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The general data analysis techniques described below are the same as those employed in the zonal wave analysis of \citet{IrvingSimmonds2015}. The following text is derived from there with minor modifications.  \subsubsection{Anomalies}  All anomaly data discussed in the paper represent the daily anomaly. For instance, in preparing the 30-day running mean surface air temperature anomaly data series, a 30-day running mean was first applied to the daily surface air temperature data. The mean value for each day in this 30-day running mean data series (over the entire 1979-2014 study period)  was then calculated to produce a daily climatology (i.e. the multi-year daily mean). The corresponding climatological  daily mean value was then subtracted at each data time to obtain the anomaly. \subsubsection{Composites}  Composite mean fields are presented throughout the paper for various data time subsets. To determine the statistical significance of the composite mean at each grid point, two-sided, independent sample t-tests were used to calculate the probability ($p$) that the composite mean value was not significantly different from the climatological (i.e. all data times) mean.