. Bertino E. Simon and L. Bertino
  • Nansen Environmental and Remote Sensing Center, Norway

Abstract. We consider the application of the Ensemble Kalman Filter (EnKF) to a coupled ocean ecosystem model (HYCOM-NORWECOM). Such models, especially the ecosystem models, are characterized by strongly non-linear interactions active in ocean blooms and present important difficulties for the use of data assimilation methods based on linear statistical analysis. Besides the non-linearity of the model, one is confronted with the model constraints, the analysis state having to be consistent with the model, especially with respect to the constraints that some of the variables have to be positive. Furthermore the non-Gaussian distributions of the biogeochemical variables break an important assumption of the linear analysis, leading to a loss of optimality of the filter. We present an extension of the EnKF dealing with these difficulties by introducing a non-linear change of variables (anamorphosis function) in order to execute the analysis step in a Gaussian space, namely a space where the distributions of the transformed variables are Gaussian. We present also the initial results of the application of this non-Gaussian extension of the EnKF to the assimilation of simulated chlorophyll surface concentration data in a North Atlantic configuration of the HYCOM-NORWECOM coupled model.

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