The briefing highlights that traditional weather forecasting models continue to outperform artificial intelligence (AI) methods in predicting extreme weather events. Despite rapid advancements in AI, conventional numerical weather prediction (NWP) systems, which rely on physical and atmospheric data, remain more reliable for forecasting severe conditions like storms, heatwaves, and heavy rainfall. Traditional models benefit from decades of refinement, incorporating complex physics and real-time observational data, enabling accurate short- and medium-term forecasts. In contrast, AI approaches, while promising in pattern recognition and data analysis, currently lack the comprehensive understanding of atmospheric dynamics necessary for precise extreme weather prediction. Researchers emphasize that AI may serve as a complementary tool, enhancing certain aspects of forecasting or processing large datasets, but it is not yet ready to replace established models. The briefing underscores the continued importance of investing in and improving traditional forecasting systems alongside exploring AI innovations to better prepare for and mitigate the impacts of extreme weather events amid climate change.

Published on: 2026-04-30 at 00:15:01