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 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—considered the global gold standard—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 one minute on a single Google TPU v4 machine, a task that takes traditional supercomputers hours to complete. Researchers emphasize that AI models like GraphCast are not intended to replace existing systems but to complement them, offering a faster, potentially more efficient tool for meteorologists. The model’s code has been made open-source to encourage further research and development in the field. Read the full article at https://technologyreview.com/2024/03/14/ai-weather-model-graphcast-outperforms-traditional-systems/