Automatic methods to detect the top of atmospheric boundary layer

Detalhes bibliográficos
Autor(a) principal: De A. Moreira, Gregori
Data de Publicação: 2013
Outros Autores: Bourayou, Riad, Da Silva Lopes, Fábio J., Albuquerque, Taciana A., Reis, Neyval C., Held, Gerhard, Landulfo, Eduardo
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1117/12.2028750
http://hdl.handle.net/11449/231311
Resumo: The main objective of this work is to obtain methods that automatically allow qualitative detections of Atmospheric Boundary Layer heights from LIDAR data. Case studies will be used to describe the more relevant days of a campaign carried out in July of 2012 in Vitória, Espírito Santo, Brazil. The data analysis compares three mathematical algorithms that automatically provide the ABL height: Gradient Method (GM), using the derivative of the Range Corrected Signal (RCS) logarithm, WCT (Wavelet Covariance Transform), and Bulk Richardson's Number, which was used to validate the methods mentioned above. The comparison between the methods has shown that as the presence of clouds and the aerosol sublayer increased, the more sensitive was the refinement needed to choose the right parameters, whereas even Richardson's method had ambiguities in finding a good estimate of the ABL top. © 2013 SPIE.
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spelling Automatic methods to detect the top of atmospheric boundary layerBoundary LayerGradient MethodLIDARRichardsonWaveletThe main objective of this work is to obtain methods that automatically allow qualitative detections of Atmospheric Boundary Layer heights from LIDAR data. Case studies will be used to describe the more relevant days of a campaign carried out in July of 2012 in Vitória, Espírito Santo, Brazil. The data analysis compares three mathematical algorithms that automatically provide the ABL height: Gradient Method (GM), using the derivative of the Range Corrected Signal (RCS) logarithm, WCT (Wavelet Covariance Transform), and Bulk Richardson's Number, which was used to validate the methods mentioned above. The comparison between the methods has shown that as the presence of clouds and the aerosol sublayer increased, the more sensitive was the refinement needed to choose the right parameters, whereas even Richardson's method had ambiguities in finding a good estimate of the ABL top. © 2013 SPIE.Laser Environmental Applications Center for Lasers and Applications - Nuclear and Energy Institute Cidade Universitária, Av. Prof. Lineu Prestes 2242, SP 05508 -000lDepartment of Environment Engineering Technologic Center Federal University of Espírito Santo, Av. Fernando Ferrari, 514, Campus Universitário, Espírito-Santo 29075 910Meteorological Research Institute State University of São Paulo - Estrada Municipal José Sandrin, Chácara Bauruense, Bauru, SP 17048-699Cidade UniversitáriaFederal University of Espírito SantoUniversidade de São Paulo (USP)De A. Moreira, GregoriBourayou, RiadDa Silva Lopes, Fábio J.Albuquerque, Taciana A.Reis, Neyval C.Held, GerhardLandulfo, Eduardo2022-04-29T08:44:45Z2022-04-29T08:44:45Z2013-12-23info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1117/12.2028750Proceedings of SPIE - The International Society for Optical Engineering, v. 8894.0277-786X1996-756Xhttp://hdl.handle.net/11449/23131110.1117/12.20287502-s2.0-84890515474Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of SPIE - The International Society for Optical Engineeringinfo:eu-repo/semantics/openAccess2022-04-29T08:44:45Zoai:repositorio.unesp.br:11449/231311Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:03:59.864199Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Automatic methods to detect the top of atmospheric boundary layer
title Automatic methods to detect the top of atmospheric boundary layer
spellingShingle Automatic methods to detect the top of atmospheric boundary layer
De A. Moreira, Gregori
Boundary Layer
Gradient Method
LIDAR
Richardson
Wavelet
title_short Automatic methods to detect the top of atmospheric boundary layer
title_full Automatic methods to detect the top of atmospheric boundary layer
title_fullStr Automatic methods to detect the top of atmospheric boundary layer
title_full_unstemmed Automatic methods to detect the top of atmospheric boundary layer
title_sort Automatic methods to detect the top of atmospheric boundary layer
author De A. Moreira, Gregori
author_facet De A. Moreira, Gregori
Bourayou, Riad
Da Silva Lopes, Fábio J.
Albuquerque, Taciana A.
Reis, Neyval C.
Held, Gerhard
Landulfo, Eduardo
author_role author
author2 Bourayou, Riad
Da Silva Lopes, Fábio J.
Albuquerque, Taciana A.
Reis, Neyval C.
Held, Gerhard
Landulfo, Eduardo
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Cidade Universitária
Federal University of Espírito Santo
Universidade de São Paulo (USP)
dc.contributor.author.fl_str_mv De A. Moreira, Gregori
Bourayou, Riad
Da Silva Lopes, Fábio J.
Albuquerque, Taciana A.
Reis, Neyval C.
Held, Gerhard
Landulfo, Eduardo
dc.subject.por.fl_str_mv Boundary Layer
Gradient Method
LIDAR
Richardson
Wavelet
topic Boundary Layer
Gradient Method
LIDAR
Richardson
Wavelet
description The main objective of this work is to obtain methods that automatically allow qualitative detections of Atmospheric Boundary Layer heights from LIDAR data. Case studies will be used to describe the more relevant days of a campaign carried out in July of 2012 in Vitória, Espírito Santo, Brazil. The data analysis compares three mathematical algorithms that automatically provide the ABL height: Gradient Method (GM), using the derivative of the Range Corrected Signal (RCS) logarithm, WCT (Wavelet Covariance Transform), and Bulk Richardson's Number, which was used to validate the methods mentioned above. The comparison between the methods has shown that as the presence of clouds and the aerosol sublayer increased, the more sensitive was the refinement needed to choose the right parameters, whereas even Richardson's method had ambiguities in finding a good estimate of the ABL top. © 2013 SPIE.
publishDate 2013
dc.date.none.fl_str_mv 2013-12-23
2022-04-29T08:44:45Z
2022-04-29T08:44:45Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1117/12.2028750
Proceedings of SPIE - The International Society for Optical Engineering, v. 8894.
0277-786X
1996-756X
http://hdl.handle.net/11449/231311
10.1117/12.2028750
2-s2.0-84890515474
url http://dx.doi.org/10.1117/12.2028750
http://hdl.handle.net/11449/231311
identifier_str_mv Proceedings of SPIE - The International Society for Optical Engineering, v. 8894.
0277-786X
1996-756X
10.1117/12.2028750
2-s2.0-84890515474
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings of SPIE - The International Society for Optical Engineering
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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