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• identify the predictable scale,
• dampen forecast jumpiness,
• estimate the overall confidence
• draw attention to possible alternative developments, in particular those which involve extreme or hazardous weather events.
  
  

A combined use of HRES and ENS is most effective in identifying and assessing these ideals and is strongly recommended.  Some guidance is given on how best to use the forecast products on the relatively few occasions when it might be necessary to use either HRES alone or ENS alone using ENS.

Issuing reliable categorical weather forecasts is of crucial importance for any meteorological service during normal weather conditions.  It builds trust with the public.  If they have confidence in the ability of a weather service to successfully forecast conditions in normal weather conditions, they will be more likely to trust its forecasts, even probabilistic ones, in cases of extreme weather.  The provision of categorical and probabilistic forecasts to the public and end-users therefore support and complement each other.

However, the categorical forecasts should also be fairly consistent over time.  Nothing Categorical forecasts imply a confidence that may not be justified and ECMWF suggests a more probabilistic approach should be used.  Nothing undermines public confidence more than “jumpy” forecasts where forecasts change, sometimes radically, and in particular in connection with anomalous or extreme weather events.  A bad five-day forecast will be identified as such only after five days; a “jumpy” forecast will be identified immediately to the exasperation of the user.   Although ENS must, by necessity, be "jumpy" to some extent, there is no reason to convey this “jumpiness” to the public by basing a forecast solely on the very latest deterministic NWP output.  This can best be avoided by making active use of uncertainty information derived from recent ENS forecasts.

Probabilistic (and deterministic) frameworks can and should be adapted whenever specific user requirements have to be taken into account; some examples are given in the appendix.

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