All weather forecasting activities aim to provide valuable information to the users of forecast products, with the ultimate goal of improving their decision-making processes. This goal can only be achieved if the forecast products correspond to customers’ requirements. In particular probabilistic forecast products are perceived to be more difficult to interpret and integrate into decision-making processes. As such, especially probabilistic products have to be carefully designed to be well understood and valuable for users. In order to create and establish useful probabilistic products, both the developers’ views and customer demands have to be understood and somehow integrated. This session will bring together these different perspectives, with the main aim of bridging the gap between theoretical considerations and practical realities of how forecast uncertainty should or can be taken into account.

Papers are invited on any aspect of the design and use of probabilistic forecast products including:
- Development of probabilistic forecast products for short-range, medium-range, to extended-range predictions, as well as seamless products
- Methods to generate probabilities from ensembles
- Methods to combine deterministic and ensemble forecast information
- Probabilities of extreme events, risk predictions, disaster prevention: Expectations and limitations.
- Developers’ perspective: what is possible, what is not possible?
- Customers’ perspective: what is acceptable, what is not acceptable? Examples from all application areas are welcome, e.g. energy, health, transport, hydrology, agriculture etc…
- Examples of current use (or plans for future use) of probabilistic products as input for (probabilistic) application models
- Integrating meteorological forecast uncertainties into decision-making processes
- Consolidation of customer demands and forecast uncertainties: how do we deal with unrealistic requests for precision and existing limitations of the predictions on all timescales?
- How to design and communicate uncertainties in view of irrational decision-making