A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior accuracy compared to conventional physics-based systems in global medium-range weather predictions. The GraphCast model, detailed in a Science journal paper, uses machine learning trained on decades of historical weather data to predict hundreds of weather variables up to 10 days in advance. 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. The AI system significantly outperformed HRES in tracking severe weather events, including tropical cyclones and atmospheric rivers, while running in under a minute on a single machine. Researchers emphasize that AI models like GraphCast should complement rather than replace traditional systems, offering faster, more efficient forecasts that could enhance early warning systems for extreme weather. The model’s code has been made publicly available to support further research and development in meteorological AI applications. Read the full article at: https://sciencedaily.com/releases/2023/11/231114155020.htm