Anomalous Arctic warming linked with severe winter weather in Northern Hemisphere continents

Anomalous Arctic warming linked with severe winter weather in Northern Hemisphere continents | Communications Earth & Environment

Abstract

We have extended a recently developed metric that ingests United States station data—the accumulated winter season severity index—to a global indicator based on temperature and snowfall from reanalysis output. The expanded index is analyzed to reveal relationships between Arctic air temperatures/pressures and the probability of severe winter weather across the Northern Hemisphere midlatitudes. Here we find a direct and quasilinear relationship between anomalously high Arctic temperatures/pressures and increased severe winter weather, especially in northeastern continental regions downstream of maximum regional Arctic warming. Positive temperature trends in the Arctic are associated with positive trends in severe winter weather across the continents in mid- to late-winter, coinciding with an increase in stratospheric polar vortex disruptions. During the era of rapid Arctic warming, variability has decreased over the Arctic Ocean and Europe, but has increased in Canada, the Northern US and northeast Asia, indicating more pronounced shifts in weather conditions.

Introduction

The Arctic cryosphere is an integral part of the Earth’s climate system that has recently undergone unprecedented changes over the observational record 1 including melting sea ice 2, 3 and diminishing spring snow cover 4, 5. Since the mid-1990s the region has exhibited an amplified signal of global warming (a.k.a. amplified or accelerated Arctic warming; AAW 4, 6, 7). It is particularly robust during fall and winter (e.g., Dai et al. 8; Cohen et al. 9), when it is observed to be two to four times greater in the Arctic relative to the rest of the globe 7, 10. AAW is consistent with model predictions that the Arctic will warm faster than elsewhere across the globe in response to increasing greenhouse gases (e.g., Alexeev et al. 11; Barnes and Polvani 12) and remote influences (e.g., Porter et al. 13; Ding et al. 14), which are subsequently amplified by a variety of positive feedback mechanisms involving sea ice, snow cover, atmospheric moisture, atmospheric lapse rate and atmospheric and oceanic energy transport (e.g., Pithan and Mauritsen 15; Burt et al. 2016 16; Goosse et al. 17; Dai et al. 8; Previdi et al. 18; Dai and Jenkins 19; Oldenberg et al. 20).

Coincident with AAW, an increase in the frequency of some types of extreme weather events has been observed (e.g., Cohen et al. 4; Coumou and Rahmstorf 21; Munich Re 22; Herring et al. 23; Diffenbaugh et al. 24; Di Capua and Rahmstorf 25). Notably, 2023 produced the highest number of billion-dollar disasters per year on record for the US (in large part due to severe thunderstorms), with damage costs approximately $95 billion 26. According to analysis by Munich Re (a major reinsurance company), the global frequency of extreme weather events causing more than $1B in damage has tripled since the early 1980s. Although the term extreme weather is used to describe a range of phenomena, the common trait is the potential for high socioeconomic disruption. Such events can be either short-lived (e.g., a strong hurricane, blizzard, or tornado) or result from persistent conditions that last for weeks to months (e.g., heat waves, cold spells, droughts, and floods). Gasparrini et al. 27 and Zhao et al. 28 attributed a far higher (approximately 10×) mortality to moderate but persistent cold spells rather than to heat waves. Analysis of the most disruptive snowstorms in the populated US Northeast, as compiled by NOAA using the Northeast Snowfall Impact Scale (NESIS), indicates a tripling of disruptive storms over the decade through 2018 compared to previous decades 9.

Because of their potentially destructive and expensive impacts on society and ecosystems, weather extremes have garnered a great deal of interest by researchers, media, public, business leaders, and policymakers. The projected change in frequency and intensity of extreme weather events is considered one of the principal, yet least understood, impacts of climate change 23, 29, 30. This incomplete understanding of the dynamics and feedback mechanisms linking changes in climate with weather extremes contributes to poor predictability of extreme events 31, 32, which can lead to inadequate preparation at all levels of government and industry along with avoidable losses of property and life.

