Working Group 3
Quantitative Precipitation Forecast II:
Quality of Precipitation Forecast, Verification and Interpretation
Issues
Participants:
Chair: Hans
Volkert
Felix Ament, Ulrich Damrath, Klaus Dengler,
Barbara Fay, Joe Klemp,
Nicole van Lipzig, Chiara Marsigli, Marco Milan, Antonella Morgillo,
Akira Noda, Antonio Parodi, Evelyne Richard, Takehiko Satumura, Hans Schipper, Hiromu Seko, Friedrich Theunert, Stefanie Wassermann, Heini
Wernli, Tanja Winterrath,
Matthias Zimmer
Report:
Jean Quiby
In Group 2, the discussion was very general and has touched numerous
points.
Mentioned here are only the points, which have trigged a substantial
discussion.
Verification of model precipitation forecasts
With the
point to point verifications methods (i.e. with the scores relating a grid
point to an observing station), it is a well known fact that the higher the
resolution of a model, the higher is the double penalty. The explanation is
simple: high resolution models show more details, more isolated and distinct features,
i.e. more possibilities to be wrong.
This fact
renders the use of verification methods that are not affected by double penalty
an absolute necessity. And such methods already exist:
-
Object
oriented methods, as the SAL method (SAL = Structure, Amplitude, Location)
-
Fuzzy
techniques, as neighbouring
-
Image
matching methods.
What is a good forecast?
The group
arrived at the conclusion that – formulated in this way - it is not possible to
answer that question, as the quality of a forecast can only be judged through
the use that is made from this forecast. The same forecast could perfectly
satisfy a user and be totally insufficient for another user working in a
different field.
Precipitation forecasts:
“Low” resolution (say 7-10 km) versus “high” resolution (say 2-3 km)
Verified by
the traditional point to point methods at the respective scales of each model
resolution, the high resolution forecasts will be worse.
When
comparing precipitation forecasts between models with different resolutions, it
is only meaningful to do it by upscaling the fields of the higher resolution
models to the coarsest model resolution.
When this
is done, it can be claimed – based on the experience accumulated until today –
that the forecasts of wind and temperature computed at high resolution are
better than the forecasts computed at the “upscaled” resolution (when the
verification is made on this latter resolution).
Is this
also the case for the precipitations? No participant could claim that the above
statement would also be valid for the precipitations.
Note that
there is another important reason to upscale high resolution model fields for
verification: there are simply not enough observations at their resolution to
carry out a reliable verification.
Why to develop high resolution, km-scale resolution models?
As it has
not yet been reliably assessed that high resolution precipitations are of
better quality than precipitations from coarser models, why do we continue to
develop high resolution models?
Or, more
directly: where are the strengths of the high resolution, km-scale models?
1.
As
already said, the temperature and, first of all, the wind forecasts are better
than at coarser resolutions.
2.
High
resolution precipitation patterns show very realistic structures, very often
amazingly similar to the corresponding radar patterns, although the location
and the timing are not always correct. This proves that the high resolution has
the capability to very well reproduce the dynamical and thermodynamical atmospheric
processes.
3.
There
today in the high resolution, km-scale resolution more potential for
improvement that at the mesoscale resolution (say 7-10 km). One of the reasons
is explicitness of the convection, which is not (yet?) at the mesoscale
properly parameterized. The absence of parameterized convection at high
resolution allows for example a better use of the radar information in data
assimilation.
Use of the probabilistic precipitation forecasts
All the
participants in the discussion agreed that the acceptance of the probabilistic
forecasts by the forecasters as well as by the professional users is
progressing very, very slowly.
It seems
that the greatest acceptance among the professional users is to be found by the
hydrologists. It has been reported that in
For the
minutes:
Jean Quiby