Google recently launched its AI-powered Weather Lab, offering forecasters a new tool better to predict the path and strength of tropical cyclones.

Traditional hurricane models rely on physics-based numerical weather prediction, which involves solving complex equations using supercomputers. These simulations can take hours to generate a single forecast.

In contrast, AI models developed by Google and the European Centre for Medium-Range Weather Forecasts (ECMWF) aim to produce similarly accurate forecasts in a fraction of the time and with significantly less computational power. Google’s model, for example, can generate a 15-day forecast in about a minute.

Built on a neural network inspired by the human brain, Google’s AI model is trained on decades of historical weather data. It uses advanced pattern recognition to generate multiple forecast scenarios.

According to Google, its AI system is “as accurate as, and often more accurate than, current physics-based methods.”

When local news station WFLA tested the model’s track forecasts for Hurricanes Helene and Milton, the predictions were within just a few miles of the storms’ actual paths. However, both storms followed relatively straightforward trajectories, and most traditional models produced similar results.

The model’s intensity forecast was less reliable. It underestimated Hurricane Milton’s strength—highlighting a common challenge for all forecasting methods, AI or otherwise.

To improve its performance, Google is working with the National Hurricane Center (NHC) to validate the AI model’s predictions.

“NHC expert forecasters are now seeing live predictions from our experimental AI models, alongside other physics-based models and observations,” Google said in a news release. “We hope this data can help improve NHC forecasts and provide earlier and more accurate warnings for hazards linked to tropical cyclones.”

Meanwhile, the Atlantic remains quiet, with no tropical development expected in the next seven days.

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(Image credit: Google)

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