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Use of non-homogeneous Poisson process (NHPP) in presence of change-points to analyze drought periods: a case study in Brazil

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Abstract

Rain precipitation in the last years has been very atypical in different regions of the world, possibly, due to climate changes. We analyze Standard Precipitation Index (SPI) measures (1, 3, 6 and 12-month timescales) for a large city in Brazil: Campinas located in the southeast region of Brazil, São Paulo State, ranging from January 01, 1947 to May 01, 2011. A Bayesian analysis of non-homogeneous Poisson processes in presence or not of change-points is developed using Markov Chain Monte Carlo methods in the data analysis. We consider a special class of models: the power law process. We also discuss some discrimination methods for the choice of the better model to be used for the rain precipitation data.

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Acknowledgments

The authors are very grateful to the Editor and a referee for their helpful and useful comments that improved the manuscript. The first author was partially supported by CNPq-Brazil.

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Authors and Affiliations

  1. Departamento de Medicina Social, FMRP, Universidade de São Paulo, Ribeirão Preto, SP, Brazil

    Jorge Alberto Achcar

  2. Departamento de Matemática, Universidade Tecnológica Federal do Paraná, Cornélio Procópio, PR, Brazil

    Emílio Augusto Coelho-Barros & Roberto Molina de Souza

Authors
  1. Jorge Alberto Achcar
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  2. Emílio Augusto Coelho-Barros
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  3. Roberto Molina de Souza
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Corresponding author

Correspondence to Emílio Augusto Coelho-Barros.

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Handling Editor Bryan F. J. Manly.

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Achcar, J.A., Coelho-Barros, E.A. & de Souza, R.M. Use of non-homogeneous Poisson process (NHPP) in presence of change-points to analyze drought periods: a case study in Brazil. Environ Ecol Stat 23, 405–419 (2016). https://doi.org/10.1007/s10651-016-0345-z

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  • DOI: https://doi.org/10.1007/s10651-016-0345-z

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