Improved short-term Atlantic hurricane intensity forecasts using reconnaissance-based core measurements

While tropical cyclone (TC) track forecasting has improved noticeably over the last 20 years, intensity forecasting has remained somewhat of an enigma to forecasters. Despite increased computing capabilities and more sophisticated dynamical models, statistical models, such as the Statistical Hurricane Intensity Prediction Scheme (SHIPS), still often outperform their dynamical counterparts. There has been a great deal of research focused on improving intensity forecasts of TCs during the past two decades. However, the overwhelming majority of this statistical research has focused on the impacts of the storm environment rather than on the effects of the TC structure itself or inner-core measurements. More focus has been placed recently on using some of these measurements from within the TC core, such as the structure of the storm and reconnaissance flight data. Still, much work remains to be done to fully utilize the available data from the inner core of TCs.

This research seeks to develop a new statistical-climatological forecasting scheme to improve short-term intensity forecasts for well-developed (having a defined eye) TCs in the Atlantic basin. Using Vortex Data Messages (VDMs) gathered by Hurricane Hunter reconnaissance flights and stored in the National Hurricane Center's Automated Tropical Cyclone Forecast (ATCF) archives, a VDM climatology from 1991-2008 is developed and exploited. This climatology includes storm-scale thermodynamic parameters to aid in TC prediction. Finally, stepwise multiple regression is performed to create a SHIPS-style intensity forecast model--Atlantic-based Statistical Prediction of Hurricane Intensity using Recon, or ASPIRE.

Cross validation results show that the ASPIRE technique outperforms SHIPS at nearly every forecast time (12-48 hours) and initial intensity, potentially indicating that a new benchmark for TC intensity forecasting may have been attained.