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On the variational data assimilation problem solving and sensitivity analysis

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Title: On the variational data assimilation problem solving and sensitivity analysis
Authors: Arcucci, R
D'Amore, L
Pistoia, J
Toumi, R
Murli, A
Item Type: Journal Article
Abstract: We consider the Variational Data Assimilation (VarDA) problem in an operational framework, namely, as it results when it is employed for the analysis of temperature and salinity variations of data collected in closed and semi closed seas. We present a computing approach to solve the main computational kernel at the heart of the VarDA problem, which outperforms the technique nowadays employed by the oceanographic operative software. The new approach is obtained by means of Tikhonov regularization. We provide the sensitivity analysis of this approach and we also study its performance in terms of the accuracy gain on the computed solution. We provide validations on two realistic oceanographic data sets.
Issue Date: 24-Jan-2017
Date of Acceptance: 18-Jan-2017
URI: http://hdl.handle.net/10044/1/48367
DOI: https://dx.doi.org/10.1016/j.jcp.2017.01.034
ISSN: 0021-9991
Publisher: ELSEVIER
Start Page: 311
End Page: 326
Journal / Book Title: JOURNAL OF COMPUTATIONAL PHYSICS
Volume: 335
Copyright Statement: © 2017 Elsevier Inc. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords: Science & Technology
Technology
Physical Sciences
Computer Science, Interdisciplinary Applications
Physics, Mathematical
Computer Science
Physics
Data Assimilation
Sensitivity analysis
Inverse Problem
LAPLACE TRANSFORM INVERSION
COVARIANCE MATRICES
CONDITION NUMBER
REGULARIZATION
IMPLEMENTATION
Applied Mathematics
01 Mathematical Sciences
02 Physical Sciences
09 Engineering
Publication Status: Published
Appears in Collections:Space and Atmospheric Physics
Physics
Faculty of Natural Sciences



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