Figure Captions
Figure 1: Representative patterns in daily 500-hPa geopotential
height anomalies [m, shaded] for all months from 1948-2019
calculated using Self-Organizing Maps. The domain covers
30oN-80oN and
180-60oW (midlatitude North America/NE Pacific).
Percentages indicate the frequency of occurrence of each node during
winter months (JFM). Numbers to left of each node are for reference
purposes. Data to generate the SOM were obtained from the NCEP/NCAR
Reanalysis (Kalnay et al., 1996).
Figure 2: Distributions of days (y-axis) of node number (1-12,
x-axis) corresponding to two days following an LDE in a particular node.
Matrices correspond to node placement in master SOM shown in Fig. 1,
indicated with bold numbers in upper left corners.
Figure 3: Change in the frequency of occurrence (days) of each
node from 1961-1989 to 1991-2019 during (a) all months and (b) winter
months (JFM). The small (large) Xs indicate changes that are
statistically significant with 90% (95%) confidence.
Figure 4: Winter (JFM) temperature extremes associated with
each node of the master SOM. (a) Number of days (shading) that air
temperature anomalies at 925 hPa exceed 1.5 σ. (b) Number of days that
air temperature anomalies at 925 hPa fall below 1.5 σ. Data are from the
NCEP/NCAR reanalysis.
Figure 5: Winter (JFM) precipitation extremes associated with
each node of the master SOM. Shading indicates number of days that daily
precipitation anomalies exceed 1.5 σ. Data are from the NCEP/NCAR
reanalysis.
Figure 6: (a) Time series of weather whiplash events (WWEs) per
year during winters (JFM) from 1949 to 2019 (x-axis), derived using data
from the NCEP reanalysis. Bold solid (dashed) lines indicate trend
significance with 95% (90%) confidence. (b) displays differences in
the number of WWEs during two 20-year intervals: 1950-1969 to 2000-2019.
The X indicates statistical significance > 95% based on
student’s t-test.
Figure 7: Timeseries of Euclidean distances (y-axis, unitless)
between the node in which an LDE occurs and the node that contains the
daily field two days after the LDE, averaged over winter months (JFM)
each year from 1950 to 2019 (x-axis). Bold (thin) trend lines are
significant at 95% (90%).
Figure 8: Changes in the number of winter (JFM) WWEs from
1979-1989 to 1995-2005 in (a) NCEP/NCAR reanalysis output and in
historical simulations from three global climate models: (b) CCSM4, (c)
CanESM2, and (d) GFDL-CM3. The small (large) Xs indicate statistical
significance > 90% (> 95%) based on a
student’s t-test.
Figure 9: Projected changes in the number of winter (JFM) WWEs
from 2006-2030 to 2076-2100 in (a) CCSM4, (b) CanESM2, and (c) GFDL-CM3.
The Xs indicate statistical significance > 95% based on a
student’s t-test.