Recent advances in AI and digital technologies are transforming how we assess and manage risks from climate extremes and natural hazards. LLMs, GenAI, and foundation models enable integration of diverse data sources, while XAI ensures transparency in high-stakes decision-making. Digital twins of the Earth system and human–environment interactions provide powerful platforms for simulating hazard cascades, testing adaptation options, and supporting anticipatory action. This session invites contributions on AI-driven knowledge extraction, hazard prediction, risk assessment, disaster response, and multi-hazard simulation. We particularly welcome work that explores synergies—for example, digital twins generating synthetic data for foundation models, or LLMs embedded as reasoning layers within simulation environments. By highlighting these intersections, the session aims to advance cross-disciplinary dialogue on how converging digital technologies can accelerate resilience to climate and natural hazard risks.
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