Diagnosing Tropical Cyclone Rapid Intensification using Support Vector Machine Classification
The predictors for the statistical models consisted of RPC scores retained from a second RPCA of the MERRA fields, since these represent the variability structure of both RI and non-RI cyclones. In order to diagnose the generalization of the models, a bootstrap cross-validation method was implemented. The resulting analyses revealed model skill that is statistically similar to current classification capabilities of the SHIPS-RII model. Results from this study suggest a possible new approach for improving forecasting of RI using artificial intelligence techniques.