Hybridisation of data assimilation methods for applications in oceanography

International audience A data assimilation method based on variational approach is presented. The novelty of the hybrid method consists in a coupling of the cost function of the variational approach with an optimal linear smoother issued from the singular evolutive extended Kalman filter (SEEK). The...

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Main Authors: Krysta, Monika, Blayo, Eric, Cosme, Emmanuel, Robert, Céline, Verron, Jacques, Vidard, Arthur
Other Authors: Modelling, Observations, Identification for Environmental Sciences (MOISE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Écoulements Géophysiques et Industriels Grenoble (LEGI), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), American Geophysical Union
Format: Conference Object
Language:English
Published: HAL CCSD 2008
Subjects:
Online Access:https://inria.hal.science/inria-00344502
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spelling ftunivrennes1hal:oai:HAL:inria-00344502v1 2024-04-28T08:30:46+00:00 Hybridisation of data assimilation methods for applications in oceanography Krysta, Monika Blayo, Eric Cosme, Emmanuel Robert, Céline Verron, Jacques Vidard, Arthur Modelling, Observations, Identification for Environmental Sciences (MOISE) Inria Grenoble - Rhône-Alpes Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK) Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS) Laboratoire des Écoulements Géophysiques et Industriels Grenoble (LEGI) Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS) American Geophysical Union Orlando, United States 2008-03-02 https://inria.hal.science/inria-00344502 en eng HAL CCSD inria-00344502 https://inria.hal.science/inria-00344502 2008 Ocean Sciences Meeting https://inria.hal.science/inria-00344502 2008 Ocean Sciences Meeting, American Geophysical Union, Mar 2008, Orlando, United States [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP] [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] info:eu-repo/semantics/conferenceObject Conference papers 2008 ftunivrennes1hal 2024-04-10T23:57:58Z International audience A data assimilation method based on variational approach is presented. The novelty of the hybrid method consists in a coupling of the cost function of the variational approach with an optimal linear smoother issued from the singular evolutive extended Kalman filter (SEEK). The background error covariance matrix of the usual variational framework remains unchanged. In the hybrid method, however, at each transition between the assimilation windows, it is replaced with the one provided by the smoother. The latter is updated whenever new background states are produced. It can be shown that the background states issued from an appropriately constructed variational framework and some particular optimal linear smoother are mathematically equivalent. Hence the matrix injection into the cost function is done in a consistent manner. The hybrid method has been implemented in a shallow water model which mimics a double-gyre circulation in the North Atlantic. Realistic OSSEs have been performed. Comparisons illustrate superiority of the 4D-Var-smoother hybrid over an ordinary 4D-Var on the one hand and on the other over the 4D-Var-filter hybrid. Conference Object North Atlantic Université de Rennes 1: Publications scientifiques (HAL)
institution Open Polar
collection Université de Rennes 1: Publications scientifiques (HAL)
op_collection_id ftunivrennes1hal
language English
topic [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]
[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]
spellingShingle [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]
[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]
Krysta, Monika
Blayo, Eric
Cosme, Emmanuel
Robert, Céline
Verron, Jacques
Vidard, Arthur
Hybridisation of data assimilation methods for applications in oceanography
topic_facet [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]
[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]
description International audience A data assimilation method based on variational approach is presented. The novelty of the hybrid method consists in a coupling of the cost function of the variational approach with an optimal linear smoother issued from the singular evolutive extended Kalman filter (SEEK). The background error covariance matrix of the usual variational framework remains unchanged. In the hybrid method, however, at each transition between the assimilation windows, it is replaced with the one provided by the smoother. The latter is updated whenever new background states are produced. It can be shown that the background states issued from an appropriately constructed variational framework and some particular optimal linear smoother are mathematically equivalent. Hence the matrix injection into the cost function is done in a consistent manner. The hybrid method has been implemented in a shallow water model which mimics a double-gyre circulation in the North Atlantic. Realistic OSSEs have been performed. Comparisons illustrate superiority of the 4D-Var-smoother hybrid over an ordinary 4D-Var on the one hand and on the other over the 4D-Var-filter hybrid.
author2 Modelling, Observations, Identification for Environmental Sciences (MOISE)
Inria Grenoble - Rhône-Alpes
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK)
Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)
Laboratoire des Écoulements Géophysiques et Industriels Grenoble (LEGI)
Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)
American Geophysical Union
format Conference Object
author Krysta, Monika
Blayo, Eric
Cosme, Emmanuel
Robert, Céline
Verron, Jacques
Vidard, Arthur
author_facet Krysta, Monika
Blayo, Eric
Cosme, Emmanuel
Robert, Céline
Verron, Jacques
Vidard, Arthur
author_sort Krysta, Monika
title Hybridisation of data assimilation methods for applications in oceanography
title_short Hybridisation of data assimilation methods for applications in oceanography
title_full Hybridisation of data assimilation methods for applications in oceanography
title_fullStr Hybridisation of data assimilation methods for applications in oceanography
title_full_unstemmed Hybridisation of data assimilation methods for applications in oceanography
title_sort hybridisation of data assimilation methods for applications in oceanography
publisher HAL CCSD
publishDate 2008
url https://inria.hal.science/inria-00344502
op_coverage Orlando, United States
genre North Atlantic
genre_facet North Atlantic
op_source 2008 Ocean Sciences Meeting
https://inria.hal.science/inria-00344502
2008 Ocean Sciences Meeting, American Geophysical Union, Mar 2008, Orlando, United States
op_relation inria-00344502
https://inria.hal.science/inria-00344502
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