Variational Data Assimilation in Chaotic Regime by Lorenz Model

Detalhes bibliográficos
Autor(a) principal: Härter, Fabrício Pereira
Data de Publicação: 2017
Outros Autores: Yamasaki, Yoshihiro, Beck, Vinícius Carvalho
Tipo de documento: Artigo
Idioma: por
Título da fonte: Anuário do Instituto de Geociências (Online)
Texto Completo: https://revistas.ufrj.br/index.php/aigeo/article/view/7845
Resumo: This paper explores some aspects of data assimilation by 3D-Var method implemented in the Lorenz model. This system was chosen because, although simple, has similar structure to the atmosphere under certain parameters. Conceptual models allow difficult judgments to be made in primitive equation models with their various nonlinear interactions at various scales. It is shown the need to apply data assimilation techniques in highly sensitive models to initial conditions. It was also shown that 3D-Var method is very dependent on the number of cycles during the process of minimizing of the cost function. In the experiment performed on this work was found that at least 1,000 interactions are necessary to solve this minimization problem. However the technique fail to 40% noise added to initial conditions, comparing to control. Additional experiments show the difficulty of performing high quality data assimilation in chaotic dynamics for underdetermined systems, such as the Earth's atmosphere.
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spelling Variational Data Assimilation in Chaotic Regime by Lorenz ModelAssimilação de Dados Via Método 3D-Var em Dinâmica Caótica do Modelo de LorenzData Assimilation; 3D-Var; LorenzAssimilação de Dados; Variacional; LorenzThis paper explores some aspects of data assimilation by 3D-Var method implemented in the Lorenz model. This system was chosen because, although simple, has similar structure to the atmosphere under certain parameters. Conceptual models allow difficult judgments to be made in primitive equation models with their various nonlinear interactions at various scales. It is shown the need to apply data assimilation techniques in highly sensitive models to initial conditions. It was also shown that 3D-Var method is very dependent on the number of cycles during the process of minimizing of the cost function. In the experiment performed on this work was found that at least 1,000 interactions are necessary to solve this minimization problem. However the technique fail to 40% noise added to initial conditions, comparing to control. Additional experiments show the difficulty of performing high quality data assimilation in chaotic dynamics for underdetermined systems, such as the Earth's atmosphere.Neste trabalho investiga-se a assimilação de dados pelo método 3D-Var no modelo de Lorenz. Este modelo foi escolhido, porque representa os diferentes modos do escoamento da atmosfera definidos em função de determinados parâmetros. Modelos simplificados, permitem avaliações do comportamento do escoamento atmosférico mais dispendiosas de serem realizadas em modelos de equações primitivas, com suas varias interações não lineares em diversas escalas. O trabalho indica a necessidade de aplicar técnicas de assimilação de dados em modelos altamente sensíveis às condições inicias. Mostra-se que o método 3D-Var é bastante dependente do número de ciclos durante processo de minimização da função custo. São necessárias no mínimo 1.000 interações para que a técnica seja eficiente. Todavia, esta estratégia falha para condições iniciais acima de determinado grau de ruído, no caso avaliado, 40%. Mostrou-se também, a dificuldade de se realizar assimilação de dados quando os graus de liberdade do modelo são muitos maiores que o número de observações a serem assimiladas.Universidade Federal do Rio de Janeiro2017-02-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufrj.br/index.php/aigeo/article/view/784510.11137/2015_1_73_80Anuário do Instituto de Geociências; Vol 38, No 1 (2015); 73-80Anuário do Instituto de Geociências; Vol 38, No 1 (2015); 73-801982-39080101-9759reponame:Anuário do Instituto de Geociências (Online)instname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJporhttps://revistas.ufrj.br/index.php/aigeo/article/view/7845/6326Copyright (c) 2016 Anuário do Instituto de Geociênciashttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessHärter, Fabrício PereiraYamasaki, YoshihiroBeck, Vinícius Carvalho2017-02-15T17:59:16Zoai:www.revistas.ufrj.br:article/7845Revistahttps://revistas.ufrj.br/index.php/aigeo/indexPUBhttps://revistas.ufrj.br/index.php/aigeo/oaianuario@igeo.ufrj.br||1982-39080101-9759opendoar:2017-02-15T17:59:16Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)false