A topic of recent scientific inquiry and debate is whether one of the most conspicuous symptoms of climate change—AAW—and the increased frequency of extreme weather events are physically linked. Several mechanisms for the linkage have been hypothesized, and recent studies reveal that different mechanisms operate in different seasons, regions, and background climate states. In general, AAW is thought to cause a remote response of the extratropical atmospheric circulation, manifesting in changes to the jet stream that favor more persistent midlatitude weather regimes 33, 34, 35 such as blocking events 36, 37, 38; high-amplitude, slow-moving meridional waves 39, 40, 41; cut-off lows; and stagnant summer patterns 42, 43, 44, 45—all of which can spawn extreme weather events.

This study builds upon past investigations of Arctic variability and statistical associations with extreme winter weather events 46, 47, 48, 49. In particular, we have expanded and extended the approach by Cohen et al. 47(hereafter C18) in which meteorological station data across the US were used to establish associations between episodes of Arctic warm anomalies and an index of severe winter weather (AWSSI—see Methods) at weather stations throughout the United States (US). In this study we adapted the computation of the AWSSI to a metric based on gridded data sets, namely the ERA5 reanalysis 50, allowing exploration of relationships across the globe. Here we mainly focus on Northern Hemisphere (NH) land areas during winter (December-February). ERA5 reanalysis compares favorably with station data for surface temperature 51, 52 and snowfall and snow depth 53, 54 and is generally considered the best reanalysis dataset currently available.

This extended analysis is an important advance from C18. Studies between AAW and midlatitude winter weather tend to focus primarily on temperature, particularly on seasonal means. The potential societal impacts of AAW, however, also include daily extremes: days below freezing, snowfall, snow depth and other variables. As seen in our analysis, sometimes snowfall trends are consistent with temperature trends, while in other cases they diverge depending on the region and timeframe. Our study encompasses these impacts not only across the lower 48 states of the US, but also across Eurasia and Canada. The new gridded version of the AWSSI allows for analyses of historical data around the Northern and Southern (not addressed here) Hemispheres using both reanalysis output and model simulations. It can also be utilized to inform subseasonal-to-seasonal forecasts and even long-term annual-to-decadal model projections, providing important information to decisionmakers endeavoring to plan for extreme winter weather events. Finally, this new analysis provides further insight into the relationships between Arctic temperature or geopotential height variability with continental severe winter weather beyond that revealed in C18.

Results and discussion

In Fig. 1, we present the climatology of the total reanalysis-based AWSSI (rAWSSI) as well as the temperature-only and snowfall-only contributions to the index across the NH. As expected, the rAWSSI generally increases from south to north and from west to east across the continents, with highest values in areas where cold temperatures and/or snowfall are likely. Separating the index into its two components reveals that severe cold is the dominant contributor to high-index values in most areas, particularly over Siberia, northern Canada and Greenland. The largest contributions from snowfall occur over high terrain, including the Rockies, Greenland, the Alps and the Himalayas, with highest values over the west-coast mountains of North America. Greenland is one of the few regions with large contributions from both cold and snowfall.

The new reanalysis-based AWSSI index (rAWSSI) is averaged over winter (DJF) and from 1950 through 2023. a is the total value, b only temperature-related contributions to the rAWSSI, and c only snow-related contributions to the rAWSSI.

Validation of correlations between PCH/PCT anomalies and rAWSSI

One of the major findings of C18 was a strong nearly linear relationship between polar cap geopotential heights (PCHs) or polar cap temperatures (PCTs) with the station-based AWSSI in a selection of US cities. Composite analysis revealed a strong relationship for northeastern cities, where severe winter weather was much less likely when the Arctic was abnormally cold and much more likely when the Arctic was abnormally warm. In the present study, we performed the same composite analysis as in C18 but using instead the reanalysis-based rAWSSI, selecting the nearest gridpoint to the same US cities. All cities shown in our analysis are indicated on a NH map shown in Supplementary Fig. 1. Supplementary Fig. 2 compares the time series of station-based AWSSI values with reanalysis-based rAWSSI values at selected US cities, indicating similar values and variability in the two metrics. In Fig. 2a from C18 but here using the new rAWSSI values. The full set of US cities for PCH is included in Supplementary Fig. 3. This extended analysis displays the same strong and direct relationship that exists between Arctic PCHs and severe winter weather in the US as that found in C18, including values updated through winter 2022/23.

