Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37742 |
Resumo: | The determination of homogeneous regions with precipitation and probability models when considering the El Niño- Southern Oscillation (ENSO) phenomenon is important for the planning of water resources and for the study of how climate change affects precipitation regimes. Thus, six homogeneous regions with annual mean precipitation were determined through a cluster analysis using Ward's agglomeration method and applied to a historical series of 31 years (1960-1990) at 413 satellite monitoring points in the state of Pará, where the selected years occurred during an El Niño or a La Niña event. When adjusting the probability models, the chi-square test was applied to 413 monitoring points spread over the six homogeneous regions during years with a La Niña or an El Niño, as well as the complete set of years. The normal model (i.e., the normal function) had the best fit, with chi-square values below 3.84 (tabulated chi-square values). The model was validated using 12 rainfall stations of the National Water Agency (ANA), which were distributed across the six homogeneous regions. In this case, the chi-square test for the 12 stations also had values lower than 3.84. A good fit between the observed and the regionalized data demonstrated the potential of the methodology developed and used for estimating annual average precipitation probabilities. |
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Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazonclimate changecluster analysisaverage annual rainfallAmazon.RegionalizaçãoThe determination of homogeneous regions with precipitation and probability models when considering the El Niño- Southern Oscillation (ENSO) phenomenon is important for the planning of water resources and for the study of how climate change affects precipitation regimes. Thus, six homogeneous regions with annual mean precipitation were determined through a cluster analysis using Ward's agglomeration method and applied to a historical series of 31 years (1960-1990) at 413 satellite monitoring points in the state of Pará, where the selected years occurred during an El Niño or a La Niña event. When adjusting the probability models, the chi-square test was applied to 413 monitoring points spread over the six homogeneous regions during years with a La Niña or an El Niño, as well as the complete set of years. The normal model (i.e., the normal function) had the best fit, with chi-square values below 3.84 (tabulated chi-square values). The model was validated using 12 rainfall stations of the National Water Agency (ANA), which were distributed across the six homogeneous regions. In this case, the chi-square test for the 12 stations also had values lower than 3.84. A good fit between the observed and the regionalized data demonstrated the potential of the methodology developed and used for estimating annual average precipitation probabilities. Universidade Estadual De Maringá2018-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionanálise estatísticaapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/3774210.4025/actascitechnol.v40i1.37742Acta Scientiarum. Technology; Vol 40 (2018): Publicação Contínua; e37742Acta Scientiarum. Technology; v. 40 (2018): Publicação Contínua; e377421806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37742/pdfCopyright (c) 2018 Acta Scientiarum. Technologyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGonçalves, Mariane FurtadoBlanco, Claudio José CavalcanteSantos, Vanessa Conceição dosOliveira, Luciana Leal dos Santos2019-07-17T11:53:49Zoai:periodicos.uem.br/ojs:article/37742Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2019-07-17T11:53:49Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon |
title |
Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon |
spellingShingle |
Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon Gonçalves, Mariane Furtado climate change cluster analysis average annual rainfall Amazon. Regionalização |
title_short |
Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon |
title_full |
Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon |
title_fullStr |
Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon |
title_full_unstemmed |
Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon |
title_sort |
Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon |
author |
Gonçalves, Mariane Furtado |
author_facet |
Gonçalves, Mariane Furtado Blanco, Claudio José Cavalcante Santos, Vanessa Conceição dos Oliveira, Luciana Leal dos Santos |
author_role |
author |
author2 |
Blanco, Claudio José Cavalcante Santos, Vanessa Conceição dos Oliveira, Luciana Leal dos Santos |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Gonçalves, Mariane Furtado Blanco, Claudio José Cavalcante Santos, Vanessa Conceição dos Oliveira, Luciana Leal dos Santos |
dc.subject.por.fl_str_mv |
climate change cluster analysis average annual rainfall Amazon. Regionalização |
topic |
climate change cluster analysis average annual rainfall Amazon. Regionalização |
description |
The determination of homogeneous regions with precipitation and probability models when considering the El Niño- Southern Oscillation (ENSO) phenomenon is important for the planning of water resources and for the study of how climate change affects precipitation regimes. Thus, six homogeneous regions with annual mean precipitation were determined through a cluster analysis using Ward's agglomeration method and applied to a historical series of 31 years (1960-1990) at 413 satellite monitoring points in the state of Pará, where the selected years occurred during an El Niño or a La Niña event. When adjusting the probability models, the chi-square test was applied to 413 monitoring points spread over the six homogeneous regions during years with a La Niña or an El Niño, as well as the complete set of years. The normal model (i.e., the normal function) had the best fit, with chi-square values below 3.84 (tabulated chi-square values). The model was validated using 12 rainfall stations of the National Water Agency (ANA), which were distributed across the six homogeneous regions. In this case, the chi-square test for the 12 stations also had values lower than 3.84. A good fit between the observed and the regionalized data demonstrated the potential of the methodology developed and used for estimating annual average precipitation probabilities. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-07-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion análise estatística |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37742 10.4025/actascitechnol.v40i1.37742 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37742 |
identifier_str_mv |
10.4025/actascitechnol.v40i1.37742 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37742/pdf |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Acta Scientiarum. Technology https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Acta Scientiarum. Technology https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 40 (2018): Publicação Contínua; e37742 Acta Scientiarum. Technology; v. 40 (2018): Publicação Contínua; e37742 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1799315336829337600 |