POTENTIALS

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).