A new artificial intelligence model developed by researchers at Stanford University demonstrates superior accuracy in short-term weather forecasting compared to conventional physics-based models. The system, named ClimaNet, was trained on decades of global atmospheric data and can predict precipitation, temperature, and severe weather events up to 10 days in advance with significantly higher precision. Initial tests show a 15% improvement in 3-day rainfall forecasts over the current leading numerical models. The AI approach processes data faster and at a lower computational cost, potentially enabling more frequent and localized updates. Researchers emphasize the model is a complementary tool for meteorologists, not a replacement, and requires further real-world validation. Read the full article at https://technologyreview.com/2024/05/15/climanet-ai-weather-forecasting.