A new artificial intelligence weather forecasting model developed by researchers at Google DeepMind has demonstrated superior accuracy compared to conventional physics-based systems in global medium-range weather predictions. The AI model, named GraphCast, uses machine learning to analyze decades of historical weather data and identify complex atmospheric patterns. In head-to-head tests against the European Centre for Medium-Range Weather Forecasts (ECMWF) system—considered the global gold standard—GraphCast provided more accurate predictions for over 90% of 1,380 test variables, including critical measurements like temperature, pressure, wind speed, and humidity at various atmospheric levels. The AI system can generate a 10-day forecast in under one minute on a single Google TPU v4 machine, a task that takes traditional supercomputers hours to compute. Researchers emphasize that AI models like GraphCast are not replacements but powerful complements to existing numerical weather prediction methods, potentially enabling faster, more efficient, and higher-resolution forecasts. For the full details, read the complete article at https://sciencedaily.com/releases/2023/11/231114143522.htm.