Joint Seminar: Long-term statistics of continuous single column model simulations at Cabauw

Single column model (SCM) simulation has become a valuable and
relied-upon tool in the development and evaluation of parameterizations
for general circulation models (GCM). In this method, the sub-grid model
of a GCM is independently integrated in time, using prescribed
large-scale forcings and boundary conditions. Typically, an idealized
case is constructed based on observational data from a field experiment.
An advantage of the SCM technique is that the model physics is studied
in controlled conditions, in an isolated mode from the larger-scale
circulation. Combined with the low computational cost involved, this
serves to enhance model transparency and facilitates getting insight
into the simulated system. A drawback of the SCM as a development tool
is that relatively few cases have yet been formulated. Often these
idealized cases represent so-called 'golden days', reflecting observed
situations thought prototypical for a specific weather regime. One could
question the representativeness of such idealized cases; i) they might
actually reflect unique situations that rarely occur, and ii) they do
not necessarily represent those regimes that cause the most problems in
GCMs. As a result, parameterizations might get optimized for rare
situations, while their performance for the most 'troublesome' regimes
remains unassessed.

These issues have inspired efforts to perform SCM evaluations on a more
continuous basis, thus automatically covering many different weather
regimes. One such project is the recently initiated Cabauw
Parameterization Testbed. Short-range (3-day) SCM simulations are
performed daily for the Cabauw meteorological site in the Netherlands,
operated by the Royal Netherlands Meteorological Institute (KNMI). The
multi-year archive of SCM simulations thus generated is evaluated
against the wealth of continuous observational datastreams measured at
Cabauw, which cover the thermodynamic, kinematic and cloudy state of the
atmosphere. The method of investigation consists of the following steps;
1) Statistically identify a problem in a 3D GCM;
2) Assess if the problem is reproduced by the corresponding 1D SCM;
3) If so, identify which individual days contribute most to the error;
4) Study those days in great detail, using a variety of statistical tools;
5) When the cause is identified and understood, formulate a solution;
6) Re-simulate and re-evaluate the modified 1D SCMs, hopefully
diagnosing improvement;
7) Rerun the 3D GCMs including the improved physics.
A benefit of this method is that GCM statistics guide the evaluation and
improvement of parameterizations. At each step in this sequence, model
evaluation against observational datasets is essential.

In this presentation the merit of an SCM Testbed will be demonstrated
using three examples of problems in a GCM that have successfully been
addressed using the method described above. All are actual problems
recently encountered during the implementation of the new EDMF-DualM
shallow cumulus scheme (Neggers et al., JAS, in press) into the ECMWF
Integrated Forecasting System (IFS). The problems concern i) the diurnal
cycle of summertime low-level cloudiness over land, ii) low-level wind
scores in the mid-latitude storm tracks, and iii) momentum transport in
the stable nocturnal boundary layer. Model performance will be assessed
through statistics on both short time-scales (individual forecasts) and
long time-scales (monthly and yearly), including standard model-obs
differences but also more advanced statistical score techniques.




15:15 h


Bundesstr. 53, room 022/023
Seminar Room 022/023, Ground Floor, Bundesstrasse 53, 20146 Hamburg, Hamburg


Roel Neggers, KNMI


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