  A new index for high-impact weather forecasting is introduced and assessed in
comparison with the well-established extreme forecast index (EFI). Two other
ensemble summary statistics are also included in this comparison study: the
shift-of-tail and a standardised ensemble mean anomaly. All these forecasts are
based on the same ingredients: the ensemble forecast run at the European Centre
for Medium-Range Weather Forecasts and the corresponding model climatology
derived from a set of reforecasts. The new index emerges from recent
developments in forecast verification of extreme events: it is derived as a
consistent forecast with the diagonal score, a weighted version of the
continuous ranked probability score targetting high-impact events. In this
study, we emphasise the importance of forecast discretisation for communication
purposes and decision-making. A forecast is actionable in the situation where a
user can decide to take action when a threshold is exceeded by the forecast.
Forecast verification is performed to assess both the potential skill of the
different indices as well as their specific skill as actionable forecasts.
Among the investigated actionable forecasts, the new proposed index
demonstrates the strongest discrimination power, in particular at longer lead
times, paving the way for seamless predictions of high-impact weather across
time ranges.
