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 and current atmospheric conditions to 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 at multiple atmospheric levels. The AI system showed particular strength in predicting severe weather events, such as tropical cyclones and extreme temperatures, days in advance. Researchers emphasize that AI models like GraphCast should complement rather than replace traditional methods, as they rely on established systems for initial data and lack the explainability of physics-based approaches. The model has been made publicly available to support further research and development in meteorological science. Read the full article: https://sciencedaily.com/releases/2023/11/231114143522.htm