Predict Extreme Weather Events in Minutes Without a Supercomputer
Predict Extreme Weather Events in Minutes Without a Supercomputer | NVIDIA Technical Blog
“Scientists from NVIDIA, in collaboration with Lawrence Berkeley National Laboratory (Berkeley Lab), released a machine learning tool called Huge Ensembles (HENS) for extreme-weather prediction that brings supercomputer-class forecasting but at significantly less computational power and cost. Available as open source code or ready-to-run model, it forecasts low-likelihood, high-impact events—from prolonged heat waves to 100-year hurricanes. The technology could help climate scientists, city officials, and emergency managers quickly test scenarios and update response plans with minimal computing resources.
The two-part study published in the journal Geoscientific Model Development, introduces a method called HENS to produce 27,000 years of data and is one of the largest and most reliable ensembles of weather and climate simulations available.
Using NVIDIA PhysicsNeMo, an open source Python framework for building, training, and fine-tuning physics AI models at scale, and Makani open source frameworks, the researchers trained global weather models to refine the HENS methodology…”
Source: developer.nvidia.com/blog/predict-extreme-weather-events-in-minutes-without-a-supercomputer
Code: https://nvidia.github.io/earth2studio/examples/11_huge_ensembles.html