A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior performance compared to traditional physics-based systems in global weather predictions. The model, named GraphCast, uses machine learning to analyze decades of historical weather data and current atmospheric conditions to generate accurate 10-day forecasts in under a minute. 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 temperature, pressure, wind speed, and humidity. The AI system particularly excelled at predicting extreme weather events, such as tropical cyclones and atmospheric rivers, earlier and with greater precision than conventional methods. Researchers emphasize that AI models like GraphCast should complement rather than replace traditional systems, offering faster, more efficient forecasts that could improve early warning systems for severe weather. The model’s code has been made publicly available to support further research and development in meteorological science. For the complete analysis and technical details, read the full article at: https://technologyreview.com/2024/11/14/ai-weather-model-graphcast-outperforms-traditional-forecasts