A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior accuracy compared to conventional numerical weather prediction systems in global medium-range forecasts. The model, named GraphCast, uses machine learning to analyze decades of historical weather data and current atmospheric conditions to predict weather patterns up to 10 days in advance. In head-to-head tests against 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 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 significant reduction from the hours of computation required by traditional physics-based models. Researchers emphasize that AI models like GraphCast are designed to complement, not replace, existing systems, offering a faster, more efficient tool for meteorologists. The findings were published in the peer-reviewed journal Science. Read the full article at: https://sciencedaily.com/releases/2023/11/231114155020.htm