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Nvidia's CorrDiff uses AI to generate higher resolution local weather forecasting

A team of engineers and weather specialists at Nvidia, working with a colleague from Taiwan's Central Weather Administration, has developed a new AI app aimed specifically at generating higher resolution local weather forecasting. In their paper in Communications Earth & Environment, the group describes their two-step approach to developing a better local weather forecasting system.

Over the past several decades, weather forecasting has improved dramatically, at least in developed countries. Advances in software, hardware and weather modeling have led to the creation of numerical-based modeling systems running on massive supercomputers that produce extremely accurate weather forecasts—in a macro sense.

Local weather prediction is still waiting for improvement, especially in places distant from large metropolitan areas, due to the huge cost that would be involved in using supercomputers to make such predictions.

The team at Nvidia has developed a weather forecasting system they call Corrective Diffusion (CorrDiff) that combines the best features of the massive computer models with artificial intelligence. It works by downscaling global weather predictions to a more local level, and then improving their resolution—and does so at far lower cost than traditional systems.

The two-step approach taken by the team involves the use of a deterministic AI mode that produces output based on a given input—no randomness is involved. The predictions it makes are based on weather behavior patterns that have been learned over time. The second step involves fine-tuning the output from the first step using a generative diffusion model.

By using the same basic repetitive techniques used by chatbots to learn how to answer queries more intelligently, the system produces higher and higher resolution results. The result is a system that brings macro-scale accuracy to the local or regional level.

The system was tested against several conventional models and was found to provide similar results—the difference was in the much lower cost associated with such results and the speed with which it delivered them.

The team at Nvidia suggests their system can bring accurate forecasting to the local level for people around the world, helping to better predict dangerous weather, and possibly, save lives. In their , representatives of the company report that the system is already being used by several meteorological agencies and companies around the world.