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When Developing Cyclone Melissa was churning south of Haiti, meteorologist Philippe Papin had confidence it would soon grow into a monster hurricane.

Serving as lead forecaster on duty, he predicted that in just 24 hours the storm would become a category 4 hurricane and begin a turn towards the coast of Jamaica. Not a single expert had ever issued such a bold forecast for rapid strengthening.

However, Papin had an ace up his sleeve: AI technology in the form of the tech giant’s new DeepMind hurricane model – released for the first time in June. And, as predicted, Melissa did become a system of astonishing strength that ravaged Jamaica.

Increasing Dependence on AI Forecasting

Forecasters are heavily relying upon Google DeepMind. During 25 October, Papin explained in his official briefing that Google’s model was a key factor for his certainty: “Approximately 40/50 Google DeepMind ensemble members show Melissa reaching a Category 5 hurricane. While I am unprepared to forecast that strength yet given path variability, that is still plausible.

“There is a high probability that a phase of quick strengthening will occur as the system drifts over exceptionally hot sea temperatures which is the most extreme oceanic heat content in the whole Atlantic basin.”

Outperforming Conventional Systems

The AI model is the pioneer artificial intelligence system focused on tropical cyclones, and now the initial to beat traditional meteorological experts at their specialty. Across all tropical systems so far this year, Google’s model is the best – even beating experts on track predictions.

The hurricane ultimately struck in Jamaica at maximum strength, among the most powerful landfalls recorded in nearly two centuries of data collection across the region. The confident prediction probably provided people in Jamaica extra time to get ready for the catastrophe, potentially preserving lives and property.

How The Model Functions

The AI system works by spotting patterns that traditional lengthy scientific weather models may miss.

“The AI performs far faster than their traditional counterparts, and the computing power is less expensive and demanding,” stated Michael Lowry, a ex forecaster.

“What this hurricane season has proven in quick time is that the recent artificial intelligence systems are competitive with and, in certain instances, more accurate than the slower physics-based weather models we’ve traditionally leaned on,” he added.

Clarifying Machine Learning

It’s important to note, Google DeepMind is an instance of AI training – a method that has been employed in research fields like meteorology for years – and is not generative AI like ChatGPT.

Machine learning processes mounds of data and extracts trends from them in a such a way that its system only requires minutes to come up with an answer, and can operate on a desktop computer – in sharp difference to the primary systems that authorities have utilized for decades that can take hours to run and require the largest high-performance systems in the world.

Expert Reactions and Upcoming Developments

Nevertheless, the reality that Google’s model could exceed previous gold-standard traditional systems so quickly is truly remarkable to weather scientists who have dedicated their lives trying to forecast the most intense weather systems.

“I’m impressed,” said James Franklin, a former expert. “The sample is sufficient that it’s pretty clear this is not a case of beginner’s luck.”

Franklin noted that although Google DeepMind is beating all competing systems on predicting the trajectory of hurricanes worldwide this year, like many AI models it sometimes errs on extreme strength predictions wrong. It had difficulty with another storm earlier this year, as it was also undergoing quick strengthening to maximum intensity north of the Caribbean.

During the next break, Franklin stated he plans to talk with Google about how it can make the AI results more useful for experts by providing extra internal information they can use to assess exactly why it is producing its conclusions.

“The one thing that nags at me is that although these forecasts seem to be really, really good, the output of the system is essentially a black box,” remarked Franklin.

Wider Industry Developments

There has never been a commercial entity that has developed a high-performance forecasting system which grants experts a view of its techniques – in contrast to most other models which are offered at no cost to the general audience in their entirety by the governments that created and operate them.

Google is not alone in starting to use artificial intelligence to solve challenging meteorological problems. The authorities also have their respective AI weather models in the works – which have also shown better performance over earlier traditional systems.

The next steps in artificial intelligence predictions seem to be startup companies tackling previously tough-to-solve problems such as long-range forecasts and better early alerts of severe weather and sudden deluges – and they are receiving US government funding to pursue this. One company, WindBorne Systems, is also deploying its own weather balloons to address deficiencies in the national monitoring system.