Automatic methods to detect the top of atmospheric boundary layer
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , , , |
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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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 |
|
_version_ |
1808129156375904256 |