Ensemble Classes of Use Cases
- 1Met Office, Exeter, United Kingdom of Great Britain – England, Scotland, Wales (ken.mylne@metoffice.gov.uk)
- 2European Centre for Medium Range Weather Forecasts, Reading, United Kingdom
- 3National Center for Atmospheric Research, Boulder, Colorado, USA
Ensemble Numerical Weather Prediction (NWP) systems have now been used operationally for over 30 years, mainly as a supplement to single realisation “deterministic” forecasts based on a higher resolution NWP model. Ensembles sample a range of possible outcomes and allow the estimation of probabilities and uncertainties in the forecast. Recognising the greater forecast skill of ensemble forecasts, the Met Office is moving towards a completely ensemble-based NWP system with no separate higher resolution deterministic forecasts, so users and developers will need to consider how these ensemble-based forecasts can best be used to cover the wide variety of applications and use cases. Ensembles offer a wealth of information which can be used in many different ways, from picking preferred or representative members to basing forecasts on a full probability distribution; forecasts may also be presented in many ways, either deterministically or taking account of the forecast uncertainty, depending on the use case and the decisions to be supported. In order to help users get the most benefit from ensembles, we present a framework of “classes of use cases” that classifies different user requirements of an NWP system and describe how these can be met. Which class is most appropriate for a particular user and application will depend on the nature of the decision(s) to be taken, the vulnerability of the user to weather impacts and the risk appetite of the user. The use cases are not fundamentally new, but by classifying them we aim to help users and service providers to identify the best approaches to address the needs of different users, and to identify synergies between the needs of different users. By classifying the use cases in this way we also highlight the implications for how we should be developing and processing ensemble data to deliver to these use cases, to ensure that the maximum benefits from ensemble NWP forecasts are pulled through for the whole of society.
How to cite: Mylne, K., Walters, D., Roberts, N., Barciela, R., Gray, M., Petch, J., Wells, O., Sachon, P., Skea, A., Davies, P., Willington, S., and Titley, H.: Ensemble Classes of Use Cases, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-143, https://doi.org/10.5194/ems2024-143, 2024.
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