Classification of Use Cases for Ensemble Weather Forecasts

Ensemble numerical weather prediction (NWP) systems have been used operationally for over 30 years, mainly supplementing higher-resolution “deterministic” forecasts. Recognizing the greater forecast skill of ensembles, some centers are moving toward completely ensemble-based NWP, which broadens the variety of applications and use cases and has implications for developers and users. Ensembles offer a considerable increase in forecast information that can bring substantial benefits if used appropriately but also bring increased costs and overhead. Applications range from picking preferred or representative members to exploiting the full probability distribution, enabling synthesis of either selected storylines (e.g., most likely or highest impact) or estimating the forecast uncertainty, depending on the decisions to be supported. To help users exploit ensembles effectively, we present a “classification of use cases.” The most appropriate class for a particular user and application will depend on the nature of the decision(s) to be taken, the risk appetite (or tolerance) of the user, and their vulnerability to weather impacts. The use cases are not fundamentally new, but by classifying them, we aim to help users and service providers identify the best approaches to address their needs. We also highlight how we should be developing and processing ensemble data to deliver to these use cases to ensure that the maximum benefits from ensemble NWP are pulled through for the whole of society.