Google's GenCast AI turns spotlight on powerful new weather forecasters Explained

The story so far: On December 4, Google DeepMind unveiled GenCast, an artificial intelligence (AI) model the company said could forecast the weather better than most existing tools as well as more days in advance.

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Details of the model were published in a peer-reviewed paper in the journal Nature.

How do we forecast weather?

“Weather predictions ... are produced by running multiple numerical simulations of the atmosphere,” Vassili Kitsios, senior research scientist at the Commonwealth Scientific and Industrial Research Organisation of Australia, wrote earlier this month. “Each simulation starts from a slightly different estimate of the current weather. This is because we don't know exactly what the weather is at this instant everywhere in the world. ... By solving equations describing the fundamental physical laws of nature, the simulations predict what will happen in the atmosphere.” This process is called numerical weather prediction (NWP). The best NWP forecasts require the use of powerful supercomputers as well as high-quality data about the weather at a particular location. Even then NWPs can predict the weather only a week or so in advance.

Ensemble forecasts entered the picture in the 1990s. Here, scientists use an NWP model to produce multiple forecasts at a certain location in time, with different starting conditions. This collection of forecasts is called an ensemble and indicates the range of meteorological possibilities.

How does GenCast perform?