dc.title.none.fl_str_mv Variational Data Assimilation in Chaotic Regime by Lorenz Model
Assimilação de Dados Via Método 3D-Var em Dinâmica Caótica do Modelo de Lorenz
title Variational Data Assimilation in Chaotic Regime by Lorenz Model
spellingShingle Variational Data Assimilation in Chaotic Regime by Lorenz Model
Härter, Fabrício Pereira
Data Assimilation; 3D-Var; Lorenz
Assimilação de Dados; Variacional; Lorenz
title_short Variational Data Assimilation in Chaotic Regime by Lorenz Model
title_full Variational Data Assimilation in Chaotic Regime by Lorenz Model
title_fullStr Variational Data Assimilation in Chaotic Regime by Lorenz Model
title_full_unstemmed Variational Data Assimilation in Chaotic Regime by Lorenz Model
title_sort Variational Data Assimilation in Chaotic Regime by Lorenz Model
author Härter, Fabrício Pereira
author_facet Härter, Fabrício Pereira
Yamasaki, Yoshihiro
Beck, Vinícius Carvalho
author_role author
author2 Yamasaki, Yoshihiro
Beck, Vinícius Carvalho
author2_role author
author
dc.contributor.author.fl_str_mv Härter, Fabrício Pereira
Yamasaki, Yoshihiro
Beck, Vinícius Carvalho
dc.subject.por.fl_str_mv Data Assimilation; 3D-Var; Lorenz
Assimilação de Dados; Variacional; Lorenz
topic Data Assimilation; 3D-Var; Lorenz
Assimilação de Dados; Variacional; Lorenz
description This paper explores some aspects of data assimilation by 3D-Var method implemented in the Lorenz model. This system was chosen because, although simple, has similar structure to the atmosphere under certain parameters. Conceptual models allow difficult judgments to be made in primitive equation models with their various nonlinear interactions at various scales. It is shown the need to apply data assimilation techniques in highly sensitive models to initial conditions. It was also shown that 3D-Var method is very dependent on the number of cycles during the process of minimizing of the cost function. In the experiment performed on this work was found that at least 1,000 interactions are necessary to solve this minimization problem. However the technique fail to 40% noise added to initial conditions, comparing to control. Additional experiments show the difficulty of performing high quality data assimilation in chaotic dynamics for underdetermined systems, such as the Earth's atmosphere.
publishDate 2017
dc.date.none.fl_str_mv 2017-02-15
dc.type.none.fl_str_mv

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10.11137/2015_1_73_80
url https://revistas.ufrj.br/index.php/aigeo/article/view/7845
identifier_str_mv 10.11137/2015_1_73_80
dc.language.iso.fl_str_mv por
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dc.relation.none.fl_str_mv https://revistas.ufrj.br/index.php/aigeo/article/view/7845/6326
dc.rights.driver.fl_str_mv Copyright (c) 2016 Anuário do Instituto de Geociências
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 Anuário do Instituto de Geociências
http://creativecommons.org/licenses/by/4.0
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dc.publisher.none.fl_str_mv Universidade Federal do Rio de Janeiro
publisher.none.fl_str_mv Universidade Federal do Rio de Janeiro
dc.source.none.fl_str_mv Anuário do Instituto de Geociências; Vol 38, No 1 (2015); 73-80
Anuário do Instituto de Geociências; Vol 38, No 1 (2015); 73-80
1982-3908
0101-9759
reponame:Anuário do Instituto de Geociências (Online)
instname:Universidade Federal do Rio de Janeiro (UFRJ)
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institution UFRJ
reponame_str Anuário do Instituto de Geociências (Online)
collection Anuário do Instituto de Geociências (Online)
repository.name.fl_str_mv Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)
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