While many studies comparing atmospheric reanalysis and surface observations have focused on the similarity of mean fields, trends, or frequencies of extreme events, very few have assessed how similar surface observations and reanalysis data sets are in terms of their specific identification of extreme temperature event days. Here, we assess the similarity between surface observations and three reanalysis products: ERA5, ERA5‐LAND, and NARR, in terms of the days on which they identify extreme heat and cold events for the period 1979–2016 at 230 locations in the United States and Canada. Cold events have a greater match than heat events. ERA5 has the greatest match percentage with station data across the study region. Match percentage is greatest in midlatitude, continental locations, with poorer performance in coastal areas, and the Arctic.

Periods of extreme cold impact the mid‐latitudes every winter. Depending on the magnitude and duration of the occurrence, extremely cold periods may be deemed cold air outbreaks (CAOs). A systematic CAO index and ranking system was developed from 20 surface weather stations from 1948 through 2016, based on a set of criteria concerning magnitude, duration, and spatial extent. Standard deviations in temperature were used to identify extreme temperatures relative to the station. A total of 49 CAOs occurred during the 67‐year period, with the majority occurring during mid‐winter. The number of CAOs proved to be largely dependent on the stations latitude and maritime influence. The duration, magnitude, and spatial extent were dependent on the time of the winter season in which the CAO occurred. Furthermore, two prominent clusters of an increased number of CAOs occurred during the 67‐year period, suggesting multi‐decadal circulations may be a factor in CAOs.

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Reconstructed sea surface temperatures (SSTs) derived from Mg/Ca measurements in nine encrusting coralline algal skeletons from the Aleutian archipelago in the northernmost Pacific Ocean reveal an overall increase in SST from 1665 to 2007. In the Aleutian SST reconstruction, decadal‐scale variability is a transient feature present during the 1700s and early 1800s and then fully emerging post‐1950. SSTs vary coherently with available instrument records of cyclone variance and vacillate in and out of coherence with multicentennial Pacific Northwest drought reconstructions as a response to SST‐driven alterations of storm tracks reaching North America. These results indicate that an influence of decadal‐scale variability on the North Pacific storm tracks only became apparent during the midtwentieth century. Furthermore, what has been assumed as natural variability in the North Pacific, based on twentieth century instrumental data, is not consistent with the long‐term natural variability evident in reconstructed SSTs predating the anthropogenic influence.

In this paper, we build upon previous literature in directly addressing the temporal relationship between the stratospheric and tropospheric polar vortex (PV), sea level pressure (SLP), and resultant cold air outbreaks (CAO). An atmospheric and teleconnection analysis was conducted on 49 predefined CAOs across the eastern United States from 1948 to 2016. Clusters of SLP, 100 and 10‐mb geopotential height anomalies were mapped utilizing self‐organizing maps (SOMs) to understand the surface, tropospheric PV, and stratospheric PV patterns preceding CAOs. The Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Pacific–North American (PNA) teleconnections were used as variables to explain the magnitude and location of mid‐latitude Arctic air displacement. Persistently negative SLP anomalies across the Arctic and North Atlantic were evident 1–2 weeks prior to the CAOs throughout the winter. The tropospheric and stratospheric PV were found to be persistently weak/weakening prior to mid‐winter CAOs and predominantly strong and off‐centred prior to early and late season CAOs. Negative phases of the AO and NAO were favoured prior to CAOs, while the PNA was found to be less applicable. This method of CAO and synoptic pattern characterization benefits from a continuous pattern representation and provides insight as to how specific teleconnections and atmospheric patterns lead to CAOs in the eastern United States.