Within the framework of WMO’s "Early Warnings for All" initiative, this session aims to contribute to a deeper understanding of the role of robust forecast and monitoring systems for hazard monitoring and early warnings. In the forecasting area, many countries lack the capacity to incorporate an impact-based approach to forecasting and still have challenges in accessing, analyzing and translating prediction model outputs into actionable warning messages. The underlying reasons are multiple, e.g., including data issues, modeling and communication challenges or co-production and knowledge gaps.
This session aims to assemble experienced practitioners, researchers and decision makers in this field to report on novel developments, best-practices but also relevant obstacles from their perspective. While for many actors the relevant focus lies on the weather forecasting scale, the outcome for and the experiences from the climate forecasting community on sub-seasonal to seasonal scales become ever more relevant on this matter, e.g., in the realm of anticipatory action.
We encourage an integrative, interdisciplinary and internationally-comprehensive exchange with contributions from social science, humanities, and interdisciplinary research related to the following topics:

• Gap analyzes on early warning needs (national, regional)
• Co-production and transdisciplinary approaches to develop impact-based forecasts
• Latest research and developments on statistical and physical weather impact models and the underlying data challenges
• The use of impact forecasts to aid the decision-making process for issuing warnings
• Seamless (impact) forecast activities and challenges from the weather to the (sub-)seasonal forecast scale
• Decision-making under uncertainties - including topics related to forecasting and modelling uncertainties, appropriate strategic responses, and emergent patterns of social vulnerability to hazards
• Integrating citizen science and crowdsourcing observations in weather and impact forecasts
• Interdisciplinary approaches integrating satellite observations, global data processing, forecasting, and analysis systems
• Enhancing equity through the development and implementation of forecast and early warning systems
• Good practices and guidelines for enhanced data access and data interoperability