Call for abstracts for the EGU session “Novel Approaches for Early Warning Systems: from AI to trans-disciplinary approaches”. The session examines innovative approaches to improve early warning systems (EWS) in view of the increasing frequency and intensity of extreme events due to climate change. The focus is on the integration of artificial intelligence (AI), machine learning and transdisciplinary approaches to increase the effectiveness and reach of EWS. Particular attention is paid to complex, multi-hazard risks and the combination of natural and social sciences. The aim is to use new technologies and methods to strengthen the resilience of communities and reduce risks more effectively, especially in the context of the UN initiative “Early Warnings for All”. Contributions from various disciplines are welcome to highlight both technical and social aspects of early warning systems.
Abstracts can be submitted until January 15.
More information can be found here.
(Image source: EGU)