Google’s new AI weather model could redefine how we predict and prepare for changing conditions.
Google DeepMind, the company’s AI research division focused on solving scientific problems, announced on Dec. 4 a new AI weather model called GenCast, which promises to provide more accurate probabilities of different weather conditions up to 15 days in advance.
Although weather forecasting typically involves physics-based models, which can take hours to compute on massive supercomputers, Google said it aims to achieve greater accuracy in only minutes. GenCast can generate a 15-day forecast scenario in just eight minutes using a Google Cloud Tensor processing unit chip, according to the company.
GenCast is part of Google’s expanding AI-powered weather model suite, which includes enhancing Google Search and Maps with improved forecasting for precipitation, wildfires, flooding and extreme heat.
Details of its latest testing were published in the journal Nature.
Although Google’s AI model provided one best estimate of future weather, GenCast uses probability-based forecasting with 50 or more predictions of how the weather may change and assessing the likelihood of those scenarios. The technology runs on a diffusion model, similar to the machine-learning models used in generative AI.
“We trained it on 40 years of historical data from [the European Centre for Medium-Range Weather Forecasts], which included variables such as temperature, wind speed, and pressure at various altitudes — enabling it to learn,” the company explained in a tweet.
When predicting extreme heat, cold and high wind speeds, Google said GenCast outperformed current forecasting models. It also noted that it delivers “superior predictions” of the path of tropical cyclones up to five days in advance.
