A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior performance compared to conventional physics-based systems in global medium-range weather predictions. The model, named GraphCast, uses machine learning to analyze decades of historical weather data and identify complex atmospheric patterns. In head-to-head tests against the European Centre for Medium-Range Weather Forecasting’s high-resolution forecast system, GraphCast provided more accurate predictions for over 90% of 1,380 test variables, including critical measurements like atmospheric pressure, temperature, and wind speed. The AI system can generate a 10-day forecast in under a minute on a single Google TPU v4 machine, a significant reduction in computational cost compared to traditional supercomputer-based models. Researchers note that while promising, AI models should complement rather than replace established physics-based systems, especially for understanding extreme weather events and long-term climate trends. Read the full article at https://technologyreview.com/2023/11/14/1084089/ai-weather-forecasting-graphcast-outperforms-traditional-models/