Estimation of optimal gravity wave parameters for climate models using data assimilation

Autores
Pulido, Manuel Arturo; Polavarapu, Saroja; Shepherd, Theodore; Thuburn, John
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
There is a current need to constrain the parameters of gravity wave drag schemes in climate models using observational information instead of tuning them subjectively. In this work, an inverse technique is developed using data assimilation principles to estimate gravity wave parameters.  Because most gravity wave drag schemes assume instantaneous vertical propagation of gravity waves within a column, observations in a single column can be used to formulate a one-dimensional assimilation problem to estimate the unknown parameters. We define a cost function that measures the differences between the unresolved drag inferred from observations (referred to here as the `observed´ gravity wave drag) and the gravity wave drag calculated with a parameterisation scheme. The geometry of the cost function presents some difficulties, including multiple minima and ill-conditioning because of the non-independence of the gravity-wave parameters. To overcome these difficulties we propose a genetic algorithm to minimize the cost function, which provides a robust parameter estimation over a broad range of prescribed `true´ parameters. When real experiments using an independent estimate of the `observed´ gravity wave drag are performed, physically unrealistic values of the parameters can result due to the non-independence of the parameters. However by constraining one of the parameters to lie within a physically realistic range, this degeneracy is broken and the other parameters are also found to lie within physically realistic ranges. This argues for the essential physical self-consistency of the gravity wave scheme. A much better fit to the observed gravity wave drag at high latitudes is obtained when the parameters are allowed to vary with latitude. However, a close fit can be obtained either in the upper or the lower part of the profiles, but not both at the same time. This result is a consequence of assuming an isotropic launch spectrum. The changes of sign in the gravity wave drag found in the tropical lower stratosphere, which are associated with part of the QBO forcing, cannot be captured by the parameterisation with optimal parameters.
Fil: Pulido, Manuel Arturo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Modelado e Innovación Tecnológica. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Modelado e Innovación Tecnologica; Argentina. University of Toronto; Canadá
Fil: Polavarapu, Saroja. Environment Canada; Canadá
Fil: Shepherd, Theodore. University of Toronto; Canadá
Fil: Thuburn, John. University Of Exeter; Reino Unido
Materia
Subgrid Scale
Genetic Algorithm
Missing Forcing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/17238

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spelling Estimation of optimal gravity wave parameters for climate models using data assimilationPulido, Manuel ArturoPolavarapu, SarojaShepherd, TheodoreThuburn, JohnSubgrid ScaleGenetic AlgorithmMissing Forcinghttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1There is a current need to constrain the parameters of gravity wave drag schemes in climate models using observational information instead of tuning them subjectively. In this work, an inverse technique is developed using data assimilation principles to estimate gravity wave parameters.  Because most gravity wave drag schemes assume instantaneous vertical propagation of gravity waves within a column, observations in a single column can be used to formulate a one-dimensional assimilation problem to estimate the unknown parameters. We define a cost function that measures the differences between the unresolved drag inferred from observations (referred to here as the `observed´ gravity wave drag) and the gravity wave drag calculated with a parameterisation scheme. The geometry of the cost function presents some difficulties, including multiple minima and ill-conditioning because of the non-independence of the gravity-wave parameters. To overcome these difficulties we propose a genetic algorithm to minimize the cost function, which provides a robust parameter estimation over a broad range of prescribed `true´ parameters. When real experiments using an independent estimate of the `observed´ gravity wave drag are performed, physically unrealistic values of the parameters can result due to the non-independence of the parameters. However by constraining one of the parameters to lie within a physically realistic range, this degeneracy is broken and the other parameters are also found to lie within physically realistic ranges. This argues for the essential physical self-consistency of the gravity wave scheme. A much better fit to the observed gravity wave drag at high latitudes is obtained when the parameters are allowed to vary with latitude. However, a close fit can be obtained either in the upper or the lower part of the profiles, but not both at the same time. This result is a consequence of assuming an isotropic launch spectrum. The changes of sign in the gravity wave drag found in the tropical lower stratosphere, which are associated with part of the QBO forcing, cannot be captured by the parameterisation with optimal parameters.Fil: Pulido, Manuel Arturo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Modelado e Innovación Tecnológica. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Modelado e Innovación Tecnologica; Argentina. University of Toronto; CanadáFil: Polavarapu, Saroja. Environment Canada; CanadáFil: Shepherd, Theodore. University of Toronto; CanadáFil: Thuburn, John. University Of Exeter; Reino UnidoJohn Wiley & Sons Ltd2011-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/17238Pulido, Manuel Arturo; Polavarapu, Saroja; Shepherd, Theodore; Thuburn, John; Estimation of optimal gravity wave parameters for climate models using data assimilation; John Wiley & Sons Ltd; Quarterly Journal Of The Royal Meteorological Society; 138; 663; 9-2011; 298-3090035-90091477-870Xenginfo:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1002/qj.932/abstractinfo:eu-repo/semantics/altIdentifier/doi/10.1002/qj.932info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:03:29Zoai:ri.conicet.gov.ar:11336/17238instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:03:30.242CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Estimation of optimal gravity wave parameters for climate models using data assimilation
title Estimation of optimal gravity wave parameters for climate models using data assimilation
spellingShingle Estimation of optimal gravity wave parameters for climate models using data assimilation
Pulido, Manuel Arturo
Subgrid Scale
Genetic Algorithm
