A new study demonstrates that artificial intelligence models can generate accurate, high-resolution weather forecasts faster and more efficiently than traditional physics-based systems. Researchers developed an AI system that analyzes vast amounts of historical weather data to predict future conditions. The model produced forecasts for precipitation and temperature that were competitive with established numerical weather prediction methods, but at a fraction of the computational cost and time. While the AI approach shows significant potential for operational forecasting, especially for rapidly updating short-term predictions, experts note that further testing is needed to ensure reliability across all weather phenomena and geographic regions. The research highlights a growing trend of using machine learning to augment or potentially transform aspects of meteorological science. Read the full article at https://sciencedaily.com/releases/2024/05/240507150541.htm