A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior accuracy compared to traditional physics-based systems in global medium-range forecasts. The GraphCast model, detailed in a Science journal paper, uses machine learning trained on decades of historical weather data to predict hundreds of weather variables up to 10 days in advance. In head-to-head comparisons with the European Centre for Medium-Range Weather Forecasts’ high-resolution forecast (HRES), GraphCast provided more accurate predictions for over 90% of 1,380 test variables. The AI system can generate a 10-day forecast in under one minute on a single Google TPU v4 machine, significantly faster than conventional methods that require hours on supercomputers. While meteorologists emphasize that AI models should complement rather than replace traditional systems, the breakthrough suggests machine learning could revolutionize weather prediction by making accurate forecasts more accessible and efficient. Read the full article at https://sciencedaily.com/releases/2023/11/231114143522.htm.