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Non-synoptic versus pseudo-synoptic data sets: an assimilation experiment

Non-synoptic versus pseudo-synoptic data sets: an assimilation experiment
Non-synoptic versus pseudo-synoptic data sets: an assimilation experiment
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.
SYNOPTIC SAMPLING, DENSITY, VERTICAL VELOCITY, DATA ASSIMILATION
0924-7963
313-333
Rixen, M.
e15b7917-e295-4ba7-a825-a7680cf5a0f8
Allen, J.T.
b251a62b-f443-4591-b695-9aa8c4d73741
Beckers, J-M.
e91ff44d-d233-43fd-aeae-120636c52884
Rixen, M.
e15b7917-e295-4ba7-a825-a7680cf5a0f8
Allen, J.T.
b251a62b-f443-4591-b695-9aa8c4d73741
Beckers, J-M.
e91ff44d-d233-43fd-aeae-120636c52884

Rixen, M., Allen, J.T. and Beckers, J-M. (2001) Non-synoptic versus pseudo-synoptic data sets: an assimilation experiment. Journal of Marine Systems, 29 (1/4), 313-333. (doi:10.1016/S0924-7963(01)00022-7).

Record type: Article

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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More information

Published date: 2001
Keywords: SYNOPTIC SAMPLING, DENSITY, VERTICAL VELOCITY, DATA ASSIMILATION

Identifiers

Local EPrints ID: 7950
URI: http://eprints.soton.ac.uk/id/eprint/7950
ISSN: 0924-7963
PURE UUID: 5f7af560-3294-4d75-bac9-55e4f5b22af4

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Date deposited: 10 Aug 2004
Last modified: 15 Mar 2024 04:50

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Contributors

Author: M. Rixen
Author: J.T. Allen
Author: J-M. Beckers

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