DIAGNOSIS OF EXTRATROPICAL VARIABILITY IN SEASONAL INTEGRATIONS OF THE ECMWF MODEL

Properties of the general circulation simulated by the ECMWF model are discussed using a set of seasonal integrations at T63 resolution. For each season, over the period of 5 years, 1986-1990. three integration s initiated on consecutive days were run with prescribed observed sea surface temperature (SST). This paper presents a series of diagnostics of extratropical variability in the model, with particular emphasis o n the northern winter. Time-filtered maps of variability indicate that in this season there is insufficient storm track activity penetrating into the Eurasian continent. Related to this the maximum of lower-fre quency variance in the Euro-Atlantic region is erroneously shifted eas tward in the model. By contrast the simulated fields of both high- and low-frequency variability for northern spring are more realistic. Blo cking is defined objectively in terms of the geostrophic wind at 500 m b. Consistent with the low-frequency transience, in the Euro-Atlantic sector the position of maximum blocking in the model is displaced east ward. The composite structure of blocks over the Pacific is realistic, though their frequency is severely underestimated at all times of yea r. Shortcomings in the simulated wintertime general circulation were a lso revealed by studying the projection of 5-day mean fields onto empi rical orthogonal functions (EOFs) of the observed flow. The largest di fferences were apparent for statistics of EOFs of the zonal mean flow. Analysis of weather regime activity, defined from the EOFs, suggested that regimes with positive PNA index were overpopulated, while the ne gative PNA regimes were underpopulated. A further comparison between o bserved and modeled low-frequency variance revealed that underestimati on of low-frequency variability occurs along the same axes that explai n most of the spatial structure of the error in the mean field, sugges ting a common dynamical origin for these two aspects of the systematic error.