Thursday, 1 May 2008: 1:45 PM
Palms GF (Wyndham Orlando Resort)
Rapid Intensifications (RI) of tropical cyclones (TC) provide major error sources in the challenging TC intensity forecasting. There are many factors affecting the RI process of TCs, and identifying the combination of conditions most favorable to RI development is very time consuming when using traditional statistical data analysis methods. Data mining techniques have been implemented in the analysis of RI of TCs, and a simpler combined condition is identified, which gives a higher RI probability than a more complex condition from ordinary statistical analysis. Moreover, the data mining technique can be used to identify the optimal RI conditions when the number of affecting factors is given. The variation of RI probabilities with the factor numbers leads to a saturation stage, and individual cases are traced back for the cases with the globally most favorable RI conditions. In this paper, we will report the most recent findings through the data mining technique based on the data for SHIPS (Statistical Hurricane Intensity Prediction Scheme), an operational statistical-dynamical hurricane intensity forecasting model.
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