Precipitação pluviométrica mensal no estado do Rio de Janeiro: sazonalidade e tendência

Detalhes bibliográficos
Autor(a) principal: Carvalho Araujo, Mirian Fernandes
Data de Publicação: 2009
Outros Autores: Guimaraes, Ednaldo Carvalho, de Carvalho, Daniel Fonseca, de Araujo, Lucio Borges [UNESP]
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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spelling 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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