Missing Forcing
title_short Estimation of optimal gravity wave parameters for climate models using data assimilation
title_full Estimation of optimal gravity wave parameters for climate models using data assimilation
title_fullStr Estimation of optimal gravity wave parameters for climate models using data assimilation
title_full_unstemmed Estimation of optimal gravity wave parameters for climate models using data assimilation
title_sort Estimation of optimal gravity wave parameters for climate models using data assimilation
dc.creator.none.fl_str_mv Pulido, Manuel Arturo
Polavarapu, Saroja
Shepherd, Theodore
Thuburn, John
author Pulido, Manuel Arturo
author_facet Pulido, Manuel Arturo
Polavarapu, Saroja
Shepherd, Theodore
Thuburn, John
author_role author
author2 Polavarapu, Saroja
Shepherd, Theodore
Thuburn, John
author2_role author
author
author
dc.subject.none.fl_str_mv Subgrid Scale
Genetic Algorithm
Missing Forcing
topic Subgrid Scale
Genetic Algorithm
Missing Forcing
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv There is a current need to constrain the parameters of gravity wave drag schemes in climate models using observational information instead of tuning them subjectively. In this work, an inverse technique is developed using data assimilation principles to estimate gravity wave parameters.  Because most gravity wave drag schemes assume instantaneous vertical propagation of gravity waves within a column, observations in a single column can be used to formulate a one-dimensional assimilation problem to estimate the unknown parameters. We define a cost function that measures the differences between the unresolved drag inferred from observations (referred to here as the `observed´ gravity wave drag) and the gravity wave drag calculated with a parameterisation scheme. The geometry of the cost function presents some difficulties, including multiple minima and ill-conditioning because of the non-independence of the gravity-wave parameters. To overcome these difficulties we propose a genetic algorithm to minimize the cost function, which provides a robust parameter estimation over a broad range of prescribed `true´ parameters. When real experiments using an independent estimate of the `observed´ gravity wave drag are performed, physically unrealistic values of the parameters can result due to the non-independence of the parameters. However by constraining one of the parameters to lie within a physically realistic range, this degeneracy is broken and the other parameters are also found to lie within physically realistic ranges. This argues for the essential physical self-consistency of the gravity wave scheme. A much better fit to the observed gravity wave drag at high latitudes is obtained when the parameters are allowed to vary with latitude. However, a close fit can be obtained either in the upper or the lower part of the profiles, but not both at the same time. This result is a consequence of assuming an isotropic launch spectrum. The changes of sign in the gravity wave drag found in the tropical lower stratosphere, which are associated with part of the QBO forcing, cannot be captured by the parameterisation with optimal parameters.
Fil: Pulido, Manuel Arturo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Modelado e Innovación Tecnológica. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Modelado e Innovación Tecnologica; Argentina. University of Toronto; Canadá
Fil: Polavarapu, Saroja. Environment Canada; Canadá
Fil: Shepherd, Theodore. University of Toronto; Canadá
Fil: Thuburn, John. University Of Exeter; Reino Unido
description There is a current need to constrain the parameters of gravity wave drag schemes in climate models using observational information instead of tuning them subjectively. In this work, an inverse technique is developed using data assimilation principles to estimate gravity wave parameters.  Because most gravity wave drag schemes assume instantaneous vertical propagation of gravity waves within a column, observations in a single column can be used to formulate a one-dimensional assimilation problem to estimate the unknown parameters. We define a cost function that measures the differences between the unresolved drag inferred from observations (referred to here as the `observed´ gravity wave drag) and the gravity wave drag calculated with a parameterisation scheme. The geometry of the cost function presents some difficulties, including multiple minima and ill-conditioning because of the non-independence of the gravity-wave parameters. To overcome these difficulties we propose a genetic algorithm to minimize the cost function, which provides a robust parameter estimation over a broad range of prescribed `true´ parameters. When real experiments using an independent estimate of the `observed´ gravity wave drag are performed, physically unrealistic values of the parameters can result due to the non-independence of the parameters. However by constraining one of the parameters to lie within a physically realistic range, this degeneracy is broken and the other parameters are also found to lie within physically realistic ranges. This argues for the essential physical self-consistency of the gravity wave scheme. A much better fit to the observed gravity wave drag at high latitudes is obtained when the parameters are allowed to vary with latitude. However, a close fit can be obtained either in the upper or the lower part of the profiles, but not both at the same time. This result is a consequence of assuming an isotropic launch spectrum. The changes of sign in the gravity wave drag found in the tropical lower stratosphere, which are associated with part of the QBO forcing, cannot be captured by the parameterisation with optimal parameters.
publishDate 2011
dc.date.none.fl_str_mv 2011-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/17238
Pulido, Manuel Arturo; Polavarapu, Saroja; Shepherd, Theodore; Thuburn, John; Estimation of optimal gravity wave parameters for climate models using data assimilation; John Wiley & Sons Ltd; Quarterly Journal Of The Royal Meteorological Society; 138; 663; 9-2011; 298-309
0035-9009
1477-870X
url http://hdl.handle.net/11336/17238
identifier_str_mv Pulido, Manuel Arturo; Polavarapu, Saroja; Shepherd, Theodore; Thuburn, John; Estimation of optimal gravity wave parameters for climate models using data assimilation; John Wiley & Sons Ltd; Quarterly Journal Of The Royal Meteorological Society; 138; 663; 9-2011; 298-309
0035-9009
1477-870X
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1002/qj.932/abstract
info:eu-repo/semantics/altIdentifier/doi/10.1002/qj.932
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons Ltd
publisher.none.fl_str_mv John Wiley & Sons Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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