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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/17238
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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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1844613851550580736 |
score |
13.070432 |