Objectif
Objectives :
To identify and minimise the tendency and forcing errors
in four different atmospheric general circulation models
(GCMs). The improved models will be developed and tested
with special attention to simulation of regional climate
over Europe and to seasonal prediction of climate.
Brief Description of the Research Project :
Two state-of-the-art atmospheric climate models and two
simpler GCMs will be used. Different techniques will be
applied to calculate the forcing errors, but the basic
method, to be tested in all four GCMs, consists of a
simple four dimensional data assimilation technique
called nudging. In nudging a given model is constantly
relaxed towards data which varies in time. In the present
application these data will be the ECMWF Re-Analyses
(ERA) and the magnitude of the relaxation will with
different constraints be used as a measure of the
models forcing errors.
The work will have an iterative character where
improvement of the GCMs will be guided by the temporal
and spatial distribution of the forcing errors and by the
characteristics of the systematic errors seen in climate
runs.
The improvement of the GCMs will follow two lines,
improvement of physical parameterization, and
developments of empirical parameterization of the forcing
errors.
The performance of physical parameterization will be
validated with special attention to simulation of
regional climate over Europe and elsewhere since such
errors severely degrades the performance of regional
climate models which receive boundary conditions from the
GCMs.
Along the second line the focus will be on testing the
seasonal prediction capabilities of GCMs which include
the empirical parameterization or correction of their
forcing errors. Such dynamical within-forecast
corrections will be compared with the more normal a
posteriori (or after-the fact) empirical corrections
(used e. g. in the PROVOST project).
Appel à propositions
Data not availableRégime de financement
CSC - Cost-sharing contractsCoordinateur
2100 KOEPENHAGEN
Danemark