Multigrid state vector for data assimilation in a two-way nested model of the Ligurian Sea

[en] A system of two nested models composed by a coarse resolution model of the Mediterranean Sea, an intermediate resolution model of the Provencal Basin and a high resolution model of the Ligurian Sea is coupled with a Kalman-filter based assimilation method. The state vector for the data assimilation is composed by the temperature, salinity and elevation of the three models. The forecast error is estimated by an ensemble run of 200 members by perturbing initial condition and atmospheric forcings. The 50 dominant empirical orthogonal functions (EOF) are taken as the error covariance of the model forecast. This error covariance is assumed to be constant in time. Sea surface temperature (SST) and sea surface height (SSH) are assimilated in this system. (c) 2006 Elsevier B.V. All rights reserved.

Research Center/Unit :

Centre Interfacultaire de Recherches en Océanologie - MARE - GHER

Disciplines :

Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others
Aquatic sciences & oceanology

Author, co-author :

Barth, Alexander ; Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Océanographie physique

Alvera Azcarate, Aïda ; Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER)

Beckers, Jean-Marie ; Université de Liège - ULiège > Département d'astrophys.

Rixen, Michel

Vandenbulcke, Luc ; Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Département d'astrophys., géophysique et océanographie (AGO)

Language :

English

Title :

Multigrid state vector for data assimilation in a two-way nested model of the Ligurian Sea

Publication date :

March 2007

Journal title :

Journal of Marine Systems

ISSN :

0924-7963

Publisher :

Elsevier Science, Amsterdam, Netherlands

Special issue title :

Marine Environmental Monitoring and Prediction

Volume :

Issue :

1-4

Pages :

41-59

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 16 January 2009

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Bibliography

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