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
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/133013
Ver los metadatos del registro completo
| id |
SEDICI_5dccec11999a22030ff5230ab2f7d4d3 |
|---|---|
| oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/133013 |
| network_acronym_str |
SEDICI |
| repository_id_str |
1329 |
| 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 |
| _version_ |
1848605670117474304 |
| score |
13.24909 |