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Severe Precipitation in Brazil: Data Mining Approach

In: Integral Methods in Science and Engineering, Volume 2

Author

Listed:
  • H. Musetti Ruivo

    (National Institute for Space Research (INPE))

  • H. F. de Campos Velho

    (National Institute for Space Research (INPE))

  • S. R. Freitas

    (National Aeronautics and Space Administration (NASA))

Abstract

Data mining approach is applied to evaluate extreme rainfall events in the Brazil. Statistical analysis is combined with an artificial intelligence technique to identify the most relevant meteorological variables for a local severe precipitation in the Rio de Janeiro state (Brazil): Rio de Janeiro and Nova Friburgo cities. The p-value statistical technique is employed to select a much smaller subset of climatic variables, preserving the information associated with extreme meteorological events. A decision tree algorithm is used as a model to identify the precipitation severity. The method is tested with the events at Apr/2010 (Rio de Janeiro city) and at Jan/2011 (Nova Friburgo city). In both cases, our results show a good local analysis for extreme precipitation episodes.

Suggested Citation

  • H. Musetti Ruivo & H. F. de Campos Velho & S. R. Freitas, 2017. "Severe Precipitation in Brazil: Data Mining Approach," Springer Books, in: Christian Constanda & Matteo Dalla Riva & Pier Domenico Lamberti & Paolo Musolino (ed.), Integral Methods in Science and Engineering, Volume 2, chapter 0, pages 221-231, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-59387-6_22
    DOI: 10.1007/978-3-319-59387-6_22
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