Today’s numerical weather prediction models have matured substantially in providing reliable probabilistic predictions, along with a useful quantification of prediction uncertainty. Including this information in the communication of weather forecasts and warnings, and integrating it into downstream models and decision-making processes has become increasingly common practice. Including uncertainties not only implies the interpretation of ‘raw’ uncertainty information in ensemble forecasts, their post-processing, and visualization, but also the integration of a wide range of non-meteorological aspects such as vulnerability and exposure data to estimate risk and the social, psychological and economic aspects which affect human decision-making and well-being. In this session, we’d like to focus on all aspects that are related to making use of uncertainty information of weather forecasts in decision processes and applications. We encourage interdisciplinary contributions that:

• report on interactions between scientists and end-users that help to overcome reservations about uncertainty forecasts
• propose visualizations of uncertainty forecasts (e.g. warnings) for expert users and / or the public
• share ideas about reducing complexity and computational or cognitive cost
• demonstrate the successful integration of forecast uncertainty information into decision making processes
• estimate the uncertainty and its propagation through the entire process chain until the risk for an impact
• quantify the value of uncertainty forecasts in decision making processes

Presentation slides:

• Social Science at the Met Office (Helen Roberts)
• Comparative test of public outreach methods about ibf information understanding through the mosaic program (Nanda Alfuadi, Cindy Selly Sukma Devi, Agie Wandala Putra)
• How to communicate uncertainty in weather warnings? Public perception in Germany (Katja Schulze, Nathalie Popovic, Nadine Fleischhhut)
• Feedback from NMHS's and their users on communication, weather warnings and probability information (Solfrida Agersten, Anders Sivle, Franziska Schmid, André Simon)

Poster presentations:

• A propinquity model approach to spatial risk level estimation (Eric Gilleland)