WeatherNext 3 from Google Research and DeepMind drops traditional physics models and learns directly from real-time satellite data. Google promises five times the detail and hourly updates.
Previous AI weather models, including WeatherNext 2, trained on numerical weather prediction (NWP) data. Those simulations run on supercomputers and carry a six-hour delay, according to Google, which introduces errors for fast-changing variables like rainfall and temperature.
WeatherNext 3 processes live geostationary satellite data instead. It generates a fresh forecast every hour based on the latest observations at up to five-kilometer resolution. For fast-developing storms or precipitation, the quicker update cycle means earlier and more accurate predictions.
Five times sharper than its predecessor
The model produces hourly forecasts at multiple resolutions. Temperature and humidity run at five kilometers, other surface variables at ten, and atmospheric values like wind speed at 25. That's about five times sharper than WeatherNext 2, which used a 25-kilometer grid in six-hour intervals.
