English Abstract A coupled atmosphere/ocean/sea-ice Model of
Intermediate Complexity (ECBilt) was developed. With ECBilt we aim at
deriving qualitative information on physical processes and feedbacks that
may be crucial for explaining climate variability on time-scales of decades
to millennia, as well as on the potential existence of instabilities in the
climate system that may lead to rapid climate transitions. The model is
very efficient, so that long integrations as well as "idealized"
experiments, sensitivity experiments and ensemble climate integrations are
possible.With the first generation ECBilt model (ECBilt1) we have
investigated the interannual to decadal climate variability in the North
Atlantic area and the Antarctic Circumpolar Wave (ACW), the possible effects
of modulations in solar irradiance on the earth climate, the possiblity for
the occurrence of rapid transitions in a 40 kY integration of ECBilt for
present day orbital parameters and the predictability of climate on decadal
time scales. In all of the above mentioned studies we have done experiments
to test the robustness of the results by introducing variations in internal
and/or external parameters. We have improved ECBilt1 in several aspects.
In the atmospheric model the ratiation code was replaced. The new radiation
scheme is a linearisation of the Morcrette scheme and includes the
possibility of variations in trace gases like CO2. We are presentyl working
on improving the boundary layer scheme. The ocean model was replaced by the
MOM model of GFDL and by the CLIO model of the University of Louvain la
Neuve. Both models are state of the art ocean models. MOM is less
expensive than CLIO and will be used for millennial time-scale variability.
CLIO will be used for studying the decadal time-scales. CLIO had a dynamic
sea-ice model. With ECBilt2 coupled to CLIO we have performed greenhouse
gas concentration scenario experiments and we have also studied the decadal
variability in the Arctic which is associated with the dynamics of sea-ice.
ECBilt2 will be integrated in the IMAGE model of RIVM for climate change
scenario studies.