A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior accuracy compared to traditional 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 and generate 10-day forecasts in under one 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, with greater precision days in advance. Researchers emphasize that AI models like GraphCast should complement rather than replace traditional methods, as they offer different strengths and computational efficiencies. The model’s open-source release aims to accelerate progress in weather prediction globally. Read the full article: https://sciencedaily.com/releases/2023/11/231114143522.htm