The predictability of atmospheric blocking in global ensemble prediction systems

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Blocking is an atmospheric phenomenon which has major implications for local weather. It can lead to extremely high or low temperatures due to the long lasting almost stationary high pressure system. Furthermore, a block can exert a strong impact on upstream, in-situ and downstream synoptic weather patterns by disrupting the midlatitude westerly flow. Thereby, blocking can be the cause for severe precipitation anomalies in cut-off lows surrounding the high pressure system. The state of the art ensemble prediction systems (EPSs) which are part of the THORPEX Interactive Grand Global Ensemble (TIGGE) perform well in predicting the frequencies of Atlantic European and Pacific blocking but have difficulties in predicting the onset and the decay of blocking. The predictability of the onset is about 1 day worse than the predictability if the blocking is already specified in the initial conditions. Furthermore, the TIGGE ensemble prediction systems (EPSs) have problems in simulating the frequencies of Greenland and Ural blocking. This study is dedicated to investigate the dynamics of selected blocking events in the medium range, the monthly, and the seasonal ECMWF EPS. Two different clustering methods based on EOF/PC 3 analysis and one method based on ensemble analysis covariance will be applied to the EPSs. Links between different types of block formation or decay and large scale events like breaking Rossby waves or small scale diabatic processes like precipitation resulting from the advection of moist air masses will be investigated. Their roles in the life cycle of a blocking event will be compared. The same investigation methods will be applied to the TIGGE ensembles and to carry forward the results obtained for the medium range ECMWF EPS alone. Additionally, for two winter seasons and for a whole year scores and skill scores used at the ECMWF will be calculated and the predictive skill of the EPSs will be assessed with regard to blockings.