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

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


	Document type :	Scientific journals : Article
	Discipline(s) :	Life sciences : Aquatic sciences & oceanology Physical, chemical, mathematical & earth Sciences : Multidisciplinary, general & others
	To cite this reference:	http://hdl.handle.net/2268/4260

Title :	Multigrid state vector for data assimilation in a two-way nested model of the Ligurian Sea
Language :	English
Author, co-author :	Barth, Alexander [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > Océanographie physique >]
	Alvera Azcarate, Aïda [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
	Beckers, Jean-Marie [Université de Liège - ULg > Département d'astrophys.]
	Rixen, Michel [> > > >]
	Vandenbulcke, Luc [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > Département d'astrophys., géophysique et océanographie (AGO) >]
Publication date :	Mar-2007
Journal title :	Journal of Marine Systems
Publisher :	Elsevier Science
Volume :	65
Issue/season :	1-4
Special issue title :	Marine Environmental Monitoring and Prediction
Pages :	41-59
Audience :	International
ISSN :	0924-7963
City :	Amsterdam
Country :	The Netherlands
Keywords :	[en] data assimilation ; two-way nested model ; reduced-rank Kalman filter ; Ligurian Sea
Abstract :	[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 units :	Centre Interfacultaire de Recherches en Océanologie - MARE - GHER
Permalink :	http://hdl.handle.net/2268/4260
DOI :	10.1016/j.jmarsys.2005.07.006

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Restricted access	barth - multigrid DA - JMS2007.pdf	No commentary	Author preprint	2.52 MB	Request copy

All documents in ORBi are protected by a user license.

Dspace v1.5