A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior accuracy and speed compared to the world’s leading conventional system, according to a peer-reviewed study published in the journal Science. The model, named GraphCast, leverages decades of historical weather data and current atmospheric conditions to generate 10-day forecasts in under a minute on a single machine. In a comprehensive evaluation against the European Centre for Medium-Range Weather Forecasts (ECMWF) high-resolution forecast (HRES), GraphCast provided more accurate predictions for over 90% of 1,380 test variables, including critical atmospheric measurements like geopotential, temperature, and wind speed. Researchers highlight its potential to improve severe weather event prediction, such as tropical cyclones and extreme temperatures, while acknowledging that AI models rely on traditional systems for initial data. The findings suggest a hybrid future for meteorology, combining the physical understanding of conventional models with the efficiency of AI. Read the full article at: https://sciencedaily.com/releases/2023/11/231114143522.htm