The forecast skill of both models is investigated by conducting 50 ensembles of each forecast to obtain enough statistics to draw statistically significant conclusions about winters with and without SSWs. We create a simulation matrix with several different simulation start dates and initial conditions with different phases of the Quasi-Biennial Oscillation (QBO) and the El Nino Southern Oscillation (ENSO). The impact of these factors on the forecast skill is examined by focusing on sea level pressure and temperature patterns, as well as temperature extremes. We find that the largest differences between forecasted surface pressure and temperature are over Europe and Eurasia, and occur between the 46L ensembles with and without SSWs. Forecast skill varies, but the 46L model tends to perform better when a SSW event is present.
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