The representation of cloud cover in atmospheric general circulation models

This dissertation describes various aspects of improvements made in
the representation of clouds in the global forecast model of the
European Centre of Medium-Range Weather Fore- casts (ECMWF). Cloud
parametrization has long been identified as one of the most crucial
and uncertain aspects in General Circulation Models (GCMs) of the
atmosphere, which are used for both Numerical Weather Prediction
and the simulation of climate. It is therefore important to
constantly monitor and improve the performance of cloud
parametrizations in those models. The first part of the work
describes the implementation of an existing cloud parametrization
into ECMWF's forecasting system with special attention to a new
treatment of the prognos- tic cloud variables in data assimilation.
This is followed by an analysis of the performance of the
parametrization during a 15-year long data assimilation experiment
carried out in the context of the ECMWF reanalysis project. It is
shown that despite an overall good perfor- mance, several
weaknesses in the simulation of clouds exist. Subtropical
stratocumulus and extratropical cloudiness are underestimated,
while the cloud fraction in the trade cumulus areas and in the
Intertropical Convergence Zone is overestimated. In the second part
of the study detailed revisions of the parametrization of cloud
generation by convective and non-convective processes are
described. A consistent new description of cloud generation by
convection is derived using the mass- ux approach. Furthermore an
improved description of the generation of clouds by non-convective
processes is introduced. The superiority of the new formulation
compared to the existing one is demonstrated and links to other
approaches to cloud parametrization are established. The third part
of the work studies the role of vertically varying cloud fraction
for the descrip- tion of microphysical processes. It is shown that
the commonly used approach of representing precipitation in GCMs by
means of grid-averaged quantities leads to serious errors in the
parametrization of various physical processes such as the
evaporation of precipitation, with severe consequences for the
model's hydrological cycle. A new parametrization of the eects of
vertically-varying cloud fraction based on a separation of cloudy
and clear-sky precipita- tion uxes is developed and its performance
assessed. It is shown that this parametrization alleviates most of
the identied problems and thereby more realistically describes the
pre- cipitation physics in the presence of cloud fraction
variations. The final part of the dissertation takes a critical
look at the way the results of cloud parametrizations are evaluated
today. A number of studies using a variety of data sources and
modelling approaches are described and the need for a coordinated
use of the various existing validation techniques is highlighted. A
strategy to achieve such coordination is proposed. This work
provides contributions to virtually all facets of the development
of cloud parame- trizations. It combines theoretical aspects with
the use of a variety of modelling approaches and data sources for
the assessment of the performance of the parametrization. All model
improvements described here are now part of the operational version
of the ECMWF forecast model.