data analysis; oceanography; variational analysis; DIVA
Abstract :
[en] A tool for multidimensional variational analysis (divand) is presented. It allows the interpolation and analysis of observations on curvilinear orthogonal grids in an arbitrary high dimensional space by minimizing a cost function. This cost function penalizes the deviation from the observations, the deviation from a first guess and abruptly varying fields based on a given correlation length (potentially varying in space and time). Additional constraints can be added to this cost function such as an advection constraint which forces the analysed field to align with the ocean current. The method decouples naturally disconnected areas based on topography and topology. This is useful in oceanography where disconnected water masses often have different physical properties. Individual elements of the a priori and a posteriori error covariance matrix can also be computed, in particular expected error variances of the analysis. A multidimensional approach (as opposed to stacking 2-dimensional analysis) has the benefit of providing a smooth analysis in all dimensions, although the computational cost is increased.
Primal (problem solved in the grid space) and dual formulations (problem solved in the observational space) are implemented using either direct solvers (based on Cholesky factorization) or iterative solvers (conjugate gradient method). In most applications the primal formulation with the direct solver is the fastest, especially if an a posteriori error estimate is needed. However, for correlated observation errors the dual formulation with an iterative solver is more efficient.
The method is tested by using pseudo observations from a global model. The distribution of the observations is based on the position of the ARGO floats. The benefit of the 3-dimensional analysis (longitude, latitude and time) compared to 2-dimensional analysis (longitude and latitude) and the role of the advection constraint are highlighted. The tool divand is free software, and is distributed under the terms of the GPL license (http://modb.oce.ulg.ac.be/mediawiki/index.php/divand).
Research Center/Unit :
GHER
Disciplines :
Earth sciences & physical geography
Author, co-author :
Barth, Alexander ; 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., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER)
Alvera Azcarate, Aïda ; Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER)
Vandenbulcke, Luc; University of Porto > CIIMAR
Language :
English
Title :
divand-1.0: n-dimensional variational data analysis for ocean observations
Alternative titles :
[en] divand
Publication date :
2014
Journal title :
Geoscientific Model Development
ISSN :
1991-959X
eISSN :
1991-9603
Publisher :
Copernicus GmbH
Volume :
7
Pages :
225-241
Peer reviewed :
Peer Reviewed verified by ORBi
Tags :
CÉCI : Consortium des Équipements de Calcul Intensif
FP7 - 283607 - SEADATANET II - SeaDataNet II: Pan-European infrastructure for ocean and marine data management
Name of the research project :
PREDANTAR, EMODNET Chemistry 2, SeaDataNet II
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique BELSPO - Service Public Fédéral de Programmation Politique scientifique DG MARE - Commission Européenne. Direction Générale des Affaires maritimes et de la Pêche CE - Commission Européenne
Commentary :
Code available at http://modb.oce.ulg.ac.be/mediawiki/index.php/Divand
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