PICO
Operational warning systems are the result innovations in the science of forecasting. New opportunities have risen in physically based modelling, AI/machine learning, hydro-meteorological forecasts, ensemble forecasting and impact-based forecasting, and real-time control. Often, the sharing of knowledge and experience about developments are limited to the particular field for which the operational system is used. Increasingly, humanitarian, disaster risk management and climate adaptation practitioners are using forecasts and warning information to enable anticipatory early action that saves lives and livelihoods. It is important to understand their needs, their decision-making process and facilitate their involvement in forecasting and warning design and implementation.
The focus of this session will be on bringing the expertise from different fields together as well as exploring differences, similarities, problems and solutions between forecasting systems for varying hazards including climate emergency. Case studies of system implementations - configured at local, regional, national, continental and global scales - will be presented. An operational warning system can include monitoring of data, analysing data, making and visualizing forecasts, impact-based solutions, giving warning signals and suggesting early action and response measures.
Contributions are welcome from both scientists and practitioners who are involved in developing and using operational forecasting and/or management systems for climate and water-related hazards, such as flood, drought, tsunami, landslide, hurricane, hydropower etc. We also welcome contributions from early career practitioners and scientists, and those working in multi-disciplinary projects (e.g. EU Horizon Disaster Resilience Societies).
We particularly welcome contributions aligned with the objectives of the WMO World Weather Research Programme project InPHRA (Integration of Precipitation and Hydrology for Early Action). InPHRA aims to advance transdisciplinary knowledge and skills for the research and development of effective multi-hazard flood forecasting and early warning systems so that “no one is surprised by a flood.” This includes integrating meteorology, hydrology, and social science, together with local and Indigenous knowledge systems, to improve the value chain from forecasts to community action, with particular attention to vulnerable populations.