Google builds an AI model that can predict future weather catastrophes

Google has released an artificial intelligence (AI) model that it claims can generate accurate weather forecasts at scale — while being cheaper than conventional physics-based forecasting.

The "Scalable Ensemble Envelope Diffusion Sampler" (SEEDS) model is designed similarly to popular large language models (LLMs) like ChatGPT and generative AI tools like Sora — which generates videos from text prompts.

SEEDS generates many ensembles — or multiple weather scenarios — much quicker and cheaper than traditional predicting models can. The team described its findings in a paper published March 29 in the journal Science Advances. 

Weather is difficult to predict, with many variables that can lead to potentially devastating weather events — from hurricanes to heat waves. As climate change worsens and extreme weather events become more common, accurately predicting the weather can save lives by giving people time to prepare for the worst effects of natural disasters.

Physics-based predictions currently used by weather services collect various measurements and give a final prediction that averages many different modeled predictions —  or an ensemble — based on all the variables. Instead of a single forecast, weather forecasting is based on a set of predictions per forecast cycle that provides a range of possible future states.

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This means most weather predictions are accurate enough for more common conditions like mild weather or warm summer days, but generating enough forecast models to find the likely outcome of an extreme weather event is out of the reach of most services.