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Non-syntopic versus pseudo-syntopic data sets: an assimilation experiment
Rixen, M.; Allen, J.T.; Beckers, J.-M. (2001). Non-syntopic versus pseudo-syntopic data sets: an assimilation experiment, in: Poulain, P.M. et al. (Ed.) Three-Dimensional Ocean Circulation: Lagrangian Measurements and Diagnostic Analyses. Selected papers from the 31st International Liège Colloquium on Ocean Hydrodynamics, held in Liège, Belgium on May 3-7, 1999. Journal of Marine Systems, 29(1-4): pp. 313-333. dx.doi.org/10.1016/S0924-7963(01)00022-7
In: Poulain, P.M.; Beckers, J.-M. (Ed.) (2001). Three-Dimensional Ocean Circulation: Lagrangian Measurements and Diagnostic Analyses. Selected papers from the 31st International Liège Colloquium on Ocean Hydrodynamics, held in Liège, Belgium on May 3-7, 1999. Journal of Marine Systems, 29(1-4). Elsevier: Liège. 1-426 pp., more
In: Journal of Marine Systems. Elsevier: Tokyo; Oxford; New York; Amsterdam. ISSN 0924-7963, more
Peer reviewed article  

Available in Authors 
    VLIZ: Open Repository 237444 [ OMA ]

Keyword
    Marine
Author keywords
    non-synoptic data sets; pseudo-synoptic data sets; assimilation

Authors  Top 
  • Rixen, M., more
  • Allen, J.T.
  • Beckers, J.-M., more

Abstract
    Several first-order correction methods are implemented to compute pseudo-synoptic data sets from non-synoptic raw data sets. These include a geostrophic relocation method, a linear and a quadratic interpolation method, and a method using spatio-temporal correlation functions. The relocation method involves analyses and geostrophic velocity computations to allow the relocation of stations in time and space to a particular analysis time. Interpolation methods involve several almost identical and consecutive surveys interpolated in time. Temporal weighting methods are based upon a spatio-temporal function modifying the weight on data with respect to the time at which they have been sampled. These techniques are tested on the OMEGA data set and are validated by simple nudging assimilation into a 3D primitive equation model (PE). It is shown that, under certain hypothesis, these methods are able to correct the lack of synopticity in hydrographic data sets, and improve the diagnosis of vertical velocities computed from the Omega equation.These methods are of particular interest for the scientific community. They might be used together with diagnostic models. They might provide suitable pseudo-synoptic fields required by 3D PE models as initial conditions, boundary conditions or assimilation data sets. They may also be useful in the design of mesoscale samplings.

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