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 study published in Science, uses machine learning to analyze decades of historical weather data, enabling it to generate 10-day forecasts in under one minute on a single cloud-based 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 measurements like atmospheric pressure, humidity, and wind speed. The AI system particularly excelled at predicting extreme weather events, such as the path of Hurricane Lee and atmospheric rivers, days earlier than traditional methods. Researchers emphasize that AI models like GraphCast are not replacements but powerful complements to existing numerical weather prediction systems, offering faster, more efficient forecasts that could improve early warning systems for severe weather. The model’s code has been made open-source to encourage further development and integration with established meteorological approaches. Read the full article at https://sciencedaily.com/releases/2023/11/231114143522.htm.