Monday, 26 June 2017
Salon A-E (Marriott Portland Downtown Waterfront)
The downward influence of stratospheric sudden warmings (SSWs) can create significant tropospheric circulation anomalies that last for several weeks. It is therefore of theoretical and practical interest to understand the month when SSWs are most likely to occur and the controlling factors for their temporal distribution. Conceivably, the distribution is controlled by the interplay between decreasing stratospheric wave driving and weakening stratospheric polar vortex strength. General circulation models (GCMs) tend to produce SSW maxima later in winter than observations, which has been considered as a model deficiency. However, the observed record is short, suggesting that under-sampling of SSWs may contribute to this discrepancy. Here, we study the climatological frequency distribution of SSWs and related events in a long control simulation with a stratosphere resolving GCM. We also create a simple statistical model to determine the primary factors controlling the SSW distribution. The statistical model is based on the daily climatological mean, standard deviation, and autocorrelation of stratospheric winds, and assumes that the winds follow a normal distribution. We find that the null hypothesis, that model and observations stem from the same distribution, cannot be rejected, suggesting that the mid-winter SSW maximum seen in the observations is due to sampling uncertainty. We also find that the statistical model faithfully reproduces the seasonal distribution of SSWs, and that the decreasing climatological strength of the polar vortex is the primary factor for it. We conclude that the late-winter SSW maximum seen in most models is realistic and that late events will be more prominent in future observations. We further conclude that SSWs simply form the tail of normally distributed stratospheric winds, suggesting that there is a continuum of weak polar vortex states and that statistically there is nothing special about the zero-threshold used to define SSWs.
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