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

Serving as lead forecaster on duty, he forecasted that in a single day the storm would become a severe hurricane and begin a turn towards the Jamaican shoreline. No forecaster had previously made such a bold prediction for quick intensification.

But, Papin had an ace up his sleeve: AI technology in the guise of the tech giant’s recently introduced DeepMind cyclone prediction system – released for the first time in June. True to the forecast, Melissa did become a storm of remarkable power that tore through Jamaica.

Growing Reliance on Artificial Intelligence Forecasting

Meteorologists are heavily relying upon the AI system. During 25 October, Papin clarified in his official briefing that Google’s model was a key factor for his certainty: “Roughly 40/50 Google DeepMind ensemble members show Melissa becoming a Category 5 hurricane. Although I am unprepared to forecast that strength at this time given path variability, that remains a possibility.

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

Outperforming Conventional Systems

The AI model is the first AI model dedicated to hurricanes, and now the first to beat traditional weather forecasters at their own game. Through all 13 Atlantic storms so far this year, Google’s model is top-performing – surpassing experts on track predictions.

Melissa eventually made landfall in Jamaica at maximum strength, one of the strongest landfalls recorded in nearly two centuries of record-keeping across the region. Papin’s bold forecast probably provided residents extra time to get ready for the catastrophe, possibly saving people and assets.

The Way The System Works

Google’s model works by identifying trends that traditional time-intensive scientific prediction systems may miss.

“They do it much more quickly than their traditional counterparts, and the computing power is more affordable and time consuming,” said Michael Lowry, a former forecaster.

“What this hurricane season has proven in quick time is that the recent AI weather models are competitive with and, in some cases, more accurate than the slower physics-based forecasting tools we’ve traditionally leaned on,” he added.

Understanding AI Technology

It’s important to note, Google DeepMind is an example of AI training – a technique that has been employed in data-heavy sciences like weather science for years – and is not generative AI like ChatGPT.

Machine learning takes large datasets and extracts trends from them in a such a way that its model only requires minutes to generate an answer, and can do so on a standard PC – in strong contrast to the flagship models that authorities have used for years that can take hours to run and need the largest supercomputers in the world.

Expert Reactions and Upcoming Advances

Still, the reality that Google’s model could exceed earlier top-tier legacy models so rapidly is nothing short of amazing to meteorologists who have dedicated their lives trying to predict the world’s strongest weather systems.

“I’m impressed,” said James Franklin, a retired expert. “The sample is sufficient that it’s pretty clear this is not just chance.”

He said that while Google DeepMind is beating all other models on predicting the trajectory of hurricanes globally this year, similar to other systems it occasionally gets high-end intensity predictions wrong. It had difficulty with Hurricane Erin earlier this year, as it was also undergoing rapid intensification to category 5 above the Caribbean.

In the coming offseason, he stated he intends to discuss with Google about how it can enhance the AI results more useful for experts by offering additional internal information they can utilize to evaluate the reasons it is producing its conclusions.

“The one thing that nags at me is that while these predictions appear highly accurate, the output of the model is kind of a opaque process,” remarked Franklin.

Wider Industry Trends

Historically, no a private, for-profit company that has developed a top-level forecasting system which grants experts a view of its techniques – unlike most systems which are offered free to the public in their entirety by the authorities that created and operate them.

Google is not the only one in starting to use artificial intelligence to address difficult weather forecasting problems. The authorities are developing their respective artificial intelligence systems in the works – which have demonstrated improved skill over previous traditional systems.

Future developments in artificial intelligence predictions seem to be new firms tackling previously tough-to-solve problems such as sub-seasonal outlooks and improved early alerts of tornado outbreaks and flash flooding – and they are receiving US government funding to pursue this. A particular firm, WindBorne Systems, is even launching its proprietary weather balloons to fill the gaps in the national monitoring system.