Nvidia · NVIDIA Blog
University of Manchester Taps NVIDIA Earth-2 to Forecast Air Pollution Across the UK
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Air pollution is a serious public health risk, contributing to an estimated 30,000 deaths in the U.K. alone last year.
Key facts
- Working with the NVIDIA Earth-2 team, Topping and colleagues generated training data from existing chemistry-climate simulations, then trained Earth-2 CorrDiff, a generative downscaling model
- To retrain the Earth-2 model for air pollution, Topping and the team used a year’s worth of U.K. pollution data simulated at hourly intervals to generate a detailed, U.K.-wide pollution model
- Earth-2 CorrDiff has shown an incredibly efficient use of the world-class NVIDIA hardware inside Isambard-AI,” said Simon McIntosh-Smith, director of the Bristol Centre for Supercomputing
- The team has since added Earth-2 StormCast, a model that enables time-dependent forecasts that directly use air quality observations, and showed the test-training and inference workflows running
Summary
David Topping, a professor in the University of Manchester’s department of Earth and environmental science, saw that the NVIDIA Earth-2 family of open AI models and tools had cracked a related problem for weather forecasting, and asked whether the same generative frameworks could work for pollution fields. “The biggest challenge is the compute required to forecast air quality,” said Topping. Working with the NVIDIA Earth-2 team, Topping and colleagues generated training data from existing chemistry-climate simulations, then trained Earth-2 CorrDiff, a generative downscaling model, on Isambard-AI, the U.K.’s national AI supercomputer in Bristol. The team has since added Earth-2 StormCast, a model that enables time-dependent forecasts that directly use air quality observations, and showed the test-training and inference workflows running on the NVIDIA DGX Spark personal AI supercomputer.