A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior performance compared to traditional numerical weather prediction systems in global medium-range forecasts. 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 predicting severe weather events, including tropical cyclones and atmospheric rivers, while running in under a minute on a single Google TPU v4 machine. Researchers emphasize that AI models like GraphCast should complement rather than replace traditional physics-based systems, offering a faster, more efficient tool for meteorologists. The model’s code has been made openly available to support further research and operational integration. Read the full article at: https://sciencedaily.com/releases/2023/11/231114155020.htm