Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência
Autor(a) principal: | |
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Data de Publicação: | 2009 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://www.seer.ufu.br/index.php/biosciencejournal/article/view/6963 http://hdl.handle.net/11449/40809 |
Resumo: | The objective of this work was to carry a descriptive analysis in the monthly precipitation of rainfall stations from Rio de Janeiro State, Brazil, using data of position and dispersion and graphical analyses, and to verify the presence of seasonality and trend in these data, with a study about the application of models of time series. The descriptive statistics was to characterize the general behavior of the series in three stations selected which present consistent historical series. The methodology of analysis of variance in randomized blocks and the determination of models of multiple linear regression, considering years and months as predictors variables, disclosed the presence of seasonality, what allowed to infer on the occurrence of repetitive natural phenomena throughout the time and absence of trend in the data. It was applied the methodology of multiple linear regression to removal the seasonality of these time series. The original data had been deducted from the estimates made by the adjusted model and the analysis of variance in randomized blocks for the residues of regression was preceded again. With the results obtained it was possible to conclude that the monthly rainfall present seasonality and they don't present trend, the analysis of multiple regression was efficient in the removal of the seasonality, and the rainfall can be studied by means of time series. |
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Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendênciaThe monthly rainfall in the Rio de Janeiro state, Brazil: seasonality and trendClimateTime seriesRainfall statisticsMultiple regressionThe objective of this work was to carry a descriptive analysis in the monthly precipitation of rainfall stations from Rio de Janeiro State, Brazil, using data of position and dispersion and graphical analyses, and to verify the presence of seasonality and trend in these data, with a study about the application of models of time series. The descriptive statistics was to characterize the general behavior of the series in three stations selected which present consistent historical series. The methodology of analysis of variance in randomized blocks and the determination of models of multiple linear regression, considering years and months as predictors variables, disclosed the presence of seasonality, what allowed to infer on the occurrence of repetitive natural phenomena throughout the time and absence of trend in the data. It was applied the methodology of multiple linear regression to removal the seasonality of these time series. The original data had been deducted from the estimates made by the adjusted model and the analysis of variance in randomized blocks for the residues of regression was preceded again. With the results obtained it was possible to conclude that the monthly rainfall present seasonality and they don't present trend, the analysis of multiple regression was efficient in the removal of the seasonality, and the rainfall can be studied by means of time series.O presente trabalho foi dirigido no sentido de realizar uma análise descritiva da precipitação pluviométrica mensal de estações climatológicas do Estado do Rio de Janeiro, utilizando medidas de posição e de dispersão e análises gráficas, e, através de um estudo sobre a aplicação de modelos de séries temporais, verificar a presença das componentes de sazonalidade e de tendência nestes dados. Os dados experimentais utilizados fazem parte do Banco de Dados Climatológicos do Estado do Rio de Janeiro. Selecionou-se três estações por apresentarem séries históricas consistentes. A estatística descritiva foi utilizada para caracterizar o comportamento geral da série. A metodologia de análise de variância em blocos casualizados e determinação de modelos de regressão linear múltipla, considerando anos e meses como variáveis preditoras, revelaram a presença de sazonalidade, que permitiu inferir sobre a ocorrência de fenômenos naturais repetitivos ao longo do tempo, e ausência de tendência. Aplicou-se a metodologia de regressão linear múltipla para a remoção da sazonalidade dessas séries temporais. Os dados originais foram subtraídos das estimativas feitas pelo modelo ajustado e procedeu-se novamente a análise de variância em blocos casualizados para os resíduos da regressão. Verificou-se que a regressão múltipla foi eficiente na remoção da sazonalidade da série.Univ São Paulo, ESALQ, BR-05508 São Paulo, BrazilUniversidade Federal de Uberlândia (UFU), Fac Matemat, BR-38400 Uberlandia, MG, BrazilUniv Fed Rural Rio de Janeiro, Inst Tecnol, Dept Engn, Soropedica, RJ, BrazilUniv Estadual Paulista, Botucatu, SP, BrazilUniv Estadual Paulista, Botucatu, SP, BrazilUniversidade Federal de Uberlândia (UFU)Universidade de São Paulo (USP)Universidade Federal de Uberlândia (UFU)Universidade Federal Rural do Rio de Janeiro (UFRRJ)Universidade Estadual Paulista (Unesp)Carvalho Araujo, Mirian FernandesGuimaraes, Ednaldo Carvalhode Carvalho, Daniel Fonsecade Araujo, Lucio Borges [UNESP]2014-05-20T15:31:45Z2014-05-20T15:31:45Z2009-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article90-100application/pdfhttp://www.seer.ufu.br/index.php/biosciencejournal/article/view/6963Bioscience Journal. Uberlandia: Universidade Federal de Uberlândia (UFU), v. 25, n. 4, p. 90-100, 2009.1516-3725http://hdl.handle.net/11449/40809WOS:000269317400012WOS000269317400012.