Challenges of forecast uncertainty within the warning value chain – a UK example from Storm Eunice

The warning value chain is a concept whereby the process of producing a warning is represented by a chain of sources of expertise (components), connected by bridges that convey bidirectional information exchanges. Uncertainties exist at all stages of the warning value chain. For example, uncertainties exist in the current (observational) state of the atmosphere used to initialise the numerical weather prediction models. This in turn contributes towards weather forecast uncertainties (e.g., ensemble-generated forecast probabilities and run-to-run variability). Weather forecast uncertainties then feed into the hazard and impact forecasts where they can be amplified – such as through uncertainties in defining hazard footprints or impact assessments. Often it comes down to operational meteorologists to examine the varying levels of forecast uncertainty across several value chain components and assess the real likelihood of high impact weather and its potential impacts. This presentation will focus on the challenges of forecast uncertainty within the value chain, using the forecasts and warnings associated with Storm Eunice which affected southern parts of the UK in February 2022 as an example. The Met Office Weather Impacts team recently used the warning value chain questionnaire produced by the WMO’s High Impact Weather (HIWeather) Warning Value Chain Flagship Project, to carry out a detailed warning value chain assessment for this event, where evidence was considered from across the value chain. Results showed that all components of the value chain performed well overall, and it was clearly a highly successful set of warnings as shown by the large reach and public/emergency response. However, several recommendations were still made and challenges resulting from forecast uncertainty were evident across many value chain components. A focus of this presentation will be on how operational meteorologists interpreted the changing forecast signal and how this affected warning issuance and communication.