In early June, shortly after the beginning of the Atlantic hurricane season, Google unveiled a new model designed specifically to forecast the tracks and intensity of tropical cyclones.
Part of the Google DeepMind suite of AI-based weather research models, the “Weather Lab” model for cyclones was a bit of an unknown for meteorologists at its launch. In a blog post at the time, Google said its new model, trained on a vast dataset that reconstructed past weather and a specialized database containing key information about hurricanes tracks, intensity, and size, had performed well during pre-launch testing.
“Internal testing shows that our model’s predictions for cyclone track and intensity are as accurate as, and often more accurate than, current physics-based methods,” the company said.
Google said it would partner with the National Hurricane Center, an arm of the National Oceanic and Atmospheric Service that has provided credible forecasts for decades, to assess the performance of its Weather Lab model in the Atlantic and East Pacific basins.
All eyes on Erin
It had been a relatively quiet Atlantic hurricane season until a few weeks ago, with overall activity running below normal levels. So there were no high-profile tests of the new model. But about 10 days ago, Hurricane Erin rapidly intensified in the open Atlantic Ocean, becoming a Category 5 hurricane as it tracked westward.
From a forecast standpoint, it was pretty clear that Erin was not going to directly strike the United States, but meteorologists sweat the details. And because Erin was such a large storm, we had concerns about how close Erin would get to the East Coast of the United States (close enough, it turns out, to cause some serious beach erosion) and its impacts on the small island of Bermuda in the Atlantic.
