Coastal communities across the Atlantic could soon receive life-saving warnings up to five days before a hurricane rapidly strengthens, after atmospheric scientists developed a statistical tool that analyses 55 environmental and storm-related factors.Led by researchers at the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR), the team created a prediction model using logistic regression to estimate the chances that a tropical cyclone will suddenly become much stronger.The study, published in the journal Weather and Forecasting under the title An Ensemble-Based Tropical Cyclone Rapid Intensification Prediction Tool for Extended Lead Times, was co-authored by scientists from the University at Albany, State University of New York, and the University Corporation for Atmospheric Research.
Longer warning times for coastal communities
Rapid intensification happens when a hurricane’s maximum sustained winds increase by at least 30 knots (about 35 mph) within 24 hours. Current tools used by the National Hurricane Center usually provide only one to three days of advance warning.“The advantage of this new technique is to provide a tool to forecast rapid intensification even further out,” said NSF NCAR scientist Christopher Rozoff, who led the study. “This can give needed time for those in harm’s way to board up their windows, evacuate, or take other steps to protect lives and property.”The researchers analysed 55 different factors, including sea surface temperatures and upper-level wind shear, using forecasts produced between 2019 and 2024 by NOAA’s Global Ensemble Forecast System.For Atlantic hurricanes, the model successfully predicted the probability of rapid intensification up to five days in advance. For storms in the eastern Pacific, it produced reliable forecasts up to three days ahead.
Mexico Beach in the Florida Panhandle was devastated after Hurricane Michael rapidly intensified and made landfall
Why rapid intensification is hard to predict
Meteorologists have long struggled to forecast rapid intensification, especially when weak storms become extremely powerful just before reaching land.When Hurricane Michael formed in the Gulf of Mexico in 2018, early forecasts predicted winds of less than 70 mph. Instead, the storm quickly strengthened into a Category 5 hurricane with 160 mph winds, devastating the Florida Panhandle and causing $6 billion in damage at Tyndall Air Force Base.Other recent storms show the same challenge:
- Hurricane Harvey (2017): Rapidly strengthened before reaching Texas, bringing record rainfall to Houston and causing $160 billion in damage.
- Hurricane Otis (2023): Intensified unexpectedly into a Category 5 hurricane before striking Acapulco, becoming the costliest Pacific hurricane in Mexico’s history.
- Hurricane Helene (2024): Grew from a weak tropical storm into a Category 4 hurricane in just two days, causing about 250 deaths across several southern U.S. states.
Tracking the most likely storm path
Besides estimating how quickly a hurricane may strengthen, the new model also identifies which forecast track is most likely to experience rapid intensification. This helps meteorologists understand how small changes in a storm’s path could affect the amount of energy it draws from warm ocean waters.The researchers said future work will include testing the model on more historical hurricane seasons and running it with other weather forecasting systems.“There are a variety of ways to strengthen these predictions,” Rozoff said. “The goal is to give forecasters enough information so they have confidence days in advance of when a hurricane is most likely to rapidly intensify.”
Testing forecasts across multiple storm scenarios
Instead of relying on a single forecast, the researchers designed the tool to analyse every member of NOAA’s Global Ensemble Forecast System (GEFS). Ensemble forecasting runs the same weather model several times with slightly different starting conditions, helping scientists estimate the likelihood of different storm outcomes instead of producing just one prediction. The new model calculates the chance of rapid intensification for each projected storm path, giving forecasters a better understanding of both confidence and uncertainty.The team also tested the model using recent storms, including Hurricane Helene (2024) and Hurricane Milton (2024). In these case studies, the system not only estimated the risk of rapid intensification several days in advance but also identified which forecast tracks were most likely to support rapid strengthening. The researchers said showing the environmental conditions behind each prediction helps forecasters understand why the model gives a high or low risk instead of treating it as a “black box.”The next step is to test the model across more hurricane seasons and with additional forecasting systems. If it continues to perform well, the researchers believe it could eventually become part of day-to-day hurricane forecasting, helping emergency officials make better decisions before storms reach the coast.
