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    
  •  Ariana Morais Neves    


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.

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