Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina

Autores
Ratto, Gustavo; Maronna, Ricardo Antonio; Berri, Guillermo Jorge
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Knowledge of frequency wind patterns is very important for air pollution modelling, especially in a city like La Plata (approximately 850,000 inhabitants) with high vehicular and industrial activities and no air monitoring network. An hourly wind analysis was carried out on data from two local weather stations (points A and J). An initial result was that, in spite of differences in data quality, the local weather stations observations were consistent with local and regional National Meteorological Service (NMS) monthly based observations. Two non conventional multivariate statistical methods were employed to further analyse hourly data at points A and J. Hierarchical cluster resulted in a good summarising tool to visualise prevailing hourly winds. Resultant vectors emerging from the clustering process showed good similarity between sites and seasons; this allowed a further visualization of the average diurnal wind development. Multidimensional scaling (MDS) permitted a pairwise comparison of a large number of hourly wind roses. These wind roses were more similar to each other in colder seasons and at site A (the one that is closer to the river) than in warmer seasons and at site J. Most of the observed variations regarding seasons and sites revealed by cluster and MDS analysis are explained in terms of the sea-land breeze circulations. The methodology applied proved to be of utility for simplifying the analysis of high dimensional data with numerous observations.
Facultad de Ingeniería
Centro de Investigaciones Ópticas
Facultad de Ciencias Exactas
Materia
Ingeniería
Ciencias Exactas
Cluster analysis
Multidimensional scaling
Wind rose analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/133013

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network_name_str SEDICI (UNLP)
spelling Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, ArgentinaRatto, GustavoMaronna, Ricardo AntonioBerri, Guillermo JorgeIngenieríaCiencias ExactasCluster analysisMultidimensional scalingWind rose analysisKnowledge of frequency wind patterns is very important for air pollution modelling, especially in a city like La Plata (approximately 850,000 inhabitants) with high vehicular and industrial activities and no air monitoring network. An hourly wind analysis was carried out on data from two local weather stations (points A and J). An initial result was that, in spite of differences in data quality, the local weather stations observations were consistent with local and regional National Meteorological Service (NMS) monthly based observations. Two non conventional multivariate statistical methods were employed to further analyse hourly data at points A and J. Hierarchical cluster resulted in a good summarising tool to visualise prevailing hourly winds. Resultant vectors emerging from the clustering process showed good similarity between sites and seasons; this allowed a further visualization of the average diurnal wind development. Multidimensional scaling (MDS) permitted a pairwise comparison of a large number of hourly wind roses. These wind roses were more similar to each other in colder seasons and at site A (the one that is closer to the river) than in warmer seasons and at site J. Most of the observed variations regarding seasons and sites revealed by cluster and MDS analysis are explained in terms of the sea-land breeze circulations. The methodology applied proved to be of utility for simplifying the analysis of high dimensional data with numerous observations.Facultad de IngenieríaCentro de Investigaciones ÓpticasFacultad de Ciencias Exactas2010-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf477-492http://sedici.unlp.edu.ar/handle/10915/133013enginfo:eu-repo/semantics/altIdentifier/issn/0006-8314info:eu-repo/semantics/altIdentifier/issn/1573-1472info:eu-repo/semantics/altIdentifier/doi/10.1007/s10546-010-9539-3info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-12T10:56:19Zoai:sedici.unlp.edu.ar:10915/133013Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-12 10:56:19.99SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina
title Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina
spellingShingle Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina
Ratto, Gustavo
Ingeniería
Ciencias Exactas
Cluster analysis
Multidimensional scaling
Wind rose analysis
title_short Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina
title_full Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina
title_fullStr Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina
title_full_unstemmed Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina
title_sort Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina
dc.creator.none.fl_str_mv Ratto, Gustavo
Maronna, Ricardo Antonio
Berri, Guillermo Jorge
author Ratto, Gustavo
author_facet Ratto, Gustavo
Maronna, Ricardo Antonio
Berri, Guillermo Jorge
author_role author
author2 Maronna, Ricardo Antonio
Berri, Guillermo Jorge
author2_role author
author
dc.subject.none.fl_str_mv Ingeniería
Ciencias Exactas
Cluster analysis
Multidimensional scaling
Wind rose analysis
topic Ingeniería
Ciencias Exactas
Cluster analysis
Multidimensional scaling
Wind rose analysis
dc.description.none.fl_txt_mv Knowledge of frequency wind patterns is very important for air pollution modelling, especially in a city like La Plata (approximately 850,000 inhabitants) with high vehicular and industrial activities and no air monitoring network. An hourly wind analysis was carried out on data from two local weather stations (points A and J). An initial result was that, in spite of differences in data quality, the local weather stations observations were consistent with local and regional National Meteorological Service (NMS) monthly based observations. Two non conventional multivariate statistical methods were employed to further analyse hourly data at points A and J. Hierarchical cluster resulted in a good summarising tool to visualise prevailing hourly winds. Resultant vectors emerging from the clustering process showed good similarity between sites and seasons; this allowed a further visualization of the average diurnal wind development. Multidimensional scaling (MDS) permitted a pairwise comparison of a large number of hourly wind roses. These wind roses were more similar to each other in colder seasons and at site A (the one that is closer to the river) than in warmer seasons and at site J. Most of the observed variations regarding seasons and sites revealed by cluster and MDS analysis are explained in terms of the sea-land breeze circulations. The methodology applied proved to be of utility for simplifying the analysis of high dimensional data with numerous observations.
Facultad de Ingeniería
Centro de Investigaciones Ópticas
Facultad de Ciencias Exactas
description Knowledge of frequency wind patterns is very important for air pollution modelling, especially in a city like La Plata (approximately 850,000 inhabitants) with high vehicular and industrial activities and no air monitoring network. An hourly wind analysis was carried out on data from two local weather stations (points A and J). An initial result was that, in spite of differences in data quality, the local weather stations observations were consistent with local and regional National Meteorological Service (NMS) monthly based observations. Two non conventional multivariate statistical methods were employed to further analyse hourly data at points A and J. Hierarchical cluster resulted in a good summarising tool to visualise prevailing hourly winds. Resultant vectors emerging from the clustering process showed good similarity between sites and seasons; this allowed a further visualization of the average diurnal wind development. Multidimensional scaling (MDS) permitted a pairwise comparison of a large number of hourly wind roses. These wind roses were more similar to each other in colder seasons and at site A (the one that is closer to the river) than in warmer seasons and at site J. Most of the observed variations regarding seasons and sites revealed by cluster and MDS analysis are explained in terms of the sea-land breeze circulations. The methodology applied proved to be of utility for simplifying the analysis of high dimensional data with numerous observations.
publishDate 2010
dc.date.none.fl_str_mv 2010-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/133013
url http://sedici.unlp.edu.ar/handle/10915/133013
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0006-8314
info:eu-repo/semantics/altIdentifier/issn/1573-1472
info:eu-repo/semantics/altIdentifier/doi/10.1007/s10546-010-9539-3
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.format.none.fl_str_mv application/pdf
477-492
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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