By: Rohit Gosh
The observed sea ice concentration (SIC) in the Arctic has been declining in recent decades. Temperatures have been rising all over the planet, but warming has been much faster over the Arctic, a phenomenon known as Arctic Amplification. We have also seen some extremely cold Eurasian winters during the same period. These cold winters lead to a Warm Arctic-Cold Eurasia (WACE) pattern in the observed surface air temperature (SAT) trend (Figure 1a). Indeed, previous studies have found links between the warming Arctic and the cooling over Eurasia. However, many opposing studies claim the observed WACE trend is simply a result of climate noise or internal atmospheric variability (Ogawa et al. 2018). Over the last five years, the observed Eurasian cooling trend has been decreasing (Figure 1), whilst SIC has continued to fall, which supports the theory that the links found can be explained by noise in the climate data. But does the recent reduced Eurasian cooling really imply that Arctic sea-ice loss plays no role in creating the WACE trend? We can figure out the answer, if we look at the two main modes of SAT variability over Eurasia and their associated dynamics.
Figure 1: a) December-January-February (DJF) surface air temperature (SAT) trend over Eurasia (20°-90°N,0-180°E) for the period 1980 to 2014 (35 years) from ERA Interim reanalysis, and b) 1980 to 2019 (40 years). Units are in K/year.
Applying principal component analysis to the winter (December-January-February, DJF) SAT variability data over Eurasia from 1980 to 2019, the first mode (EOF1) shows a Eurasian warming pattern (Figure 2a). The associated sea level pressure (SLP) shows a low centered on the Barents Sea (north of Scandinavia and Russia). This low is part of the Arctic Oscillation (AO), the main cause of Northern Hemisphere SLP variability, as the AO index has a strong correlation (Pearson correlation coefficient: 0.81) with the principal component (PC1) of the EOF1 (Figure 2c). The second mode of Eurasian SAT variability (EOF2) shows the WACE pattern, with a warm centre over the Barents Sea and a cold centre over central and eastern Eurasia (Figure 2b). The WACE pattern is associated with an SLP high centered on northern Eurasia/Siberia, which is known as the Ural blocking or Siberian high.
Figure 2: The spatial patterns (in shading) of the a) PC1/EOF1 and b) PC2/EOF2 principal component modes of winter (DJF) SAT variability over Eurasia (20°-90°N,0-180°E) in the ERA Interim reanalysis (1979-2019). The upper right corners of each panel show the explained variance fraction of each component. The EOF patterns are scaled to correspond to the one standard deviation variation of the respective principal component time series, and thus have units in K. The black contours are the SLP (in hPa) fields associated with the respective EOFs, derived by linear regression of the SLP field on the respective normalized PC time series. c) The normalized PC1 time series (in black) associated with the EOF1 patter in a) and the Arctic Oscillation index (in red), which is the normalized PC1 time series associated with the EOF1 of Northern Hemisphere (20°-90°N,180W-180°E) SLP. d) Th normalized PC2 Eurasian SAT timeseries (in black) associated with EOF2/WACE pattern in b) and the normalized sign reversed timeseries of the winter area averaged (74°N-80°N, 20°E-68°E) Barents Sea SIC (in blue). Light gray vertical lines in c) and d) shows the year 2014, when the AO changed to a positive phase.
The principle component associated with the EOF2 or WACE pattern (PC2), shows a persistent positive trend, especially after 2005 (black time series in Figure 2d). This indicates a strengthening Ural blocking. Moreover, the time series is highly correlated with the SIC anomalies over the Barents Sea (Pearson correlation coefficient: 0.85). This is the area in the Arctic which has seen the highest SIC decline (red contoured area in Figure 3), situated below the warming center of the WACE pattern. This correlation suggests that the WACE pattern is in fact, dynamically coupled with the Barents Sea-ice variations (Mori et al. 2014) and therefore not simply due to climate noise. Moreover, the WACE pattern has strengthened over the last five years, leading to an enhanced Eurasian cooling. So, if the WACE-sea-ice relation holds, how did the overall Eurasian cooling decrease? 
Figure 3: The winter (DJF) mean sea-ice concentration (SIC) trend in percent/year over the Arctic Ocean from HadISST-SIC data from 1979 to 2019. The red contour shows the Barents Sea region (74°N-80°N, 20°E-68°E).
The reduction of Eurasian cooling over the last five years is instead a result of the change in the PC1 trend from negative to positive after 2014 (black time series in Figure 2c). This change in trend effects the overall Eurasian SAT trends shown in Figure 1, which is a linear combination of the trends contributed by each principal component or EOF. The trend in PC1 is not significant as it arises mainly due to AO related internal variability. Nevertheless, until 2014, PC1 has a negative trend due to the negative phase of the AO from 2009 (Figure 2c). This brings a central Eurasian cooling response and reinforces the Barents Sea-ice forced cooling trend from the WACE pattern (Figure 2b) and enhances the Eurasian cooling signal (Figure 1a). However, by 2019, PC1 trend becomes positive due to the positive phase of AO after 2014. This leads to central Eurasian warming and competes with the significant cooling trend from the WACE pattern. The net effect is a reduced Eurasian cooling signal in the overall SAT trend (Figure 1b). Hence, in spite of an increasing WACE trend, Eurasian SAT cooling has weakened over the last five years due to the phase change of the Arctic Oscillation.
References:
Masato, M., M. Watanabe, H. Shiogama, J. Inoue, J. and M. Kimoto, 2014: Robust Arctic Sea-Ice Influence on the Frequent Eurasian Cold Winters in Past Decades, Nat. Geosci., 7, 869-873, https://doi.org/10.1038/ngeo2277
Ogawa, F., and Coauthors, 2018: Evaluating Impacts of Recent Arctic Sea Ice Loss on the Northern Hemisphere Winter Climate Change. Geophys. Res. Lett., 45, 3255–63, https://doi.org/10.1002/2017GL076502