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/2009 (Rio de Janeiro city) and at Jan/2011 (Nova Friburgo city). In both cases, our results show a good local analysis for extreme precipition episodes.
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