An ensemble framework for time delay synchronization
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da Produção Científica da Marinha do Brasil (RI-MB) |
Texto Completo: | http://www.repositorio.mar.mil.br/handle/ripcmb/844607 |
Resumo: | Synchronization based state estimation tries to synchronize a model with the true evolution of a system via the observations. In practice, an extra term is added to the model equations which hampers growth of instabilities transversal to the synchronization manifold. Therefore, there is a very close connection between synchronization and data assimilation. Recently, synchronization with time-delayed observations has been proposed, in which observations at future times are used to help synchronize a system that does not synchronize using only present observations, with remarkable successes. Unfortunately, these schemes are limited to small-dimensional problems. In this article, we lift that restriction by proposing an ensemble-based synchronization scheme. Tests were performed using the Lorenz’96 model for 20-, 100- and 1000-dimension systems. Results show global synchronization errors stabilizing at values of at least an order of magnitude lower than the observation errors, suggesting that the scheme is a promising tool to steer model states to the truth. While this framework is not a complete data assimilation method, we develop this methodology as a potential choice for a proposal density in a more comprehensive data assimilation method, like a fully nonlinear particle filter. |
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Pinheiro, Flávia R.Leeuwen, Peter Jan vanParlitz, Ulrich2020-04-14T18:19:54Z2020-04-14T18:19:54Z2018-01http://www.repositorio.mar.mil.br/handle/ripcmb/844607Synchronization based state estimation tries to synchronize a model with the true evolution of a system via the observations. In practice, an extra term is added to the model equations which hampers growth of instabilities transversal to the synchronization manifold. Therefore, there is a very close connection between synchronization and data assimilation. Recently, synchronization with time-delayed observations has been proposed, in which observations at future times are used to help synchronize a system that does not synchronize using only present observations, with remarkable successes. Unfortunately, these schemes are limited to small-dimensional problems. In this article, we lift that restriction by proposing an ensemble-based synchronization scheme. Tests were performed using the Lorenz’96 model for 20-, 100- and 1000-dimension systems. Results show global synchronization errors stabilizing at values of at least an order of magnitude lower than the observation errors, suggesting that the scheme is a promising tool to steer model states to the truth. While this framework is not a complete data assimilation method, we develop this methodology as a potential choice for a proposal density in a more comprehensive data assimilation method, like a fully nonlinear particle filter.engUniversity od ReadingSincronizationData AssimilationEnsembleAn ensemble framework for time delay synchronizationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleInglaterrainfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Produção Científica da Marinha do Brasil (RI-MB)instname:Marinha do Brasil (MB)instacron:MBTEXTCC_FLAVIA_artigo.pdf.txtCC_FLAVIA_artigo.pdf.txtExtracted texttext/plain55671https://www.repositorio.mar.mil.br/bitstream/ripcmb/844607/2/CC_FLAVIA_artigo.pdf.txt423f91384fdc29b4e447a5f548fc7d9dMD52THUMBNAILCC_FLAVIA_artigo.pdf.jpgCC_FLAVIA_artigo.pdf.jpgGenerated Thumbnailimage/jpeg1628https://www.repositorio.mar.mil.br/bitstream/ripcmb/844607/3/CC_FLAVIA_artigo.pdf.jpg3e09f98332c9ffd99d1a4b2310e3fc6fMD53ORIGINALCC_FLAVIA_artigo.pdfCC_FLAVIA_artigo.pdfapplication/pdf13342321https://www.repositorio.mar.mil.br/bitstream/ripcmb/844607/1/CC_FLAVIA_artigo.pdf30f5fadc2193c388b86539f03e665952MD51ripcmb/8446072022-09-22 15:30:25.259oai:www.repositorio.mar.mil.br:ripcmb/844607Repositório InstitucionalPUBhttps://www.repositorio.mar.mil.br/oai/requestdphdm.repositorio@marinha.mil.bropendoar:2022-09-22T18:30:25Repositório Institucional da Produção Científica da Marinha do Brasil (RI-MB) - Marinha do Brasil (MB)false |
dc.title.pt_BR.fl_str_mv |
An ensemble framework for time delay synchronization |
title |
An ensemble framework for time delay synchronization |
spellingShingle |
An ensemble framework for time delay synchronization Pinheiro, Flávia R. Sincronization Data Assimilation Ensemble |
title_short |
An ensemble framework for time delay synchronization |
title_full |
An ensemble framework for time delay synchronization |
title_fullStr |
An ensemble framework for time delay synchronization |
title_full_unstemmed |
An ensemble framework for time delay synchronization |
title_sort |
An ensemble framework for time delay synchronization |
author |
Pinheiro, Flávia R. |
author_facet |
Pinheiro, Flávia R. Leeuwen, Peter Jan van Parlitz, Ulrich |
author_role |
author |
author2 |
Leeuwen, Peter Jan van Parlitz, Ulrich |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Pinheiro, Flávia R. Leeuwen, Peter Jan van Parlitz, Ulrich |
dc.subject.por.fl_str_mv |
Sincronization Data Assimilation Ensemble |
topic |
Sincronization Data Assimilation Ensemble |
description |
Synchronization based state estimation tries to synchronize a model with the true evolution of a system via the observations. In practice, an extra term is added to the model equations which hampers growth of instabilities transversal to the synchronization manifold. Therefore, there is a very close connection between synchronization and data assimilation. Recently, synchronization with time-delayed observations has been proposed, in which observations at future times are used to help synchronize a system that does not synchronize using only present observations, with remarkable successes. Unfortunately, these schemes are limited to small-dimensional problems. In this article, we lift that restriction by proposing an ensemble-based synchronization scheme. Tests were performed using the Lorenz’96 model for 20-, 100- and 1000-dimension systems. Results show global synchronization errors stabilizing at values of at least an order of magnitude lower than the observation errors, suggesting that the scheme is a promising tool to steer model states to the truth. While this framework is not a complete data assimilation method, we develop this methodology as a potential choice for a proposal density in a more comprehensive data assimilation method, like a fully nonlinear particle filter. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018-01 |
dc.date.accessioned.fl_str_mv |
2020-04-14T18:19:54Z |
dc.date.available.fl_str_mv |
2020-04-14T18:19:54Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.repositorio.mar.mil.br/handle/ripcmb/844607 |
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http://www.repositorio.mar.mil.br/handle/ripcmb/844607 |
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eng |
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eng |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.publisher.none.fl_str_mv |
University od Reading |
publisher.none.fl_str_mv |
University od Reading |
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