Early warnings must be understandable, trusted and actionable to help protect lives and livelihoods from natural hazards such as floods, droughts, heatwaves, tropical cyclones, storms and tsunamis. Recent disasters, such as the 2021 floods in Western Europe, the 2024 Valencia floods, and the 2020-2023 Horn of Africa drought, show that significant gaps in the early warning - early action chains persist, despite major advances in forecasting capabilities over last decades. The Early Warnings for All initiative (led by WMO, UNDRR, ITU, and IFRC) recognizes that increased efforts are required to develop life-saving, impact-based multi-hazard early warning systems.
The scientific community needs to move beyond natural hazard forecasting and towards impact- and action-based forecasting. This, in turn, requires commitment to the creation and dissemination of multi-hazard risk and multi-source impact data (including from social media) as well as the collaborative production of impact-based forecasting services and linked early action protocols.
However, much remains unknown and significant knowledge gaps persist. This session aims to offer valuable insights and share best practices on impact-based early warning systems from the perspective of both the knowledge producers and users. Such systems demand much knowledge about how hazards translate to impacts through exposure and vulnerability, novel impact-based forecasting technologies (including machine learning models), the costs and benefits of triggered actions, human decision-making and risk perception dynamics.
Topics of interest include, but are not limited to:
- Practical applications and operational use-cases of impact-based forecasts
- Novel physics-based, Artificial Intelligence (AI) and hybrid models for impact-based forecasting
- Innovative solutions to address challenges in impact-based forecasting effectively, including the application of AI, harnessing big data and earth observations
- Development of cost-efficient, evidence-based early action portfolios
- Impact and action-oriented forecast verification and post-processing techniques
- Triangulation of indigenous and scientific knowledge for leveraging forecasts, multi-hazard risk information and climate services to last-mile communities
- Bridging the gaps in risk and impact data to support impact-based forecasting
- Collecting and expanding datasets on interventions and adaptations to build an early action evidence base