The development of digital twins in Earth systems, such as Destination Earth, is revolutionizing our approach to understand and manage our planet’s complex dynamics under a changing climate. These advanced simulations enable us to integrate diverse types and sources of data, providing a comprehensive view of Earth-climate dynamics and human-environment interactions. In detail, digital twins allow to replicate a system behaviour, provide an up-to-date status of ongoing physical processes, support informed decision-making. They enable predictive Earth observation, exploring "what if" scenarios or simulating hazard cascades, and testing various adaptation strategies.
This session will explore the role of digital twins for bridging observations and simulations to applications in impact sectors. There will be a special focus on uncertainty quantification, data assimilation, multi-source data streams, hybrid modelling, and decision support. We are particularly interested in studies that highlight the synergies between digital twin technology and other AI-driven tools, such as predictive analytics and machine learning, in improving operational outcomes. This session aims to foster cross-disciplinary dialogue on how these converging technologies can accelerate resilience to climate-related risks and natural hazards, including in a variety of impact sectors (energy, food, carbon storage, etc…) and will extend to economic, social components and policy considerations. It will act as a forum for researchers and practitioners to share their insights and recent developments in this rapidly evolving field.