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Application of blocking diagnosis methods to General Circulation Models. Part II: model simulations

Barriopedro D., García-Herrera R., González-Rouco J.F., Trigo R.M.
Climate Dynamics, DOI 10.1007/s00382-010-0766-6

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Abstract

A previously defined automatic method is applied to reanalysis and present-day (1950-1989) forced simulations of the ECHO-G model in order to assess its performance in reproducing atmospheric blocking in the Northern Hemisphere. Unlike previous methodologies, critical parameters and thresholds to estimate blocking occurrence in the model are not calibrated with an observed reference, but objectively derived from the simulated climatology. The choice of model dependent parameters allows for an objective definition of blocking and corrects for some intrinsic model bias, the difference between model and observed thresholds providing a measure of systematic errors in the model. The model captures reasonably the main blocking features (location, amplitude, annual cycle and persistence) found in observations, but reveals a relative southward shift of Eurasian blocks and an overall underestimation of blocking activity, especially over the Euro-Atlantic sector. Blocking underestimation mostly arises from the model inability to generate long persistent blocks with the observed frequency. This error is mainly attributed to a bias in the basic state. The bias pattern consists of excessive zonal winds over the Euro-Atlantic sector and a southward shift at the exit zone of the jet stream extending into in the Eurasian continent, that are more prominent in cold and warm seasons and account for much of Euro-Atlantic and Eurasian blocking errors, respectively. It is shown that other widely used blocking indices or empirical observational thresholds may not give a proper account of the lack of realism in the model as compared with the proposed method. This suggests that in addition to blocking changes that could be ascribed to natural variability processes or climate change signals in the simulated climate, attention should be paid to significant departures in the diagnosis of phenomena that can also arise from an inappropriate adaptation of detection methods to the climate of the model.