AI is outperforming our best weather forecasting tech, thanks to DeepMind


Data from a multi-decade simulation, called ERA5, is fed into the GraphCast graph network as a set of measurements at a particular point. By traversing the graph, GraphCasts predicts the next measurement for that point and for its neighbors. 


Climatologists have spent decades amassing data on how the weather has changed at points around the globe. Efforts such as ERA5, a record of climate back to 1950, developed by the European Centre for Medium-Range Weather Forecasts (ECMWF), are a kind of simulation of the earth over time, a record of the wind speed, temperature, air pressure, and other variables, hour by hour.

Google’s DeepMind this week is heralding what it calls a turning point in using all that data to make inexpensive predictions of the weather. Running on a single AI chip, Google’s Tensor Processing Unit (TPU), the DeepMind scientists were able to run a program that can predict weather conditions more accurately than a traditional model running on a supercomputer. 

Also: Less is a lot more when it comes to AI, says Google’s DeepMind

The DeepMind paper is published in next week’s issue of the scholarly journal Science, accompanied by a staff article that likens the paper to part of a “revolution” in weather forecasting. 

Mind you, GraphCast, as the program is called, is not a replacement for traditional models of forecasting, according to lead author Remi Lam and colleagues at DeepMind. Instead, they view it as a potential “complement” to existing methods. Indeed, the only reason GraphCast is possible is because human climate scientists built the existing algorithms that were used to “re-analyze,” meaning, go back in time and compile the enormous daily data of ERA5. Without that precision effort to create a world model of weather, there would be no GraphCast.

The challenge Lam and team took on was to take a number of the ERA5 weather records and see if their program, GraphCast, could predict some unseen records better than the gold standard for weather forecasting, a system called HRES, also developed by ECMWF.

HRES, which stands for High RESolution Forecast, predicts the weather for the next 10 days, around the world, using an hour’s worth of work, for an area measuring around 10 kilometers squared. The HRES is made possible because of mathematical models developed over decades by researchers. HRES is “improved by highly trained experts”…