Deterministic to Probabilistic Statistical Rapid Intensification Index (DTOPS): A New Method for Forecasting RI Probability

A new statistical scheme for forecasting the likelihood of rapid intensification (RI) has been developed. The Deterministic to Probabilistic Statistical Model (DTOPS) uses forecast guidance from five models that are frequently used in tropical cyclone forecasting: ECMWF, GFS, HWRF, LGEM, and SHIPS. The intensity change forecasted by these models along with several other geographic or multi-model parameters were compiled for numerous cases from 2010 – 2016 in the Atlantic and East-Pacific basins. These forecasts were compared to Best Track intensity change and binomial logistic regression was used to derive coefficients for each model or parameter. These coefficients then are used for the multi-model logistic prediction scheme. Brier skill scores (BSS) for various RI thresholds computed from the 2014 – 2016 portion of the dependent data set show that DTOPS performed similarly or better than the operationally used SHIPS-RII scheme. The largest improvements (when compared to SHIPS-RII) occurred in the Atlantic basin where substantial BSS improvements were obtained. DTOPS was run experimentally at the National Hurricane Center during the 2017 hurricane season and these results will be discussed. Preliminary results suggest that DTOPS may be a useful tool for diagnosing the likelihood of RI in the operational hurricane forecasting environment.