Variational Data Assimilation in Chaotic Regime by Lorenz Model
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , |
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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Anuário do Instituto de Geociências (Online) |
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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 |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufrj.br/index.php/aigeo/article/view/7845 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 |
language |
por |
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 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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) instacron:UFRJ |
instname_str |
Universidade Federal do Rio de Janeiro (UFRJ) |
instacron_str |
UFRJ |
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) |
repository.mail.fl_str_mv |
anuario@igeo.ufrj.br|| |
_version_ |
1797053541168185344 |