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporBioscience Journal0,303info:eu-repo/semantics/openAccess2024-01-19T06:34:27Zoai:repositorio.unesp.br:11449/40809Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:26:27.984408Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência The monthly rainfall in the Rio de Janeiro state, Brazil: seasonality and trend |
title |
Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência |
spellingShingle |
Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência Carvalho Araujo, Mirian Fernandes Climate Time series Rainfall statistics Multiple regression |
title_short |
Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência |
title_full |
Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência |
title_fullStr |
Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência |
title_full_unstemmed |
Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência |
title_sort |
Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência |
author |
Carvalho Araujo, Mirian Fernandes |
author_facet |
Carvalho Araujo, Mirian Fernandes Guimaraes, Ednaldo Carvalho de Carvalho, Daniel Fonseca de Araujo, Lucio Borges [UNESP] |
author_role |
author |
author2 |
Guimaraes, Ednaldo Carvalho de Carvalho, Daniel Fonseca de Araujo, Lucio Borges [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Federal de Uberlândia (UFU) Universidade Federal Rural do Rio de Janeiro (UFRRJ) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Carvalho Araujo, Mirian Fernandes Guimaraes, Ednaldo Carvalho de Carvalho, Daniel Fonseca de Araujo, Lucio Borges [UNESP] |
dc.subject.por.fl_str_mv |
Climate Time series Rainfall statistics Multiple regression |
topic |
Climate Time series Rainfall statistics Multiple regression |
description |
The objective of this work was to carry a descriptive analysis in the monthly precipitation of rainfall stations from Rio de Janeiro State, Brazil, using data of position and dispersion and graphical analyses, and to verify the presence of seasonality and trend in these data, with a study about the application of models of time series. The descriptive statistics was to characterize the general behavior of the series in three stations selected which present consistent historical series. The methodology of analysis of variance in randomized blocks and the determination of models of multiple linear regression, considering years and months as predictors variables, disclosed the presence of seasonality, what allowed to infer on the occurrence of repetitive natural phenomena throughout the time and absence of trend in the data. It was applied the methodology of multiple linear regression to removal the seasonality of these time series. The original data had been deducted from the estimates made by the adjusted model and the analysis of variance in randomized blocks for the residues of regression was preceded again. With the results obtained it was possible to conclude that the monthly rainfall present seasonality and they don't present trend, the analysis of multiple regression was efficient in the removal of the seasonality, and the rainfall can be studied by means of time series. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-01-01 2014-05-20T15:31:45Z 2014-05-20T15:31:45Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.seer.ufu.br/index.php/biosciencejournal/article/view/6963 Bioscience Journal. Uberlandia: Universidade Federal de Uberlândia (UFU), v. 25, n. 4, p. 90-100, 2009. 1516-3725 http://hdl.handle.net/11449/40809 WOS:000269317400012 WOS000269317400012.pdf |
url |
http://www.seer.ufu.br/index.php/biosciencejournal/article/view/6963 http://hdl.handle.net/11449/40809 |
identifier_str_mv |
Bioscience Journal. Uberlandia: Universidade Federal de Uberlândia (UFU), v. 25, n. 4, p. 90-100, 2009. 1516-3725 WOS:000269317400012 WOS000269317400012.pdf |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
Bioscience Journal 0,303 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
90-100 application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Uberlândia (UFU) |
publisher.none.fl_str_mv |
Universidade Federal de Uberlândia (UFU) |
dc.source.none.fl_str_mv |
Web of Science 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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1808129520758161408 |