Can a hybrid AI-physics model address the challenges of typhoon forecasting? New study shows significant accuracy gains
Peer-Reviewed Publication
Updates every hour. Last Updated: 1-Jan-2026 00:11 ET (1-Jan-2026 05:11 GMT/UTC)
A research team has studied the development of the Shanghai Typhoon Model from a traditional physics-based regional model toward a data-driven, machine-learning typhoon forecasting system. They summarize the model’s performance in Typhoon Danas in 2025, noting that a hybrid Shanghai Typhoon Model provides a significant advancement in forecast accuracy. Their paper outlines a roadmap for evolving the physically driven Shanghai Typhoon Model into a purely data-driven, regional machine-learning weather-prediction model designed for typhoon prediction.
Current clinical protocols predominantly utilize mononuclear gadolinium(III) complexes as contrast agents. Recently, coordination clusters composed of multi-nuclear paramagnetic metal ions have demonstrated promisingly higher relaxation rates as MRI contrast agents and adaptable stability in various solutions, offering promising medical application prospects. This review mainly highlights such advancements, focusing on the influence of ligand selection and structural design on the relaxation rates of metal clusters as MRI contrast agents.