Predictability of a large-scale flow conducive to extreme precipitation over western Alps
Dr. Federico Grazzini
ARPA-Servizio IdroMeteorologico, Bologna, Italy
Abstract:
The quality of numerical weather prediction has improved
considerably since its beginning, however this
remarkable achievement has to be considered true for average
conditions. It is known that atmospheric predictability and model errors
are highly flow-dependent therefore an increase in skill for
average conditions may not imply the same improvements
in specific conditions. Moreover the potential value of numerical
weather prediction is perceived to be higher in some
specific cases, like high-impact weather events. There
is therefore a growing need to know the forecasting accuracy
of significant weather events, something that cannot be
easily inferred through average scores, not least because of
the rarity of these events. For these reasons, a study has been
carried out to examine the skill of the European Centre for
Medium-Range Weather Forecast (ECMWF) global forecasting
system in predicting a specific flow configuration
that is believed to be associated with extreme precipitation
events over the Alpine region. Despite quantitative predictions
of extreme precipitations is still challenging, it was
found that the large-scale flow conducive to major rain
events has better predictive skill than average conditions.
This is perhaps surprising since it is a common perception
to associate severe weather with low predictability.