THE MONTHLY RAINFALL IN THE RIO DE JANEIRO STATE, BRAZIL: SEASONALITY AND TREND


Autoria(s): ARAUJO, Mirian Fernandes Carvalho; GUIMARAES, Ednaldo Carvalho; CARVALHO, Daniel Fonseca de; ARAUJO, Lucio Borges de
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

18/10/2012

18/10/2012

2009

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.

Identificador

BIOSCIENCE JOURNAL, v.25, n.4, p.90-100, 2009

1516-3725

http://producao.usp.br/handle/BDPI/19398

http://apps.isiknowledge.com/InboundService.do?Func=Frame&product=WOS&action=retrieve&SrcApp=EndNote&UT=000269317400012&Init=Yes&SrcAuth=ResearchSoft&mode=FullRecord

Idioma(s)

por

Publicador

UNIV FEDERAL UBERLANDIA

Relação

Bioscience Journal

Direitos

openAccess

Copyright UNIV FEDERAL UBERLANDIA

Palavras-Chave #Climate #Time series #Rainfall statistics #Multiple regression #Agriculture, Multidisciplinary #Agronomy #Biology
Tipo

article

original article

publishedVersion