SyncAI.news, a Varaisys broadcasting
How WeatherNext helped the National Hurricane Center better predict Hurricane Melissa’s historic landfall in Jamaica
GD

Google DeepMind

· 1 min read

AI LabsGoogle DeepMind

How WeatherNext helped the National Hurricane Center better predict Hurricane Melissa’s historic landfall in Jamaica

May 19, 2026 Science

WeatherNext team

The National Hurricane Center was able to issue advanced weather warnings to give communities in Jamaica additional lead time to prepare, evacuate, and help protect livelihoods

In October 2025, Hurricane Melissa made history. It was the strongest hurricane on record to land in Jamaica and tied for the strongest hurricane in the Atlantic.

The National Hurricane Center’s (NHC) forecast also marked a historic milestone. For the first time, they predicted a storm would reach Category 5 intensity starting from Category 1 wind speed. Our AI model WeatherNext helped the NHC make this decision by predicting the storm’s rapid intensification and landfall in Jamaica with high confidence—and most critically, this prediction came five days in advance.

Predicting dangerous storms earlier and more accurately helps teams on the ground to better mobilize resources and coordinate evacuations effectively.

The challenge of rapid intensification

Predicting a storm’s path is difficult, but predicting a sudden jump in strength - known as “rapid intensification” - is even harder. This occurs when a hurricane's winds increase by at least 35 mph in just 24 hours. These events are very difficult to predict and also exceedingly dangerous because a weak system can transform into a major hurricane overnight, leaving little time to prepare.

Historically, meteorologists faced a trade-off: larger global models were excellent at predicting a storm’s path, but often lacked the resolution to see the small-scale thunderstorms that drove its “engine”. Conversely, high-resolution local models could better see intensity, but lacked global context for accurate track forecasting. This meant that models either excelled at predicting a tropical cyclone's track, or its intensity, but not both.

Original source

This story was published by Google DeepMind. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on deepmind.google

Similar News