John Kaplan presented a seminar on “Investigating the variability in skill of operational statistical rapid intensification (RI) prediction models” that is available on the NHC science presentation web site.
Despite recent improvements in tropical cyclone (TC) intensity forecasting skill, predicting changes in TC intensity remains problematic particularly the forecasting of episodes of rapid intensification (RI) which the National Hurricane Center (NHC) has declared as its highest operational forecasting priority.
In recent years, a statistical rapid intensification index (SHIPS-RII) that employs environmental data from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) to estimate the probability of RI has been developed based upon linear discriminant analysis. Although the SHIPS-RII is currently employed as an operational forecasting tool by the NHC its utility has been somewhat restricted since the original version only provided probabilistic forecasts for the single lead time of 24 h. Thus, additional versions of the SHIPS-RII as well as new logistic regression and Bayesian RI models have been recently developed for the added lead times of 12-h, 36-h, and 48-h. These new multi-lead time RI models are expected to become operational during the 2016 Hurricane Season.
In our upcoming presentation, a brief description of the new RI models as well as an assessment of their overall level skill will be provided. In addition, an analysis of the environmental conditions and initial tropical cyclone structure is performed to investigate whether differences in either of these factors appear to contribute to the observed variability in predictive skill of the statistical RI models. Preliminary results from this analysis will also be presented.