Validade da Estatística na Compreensão do Clima para Diagnóstico e Previsão (Validity of statistics in understanding the climate for diagnosis and forecasting)
DOI:
https://doi.org/10.26848/rbgf.v.10.5.p1346-1354Keywords:
Climatologia – Modelo linear, Precipitação, Previsão do tempoAbstract
A proposta deste artigo é o desenvolvimento instrumental integrado de conhecimentos, buscando desvendar parte da complexidade atmosférica que cerca a Climatologia, a Agrometeorologia e a Geografia, com técnicas estatísticas aplicadas a previsão do tempo, especialmente direcionadas para a Agricultura e tendo como variável a precipitação pluviométrica. A modelagem estatística da variável resposta precipitação em relação às médias mensais é aplicada em 40 municípios do Estado de Sergipe, considerando 100 anos de observações, nos 12 meses do ano, anual e períodos seco e chuvoso. Verifica-se um bom desempenho dos modelos, onde todos os valores apresentados estão próximos de zero, indicando menor erro. Os valores médios que representam o período com maior intensidade de precipitação estão entre os meses de Abril a Agosto. O melhor modelo apresentado foi para o mês de outubro, com 82,72% de associação entre as variáveis.
A B S T R A C T
The purpose of this article is the integrated instrumental development of knowledge, seeking to unravel part of atmospheric complexity surrounding the Climatology, the Agrometeorology and Geography, with statistical techniques applied the weather forecast, especially directed to the Agriculture and having as variable rainfall. Statistical modeling of variable rainfall response in relation to the monthly average is applied in 40 municipalities of the State of Sergipe, considering 100 years of observations in the 12 months of the year, annual and dry and rainy seasons. There is a good performance of the models, which all displayed values are close to zero, indicating minor error. Average values that represent the period with higher intensity of rainfall are between the months of April to August. The best model was presented for the month of October, with 82.72 % of the association between variables.
Keywords: climatology - linear model - precipitation – weather forecast.
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Copyright (c) 2017 Eucymara França Nunes Santos, Inajá Francisco de Souza, Josefa Eliane Santana de Siqueira Pinto, Paulo José Duarte Neto
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