An ensemble-based tropical cyclone rapid intensification prediction tool for extended lead times
Rozoff, C. M., Vigh, J., Hendricks, E. A., Freeman, B., Kucera, P. A.. (2026). An ensemble-based tropical cyclone rapid intensification prediction tool for extended lead times. Weather and Forecasting, doi:https://doi.org/10.1175/waf-d-25-0076.1
| Title | An ensemble-based tropical cyclone rapid intensification prediction tool for extended lead times |
|---|---|
| Genre | Article |
| Author(s) | Christopher M. Rozoff, Jonathan Vigh, Eric A. Hendricks, B. Freeman, Paul A. Kucera |
| Abstract | Reliable predictions of tropical cyclone (TC) rapid intensification (RI) have long tantalized the research and forecasting communities. In recent years, considerable advances have been achieved in the probabilistic prediction of RI from the current time through the subsequent 24, 48, or even 72 h. It is thus natural to ask whether probabilistic methods may prove reliable in indicating RI episodes starting at more distant lead times. This question is particularly important in the case of a TC still in its formative stages. The present study addresses the prediction of RI at extended lead times using a logistic regression model that incorporates both environmental and inner-storm structure characteristics as prognostic indicators. These predictors are derived from the Global Ensemble Forecast System (GEFS) of the National Oceanic and Atmospheric Administration and a limited set of observations. In particular, the control member of the GEFS is used to derive and evaluate the model against observations. Drawing on data spanning 2019–24, the resulting lead-time-dependent logistic regression models derived for the Atlantic and eastern Pacific basins demonstrate skillful predictions of 24-h RI periods out to 120 h. Moreover, the regression scheme derived from the control member may be extended to the entire GEFS ensemble, yielding probabilistic estimates of RI along each forecasted track out to the same temporal horizon. Plots of the evolving values of relevant predictors along these trajectories further confer a measure of physical insight into the probabilities obtained, thereby linking statistical inference with dynamical interpretation. Significance Statement This paper describes a simple probabilistic tool for anticipating tropical cyclone rapid intensification (RI) at extended forecast intervals. The prediction of RI episodes starting at such later leads has not hitherto been a capability in operational forecasting. In spite of its simplicity, this probabilistic model demonstrates skillful RI prediction at extended forecast horizons. |
| Publication Title | Weather and Forecasting |
| Publication Date | May 1, 2026 |
| Publisher's Version of Record | https://doi.org/10.1175/waf-d-25-0076.1 |
| OpenSky Citable URL | https://n2t.net/ark:/85065/d7hd8162 |
| OpenSky Listing | View on OpenSky |
| RAL Affiliations | NSAP |