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 particularly excelled at predicting severe weather events, more accurately tracking the path of tropical cyclones and anticipating extreme temperatures. Researchers emphasize that AI models like GraphCast should complement rather than replace traditional systems, offering faster, more efficient forecasts that could improve early warning systems for dangerous weather. Read the full article at: https://sciencedaily.com/releases/2023/11/231114143522.htm