A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior accuracy compared to traditional physics-based systems in global medium-range weather predictions. The GraphCast model, detailed in a recent Science publication, uses machine learning to analyze decades of historical weather data, learning complex atmospheric patterns to generate 10-day forecasts in under one minute on a single computer. In head-to-head comparisons with the European Centre for Medium-Range Weather Forecasts’ high-resolution forecasting system (HRES), GraphCast provided more accurate predictions for over 90% of 1,380 test variables, including critical metrics like tropical cyclone tracking and extreme temperature forecasts. Researchers emphasize that AI models like GraphCast are not replacements for but powerful complements to established numerical weather prediction methods, offering faster, more efficient forecasts that could improve early warning systems for severe weather events. The model’s code has been made openly available to support further research and development in meteorological science. Read the full article at: https://sciencedaily.com/releases/2023/11/231114155020.htm