Early Warning Systems (EWS) are a cornerstone of disaster risk reduction, protecting lives and livelihoods through timely, actionable information. Their efficacy depends not only on scientific robustness but also on integration across disciplines, from risk knowledge and hazard detection to communication and community and institutional response. Despite ambitious targets in the Early Warnings for All (EW4ALL) action plan and the Sendai Framework towards multi-hazard, all-vulnerability, and impact-based EWS, gaps persist between these ambitions, operational realities, and the supporting science. This session fosters dialogue on EWS implementation and methodological innovation among researchers working toward more effective, inclusive, and actionable systems.

We invite contributions from all disciplines and sectors involved in EWS development and implementation, including natural hazards science, atmospheric and hydrologic research, social sciences, and disaster management practice. We welcome work on any element of the early warning value chain, from forecasting advances to tools, platforms, or systems in use or development, as well as reflections on successes and failures in closing the gap between ambition and action. We encourage submissions addressing:
■ Early warning and anticipatory action: frameworks, tools and multi-stakeholder implementation in translating early warnings into effective disaster response and preparedness;
■ Impact-based approaches: methods for designing and implementing impact-based EWS;
■ Technological innovations: advances in AI, machine learning, Earth observation, IoT and other technologies in EWS components;
■ Risk communication and community engagement: strategies that integrate behavioral and psychological insights, build trust, and ensure effective warning dissemination, particularly at community level;
■ Data integration and system interoperability: approaches to integrating diverse data sources and addressing challenges in cross-agency data sharing and platform integration;
■ Bridging ambition and implementation: case studies showing how scientific progress translates into operational practice.

This session is developed in cooperation with the RiskKAN Working Groups "Warnings and Preparedness for a Riskier World" and "AI for Complex Climate Risk Mitigation".