A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior performance compared to traditional physics-based systems in global medium-range weather predictions. The model, named GraphCast, uses machine learning to analyze decades of historical weather data and current atmospheric conditions to generate forecasts up to 10 days in advance. In head-to-head comparisons with the European Centre for Medium-Range Weather Forecasts’ 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 one minute on a single Google TPU v4 machine, significantly faster than conventional methods that require hours of supercomputer calculations. Researchers note that while GraphCast excels at medium-range forecasting, traditional models still provide important complementary data and are necessary for initial condition analysis. The development represents a significant shift toward data-driven approaches in meteorology, potentially enabling more timely and accessible weather predictions worldwide. Read the full article at https://technologyreview.com/2023/11/14/1084089/ai-weather-model-graphcast-outperforms-traditional-forecasts/