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 generate 10-day forecasts in under a minute on a single computer. 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 temperature, pressure, wind speed, and humidity at multiple atmospheric levels. The AI system showed particular strength in predicting severe weather events, more accurately tracking the path of Tropical Cyclone Lee. 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 explanatory power of physics-based approaches. The model has been made publicly available to support further research and development in meteorological science. Read the full article at: https://sciencedaily.com/releases/2023/11/231114155020.htm