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As Tropical Storm Melissa swirled off the coast of Haiti, meteorologist Philippe Papin felt certain it was about to escalate to a monster hurricane.

As the primary meteorologist on duty, he forecasted that in a single day the storm would become a category 4 hurricane and start shifting towards the coast of Jamaica. Not a single expert had ever issued this confident prediction for rapid strengthening.

However, Papin possessed a secret advantage: AI technology in the guise of the tech giant’s new DeepMind hurricane model – released for the first time in June. True to the forecast, Melissa did become a storm of remarkable power that tore through Jamaica.

Increasing Dependence on AI Predictions

Meteorologists are heavily relying upon the AI system. During 25 October, Papin clarified in his official briefing that the AI tool was a primary reason for his confidence: “Roughly 40/50 AI simulation runs show Melissa becoming a Category 5 hurricane. Although I am not ready to predict that intensity yet given track uncertainty, that is still plausible.

“It appears likely that a period of rapid intensification is expected as the system drifts over very warm sea temperatures which is the most extreme marine thermal energy in the whole Atlantic basin.”

Outperforming Traditional Models

The AI model is the pioneer artificial intelligence system focused on hurricanes, and now the first to beat traditional weather forecasters at their specialty. Across all 13 Atlantic storms this season, Google’s model is the best – even beating experts on track predictions.

The hurricane ultimately struck in Jamaica at category 5 intensity, one of the strongest coastal impacts recorded in almost 200 years of data collection across the Atlantic basin. Papin’s bold forecast likely gave people in Jamaica extra time to get ready for the catastrophe, potentially preserving lives and property.

How The Model Functions

Google’s model operates through identifying trends that traditional time-intensive physics-based weather models may overlook.

“They do it far faster than their physics-based cousins, and the computing power is less expensive and time consuming,” stated Michael Lowry, a former forecaster.

“This season’s events has demonstrated in quick time is that the newcomer artificial intelligence systems are competitive with and, in some cases, superior than the less rapid traditional forecasting tools we’ve traditionally leaned on,” Lowry said.

Clarifying Machine Learning

To be sure, the system is an instance of AI training – a technique that has been used in research fields like weather science for a long time – and is not generative AI like ChatGPT.

Machine learning takes large datasets and extracts trends from them in a such a way that its system only takes a few minutes to come up with an result, and can do so on a standard PC – in strong contrast to the flagship models that governments have utilized for decades that can require many hours to run and require the largest supercomputers in the world.

Expert Responses and Future Advances

Nevertheless, the fact that Google’s model could outperform earlier top-tier traditional systems so rapidly is truly remarkable to weather scientists who have spent their careers trying to predict the most intense storms.

“It’s astonishing,” said James Franklin, a former forecaster. “The sample is sufficient that it’s pretty clear this is not a case of chance.”

Franklin said that while Google DeepMind is outperforming all other models on forecasting the trajectory of storms globally this year, like many AI models it occasionally gets extreme strength forecasts wrong. It had difficulty with Hurricane Erin earlier this year, as it was similarly experiencing rapid intensification to maximum intensity above the Caribbean.

During the next break, Franklin said he intends to talk with Google about how it can enhance the AI results even more helpful for forecasters by providing additional under-the-hood data they can utilize to assess the reasons it is producing its conclusions.

“The one thing that troubles me is that although these forecasts appear really, really good, the output of the system is kind of a opaque process,” remarked Franklin.

Broader Sector Trends

Historically, no a private, for-profit company that has developed a top-level weather model which allows researchers a view of its techniques – unlike nearly all systems which are provided free to the public in their full form by the authorities that created and operate them.

Google is not the only one in adopting artificial intelligence to address difficult weather forecasting problems. The authorities also have their respective AI weather models in the works – which have demonstrated improved skill over earlier traditional systems.

Future developments in artificial intelligence predictions appear to involve startup companies taking swings at previously tough-to-solve problems such as sub-seasonal outlooks and better advance warnings of tornado outbreaks and sudden deluges – and they have secured US government funding to pursue this. One company, WindBorne Systems, is even launching its own weather balloons to address deficiencies in the national monitoring system.