Reamostragem de Séries Pluviométricas no Estado da Paraíba (Resampling series rainfall in the state of Paraiba)
DOI:
https://doi.org/10.5935/1984-2295.20160068Keywords:
Bootstrap, Séries Temporais, ClimatologiaAbstract
As falhas presentes nos dados observacionais das séries históricas meteorológicas podem proporcionar erros na análise e por sua vez, interpretações errôneas dos resultados, indicando falsos valores nas tendências ou períodos de retorno, em eventos extremos como exemplo, principalmente nos estudos das séries temporais pluviométricas. Diante deste trabalho é proposto o preenchimento das falhas em 18 municípios da Paraíba, correspondente ao período de 1935 à 2014. A metodologia utilizada na reamostragem dos dados foi a de bootstrap, no qual utiliza por intermédio de interpolações da série histórica correspondente a cada município, e aos vizinhos mais próximos do mesmo ou os representativos da localidade, no desenvolvimento de uma nova amostragem de dados. Por meio deste método foi possível a realização do preenchimento das falhas, obtendo como resultado principal, uma melhoria na qualidade das séries pluviométricas, devido a aplicação da reamostragem nos meses onde havia ausência de informações.
A B S T R A C T
These gaps in observational data of meteorological time series can provide errors in the analysis and in turn, misinterpretation of results, indicating false values in trends or return periods in extreme events as an example, particularly in studies of rainfall time series. Before this work is proposed to fill the gaps in 18 cities of Paraiba, corresponding to the period 1935 to 2014. The methodology used in the resampling of the data was the bootstrap, which uses through interpolations of the time series of each municipality, and the nearest neighbors of the same or representative of the locality, the development of a new sample data. Through this method it was possible to realize the fulfillment of failures, obtaining as main result, an improvement in the quality of rainfall series, due to application of resampling in the months where there was lack of information.
Keywords: Bootstrap, Time Series, Climatology.
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Copyright (c) 2016 Leydson Galvíncio Dantas, Carlos Antonio Costa dos Santos, Ricardo Alves de Olinda
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