Probabilistic Modeling of Monthly Temperature Historical Series in Mossoró, Northeastern Brazil

Janilson Pinheiro de Assis, Roberto Pequeno de Sousa, Ben Deivide de Oliveira Batista, Paulo César Ferreira Linhares, Eudes de Almeida Cardoso, José Aluisio de Araújo Paula and Ariana Morais Neves

Journal of Agricultural Science, 2024, vol. 10, issue 12, 534

Abstract: We fitted the following seven distribution probabilities to the data of monthly average temperature in Mossoró, northeastern Brazil- Normal, Log-Normal, Beta, Gamma, Log-Pearson (Type III), Gumbel, and Weibull. To assess the goodness of fit the empirical distributions to the theoretical distribution, we applied the tests of Kolmogorov-Smirnov, Chi-square, Cramer-von Mises, Anderson-Darling, Kuiper, and Logarithm of Maximum Likelihood, at 10% of probability. The temperature series were obtained from 1970 to 2007. The Normal distribution provided the best fit to the historical series of average monthly temperature. Although the Kolmogorov-Smirnov test showed a very high level of approval, which generated some uncertainty regarding the test criteria, it is the more recommended to studies with approximately symmetric data and small series.

Date: 2024
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