An assessment of independent vs joint data assimilation for a coupled atmosphere-ocean system

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Tuesday, 19 January 2010: 9:15 AM
B207 (GWCC)
Faez Bakalian, Dalhousie University, Halifax, NS, Canada; and H. Ritchie and A. M. Thompson

A simple linear state space model representation of the coupled atmosphere-ocean system has been employed to critically examine the advantages and disadvantages of independent versus joint assimilation. The assimilation was carried out using a linear Kalman filter technique. In independent assimilation, data was assimilated into each of the respective media and the information was communicated between the media only through the coupling terms. In joint assimilation, the data was assimilated into each of the respective media but the information was immediately transferred to the other medium through the Kalman Filter and both media were updated simultaneously at each assimilation stage. Owing to the linearity of the state space model and Kalman filter, analytical solutions were obtained for the background error variances. Significant improvements in forecast skill were observed when joint assimilation was carried out for data confined to one medium only as compared independent assimilation of that data. This research is being conducted to assess assimilation strategies for use in coupled atmosphere-ocean numerical models.