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Ensembles are well equipped to forecast the first two types of anomalous events with the current resolution.   Extreme convective features are less well captured but can, to some extent, be added by experienced forecasters, or via statistical interpretation schemes.

The Extreme Forecast Index (EFI) and Shift of Tails (SOT) have been developed to show forecasters how ongoing weather event probabilities relate to time-of-year dependant climatological conditions at every location.   EFI and SOT parameters for CAPE and CAPE-shear have shown some noteworthy skill in foretelling of severe convective events that the IFS itself cannot predict directly.

These parameters have some general applicability for impact forecasting as they indirectly relate to local return periods for different types of adverse weather.  Forecasters can also benefit from an understanding of the local resilience of man-made infrastructure in the face of natural hazards.

The forecaster’s role

Considerations of probability, jumpiness, and the forecaster’s role apply in particular to extreme weather forecasting.  Calibrating or otherwise applying statistically based modifications to extreme weather events is very difficult because of their rarity.  However, forecasters can accumulate some experience of the IFS models’ capabilities from extreme weather events in neighbouring areas.  Complementary information, in particular forecasts from different NWP models and/or IFS runs, might motivate forecasters to upgrade or downgrade the probabilities.  Forecasters also have a unique role in supplying probability forecasts of events that are not explicitly covered by the ECMWF forecast products (e.g. thunderstorms).   Perhaps the most important task is to help end-users, such as regional and national authorities, to make the optimal decision about protective action.

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Severe or extreme weather is often characterized by low protective or insurance costs compared to high potential losses.  Thus relatively low probabilities can become highly decisive.  Using a cost-benefit approach can help the forecaster to enhance advice to the customer.  Protective action might be prompted at a level as low as 10% event probability, or even lower.  Forecasters’ advice does not have to be probabilistic; if they are very familiar with their customer’s decision process and preferences, purely categorical guidelines may be generated.  In cases of extreme weather, the necessary actions may be obvious - evacuating the area or taking shelter but in the end the decision to advise on and/or enforce major actions such as these will probably be down to the customer.

_{Updated/Amended 30/12/19 - Simplification of High Impact Weather}