A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior accuracy to traditional physics-based systems in global medium-range weather predictions. The model, named GraphCast, uses machine learning to analyze decades of historical weather data and current atmospheric conditions to generate forecasts up to 10 days in advance. In head-to-head comparisons with the European Centre for Medium-Range Weather Forecasts’ high-resolution system (HRES), GraphCast provided more accurate predictions for over 90% of 1,380 test variables, including critical metrics like temperature, pressure, wind speed, and humidity. The AI system can generate a 10-day forecast in under one minute on a single Google TPU v4 machine, a significant efficiency gain over conventional methods that require hours of computation on supercomputers. Researchers emphasize that AI models like GraphCast are designed to complement, not replace, established numerical weather prediction systems, offering a powerful new tool for meteorologists. The findings were published in the peer-reviewed journal Science. Read the full article at: https://sciencedaily.com/releases/2023/11/231114155020.htm