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: | eng por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/219775 |
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 trendClimateMultiple regressionRainfall statisticsTime seriesThe 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.Escola Superior de Agricultura 'Luiz de Queiroz'-ESALQ Universidade de São Paulo-USPFaculdade de Matemática Universidade Federal de Uberlândia, Uberlânida, MGUniversidade Federal Rural do Rio de Janeiro Instituto de Tecnologia Departamento de Engenharia, Soropédica, RJESALQ USP Universidade Estadual Paulista, Botucatu, SPESALQ USP Universidade Estadual Paulista, Botucatu, SPUniversidade de São Paulo (USP)Universidade Federal de Uberlândia (UFU)Instituto de TecnologiaUniversidade Estadual Paulista (UNESP)Araújo, Mirian Fernandes CarvalhoGuimarães, Ednaldo Carvalhode Carvalho, Daniel Fonsecade Araújo, Lúcio Borges [UNESP]2022-04-28T18:57:23Z2022-04-28T18:57:23Z2009-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article90-100Bioscience Journal, v. 25, n. 4, p. 90-100, 2009.1516-37251981-3163http://hdl.handle.net/11449/2197752-s2.0-84858173608Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengporBioscience Journalinfo:eu-repo/semantics/openAccess2022-04-28T18:57:23Zoai:repositorio.unesp.br:11449/219775Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:52:03.773086Repositório 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 Araújo, Mirian Fernandes Carvalho Climate Multiple regression Rainfall statistics Time series |
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 |
Araújo, Mirian Fernandes Carvalho |
author_facet |
Araújo, Mirian Fernandes Carvalho Guimarães, Ednaldo Carvalho de Carvalho, Daniel Fonseca de Araújo, Lúcio Borges [UNESP] |
author_role |
author |
author2 |
Guimarães, Ednaldo Carvalho de Carvalho, Daniel Fonseca de Araújo, Lúcio Borges [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Federal de Uberlândia (UFU) Instituto de Tecnologia Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Araújo, Mirian Fernandes Carvalho Guimarães, Ednaldo Carvalho de Carvalho, Daniel Fonseca de Araújo, Lúcio Borges [UNESP] |
dc.subject.por.fl_str_mv |
Climate Multiple regression Rainfall statistics Time series |
topic |
Climate Multiple regression Rainfall statistics Time series |
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 |
2009-07-01 2022-04-28T18:57:23Z 2022-04-28T18:57:23Z |
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 |
Bioscience Journal, v. 25, n. 4, p. 90-100, 2009. 1516-3725 1981-3163 http://hdl.handle.net/11449/219775 2-s2.0-84858173608 |
identifier_str_mv |
Bioscience Journal, v. 25, n. 4, p. 90-100, 2009. 1516-3725 1981-3163 2-s2.0-84858173608 |
url |
http://hdl.handle.net/11449/219775 |
dc.language.iso.fl_str_mv |
eng por |
language |
eng por |
dc.relation.none.fl_str_mv |
Bioscience Journal |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
90-100 |
dc.source.none.fl_str_mv |
Scopus 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 |
|
_version_ |
1808129131192254464 |