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An ensemble framework for time delay synchronization
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993319/ https://www.ncbi.nlm.nih.gov/pubmed/29937591 http://dx.doi.org/10.1002/qj.3204 |
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author | Pinheiro, Flavia R. van Leeuwen, Peter Jan Parlitz, Ulrich |
author_facet | Pinheiro, Flavia R. van Leeuwen, Peter Jan Parlitz, Ulrich |
author_sort | Pinheiro, Flavia R. |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-5993319 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley & Sons, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-59933192018-06-20 An ensemble framework for time delay synchronization Pinheiro, Flavia R. van Leeuwen, Peter Jan Parlitz, Ulrich Q J R Meteorol Soc Research Articles 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. John Wiley & Sons, Ltd 2018-01-15 2018-01 /pmc/articles/PMC5993319/ /pubmed/29937591 http://dx.doi.org/10.1002/qj.3204 Text en © 2017 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Pinheiro, Flavia R. van Leeuwen, Peter Jan Parlitz, Ulrich An ensemble framework for time delay synchronization |
title | 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_short | An ensemble framework for time delay synchronization |
title_sort | ensemble framework for time delay synchronization |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993319/ https://www.ncbi.nlm.nih.gov/pubmed/29937591 http://dx.doi.org/10.1002/qj.3204 |
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