Predicting Extreme Weather Risk Three Weeks in Advance With FourCastNet

A small 50-member ensemble takes one hour to generate on a large supercomputer using traditional numerical simulations. But small ensembles often miss low-probability, high-impact events.

By running FourCastNet—an AI framework developed by researchers at NVIDIA, Caltech, and Lawrence Berkeley Lab—in NVIDIA Modulus, and leveraging FNO, we were able to generate 21-day global weather trajectories of 1,000 ensemble members in a tenth of the time it previously took to do a single trajectory, while using 1,000X less energy.

In this demo, …

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