We’ve released a new paper describing our core weather model, and are providing an archive on Weather Lab of historical cyclone track data, for evaluation and backtesting.

Internal testing shows that our model's predictions for cyclone track and intensity are as accurate as, and often more accurate than, current physics-based methods. We’ve been partnering with the U.S. National Hurricane Center (NHC), who assess cyclone risks in the Atlantic and East Pacific basins, to scientifically validate our approach and outputs.

NHC expert forecasters are now seeing live predictions from our experimental AI models, alongside other physics-based models and observations. We hope this data can help improve NHC forecasts and provide earlier and more accurate warnings for hazards linked to tropical cyclones.

Weather Lab’s live and historical cyclone predictions

Weather Lab shows live and historical cyclone predictions for different AI weather models, alongside physics-based models from the European Centre for Medium-Range Weather Forecasts (ECMWF). Several of our AI weather models are running in real time: WeatherNext Graph, WeatherNext Gen and our latest experimental cyclone model. We’re also launching Weather Lab with over two years of historical predictions for experts and researchers to download and analyze, enabling external evaluations of our models across all ocean basins.