  Probabilistic temperature forecasts are potentially useful to the energy and
weather derivatives industries. However, at present, they are little used.
There are a number of reasons for this, but we believe this is in part due to
inadequacies in the methodologies that have been used to evaluate such
forecasts, leading to uncertainty as to whether the forecasts are really useful
or not and making it hard to work out which forecasts are best. To remedy this
situation we describe a set of guidelines that we recommend should be followed
when evaluating the skill of site-specific probabilistic medium range
temperature forecasts. If these guidelines are followed then the results of
validation can be used directly by forecast users to make decisions about which
forecasts to use. If they are not followed then the results of validation may
be interesting, but will not be practically useful for users. We find that none
of the published studies that evaluate such forecasts fall within our
guidelines, and that, as a result, none convey the information that the users
need to make appropriate decisions about which forecasts are best.
