2025-06-27 マックス・プランク研究所
＜関連情報＞
- https://www.mpg.de/24966451/extreme-weather-early-warning
- https://www.nature.com/articles/s41467-025-57640-w
統合人工知能による複雑な気候リスクの早期警告 Early warning of complex climate risk with integrated artificial intelligence
Markus Reichstein,Vitus Benson,Jan Blunk,Gustau Camps-Valls,Felix Creutzig,Carina J. Fearnley,Boran Han,Kai Kornhuber,Nasim Rahaman,Bernhard Schölkopf,José María Tárraga,Ricardo Vinuesa,Karen Dall,Joachim Denzler,Dorothea Frank,Giulia Martini,Naomi Nganga,Danielle C. Maddix & Kommy Weldemariam
Nature Communications Published:15 March 2025
DOI:https://doi.org/10.1038/s41467-025-57640-w
Abstract
As climate change accelerates, human societies face growing exposure to disasters and stress, highlighting the urgent need for effective early warning systems (EWS). These systems monitor, assess, and communicate risks to support resilience and sustainable development, but challenges remain in hazard forecasting, risk communication, and decision-making. This perspective explores the transformative potential of integrated Artificial Intelligence (AI) modeling. We highlight the role of AI in developing multi-hazard EWSs that integrate Meteorological and Geospatial foundation models (FMs) for impact prediction. A user-centric approach with intuitive interfaces and community feedback is emphasized to improve crisis management. To address climate risk complexity, we advocate for causal AI models to avoid spurious predictions and stress the need for responsible AI practices. We highlight the FATES (Fairness, Accountability, Transparency, Ethics, and Sustainability) principles as essential for equitable and trustworthy AI-based Early Warning Systems for all. We further advocate for decadal EWSs, leveraging climate ensembles and generative methods to enable long-term, spatially resolved forecasts for proactive climate adaptation.