Daily departures from the winter average in the rAWSSI at gridpoints closest to several cities across the US during winter (DJF, shading) are composited for standard anomalies in polar-cap (north of 65oN) geopotential heights (PCH; top) and temperature (PCT; bottom) from 1000 hPa to 10 hPa (y-axis) from 1950 to 2023 for Bismarck ND, Chicago IL and Boston MA (represented by Blue Hills). Blue (red) shades indicate severe (mild) winter weather coinciding with positive (negative) PCH anomalies. Anomalies are computed relative to the climatology from 1981–2010.

In Chicago, IL, for example, the blue shading along the right side of the plot indicates that PCH anomalies are strongly positive ( > 1 on the x axis) from the surface to ~30 hPa when rAWSSI daily values are also positive (blue shading), suggesting that severe winter weather is more likely when geopotential heights over the Arctic are anomalously high. A strong relationship between higher Arctic pressures/geopotential heights throughout the troposphere and an increased frequency of severe winter weather is apparent for all cities east of the Rockies, with the strongest association in the northern half of the US. When Arctic geopotential heights are abnormally low (PCH <−1), the occurrence of severe winter weather is unlikely (red shading). In the Rockies and along the west coast, however, the relationship is weak, and some stations even exhibit the opposite relationship, i.e., a relatively warm Arctic is related to milder winter weather (Supplementary Fig. 3). Why the relationship between Arctic pressures/heights and severe winter weather is of opposite signs east and west of the Rockies is not fully understood though a similar relationship exists between the Arctic Oscillation (AO), the strength of the stratospheric polar vortex, and US temperatures. When the Arctic is warm and/or dominated by high pressure, a western jet-stream ridge and eastern trough pattern often occurs that transports subtropical Pacific air northward into the western US and western Canada, while continental Arctic air flows southward into states east of the Rockies. A positive AO is associated with a cold Arctic and lower pressure, which often coincides with a western trough/eastern ridge pattern that delivers polar maritime air to the west coast of North America and mild subtropical airmasses to eastern states 55. This is also consistent with the observed predominance of an anomalous western ridge during the recent period of pronounced AAW 56. In the southern US, where snowfall and below-freezing temperatures are uncommon, the quasi-linear relationship between Arctic temperatures and severe winter weather is still evident but weaker (e.g., see Atlanta GA).

Also shown in Fig. 2 is the relationship between PCT and rAWSSI (the full set of cities is shown in Supplementary Fig. 4). Though the relationships between PCTs and severe winter weather are qualitatively similar to PCHs, they are more complex than what was previously shown in C18 (where the AWSSI derived from station data is related to PCH and PCT based on NCEP/NCAR reanalysis) owing to differences between PCH and PCT in the lower troposphere. We find positive lower-tropospheric PCT anomalies (warm Arctic troposphere) are generally associated with positive rAWSSI values (enhanced winter extremes), although negative tropospheric PCT anomalies are also associated with positive rAWSSI values in some cases. From the mid-troposphere to the lower stratosphere, however, the PCT and PCH relationships with rAWSSI are consistent: warmer Arctic temperatures are associated with positive rAWSSI and colder Arctic temperatures are associated with negative rAWSSI. This result is consistent with recent modeling studies that suggest only deep Arctic warming – extending into the mid- to upper-troposphere and lower stratosphere – is likely to force severe winter weather in the midlatitudes 57, 58, 59, 60.

This relationship is further highlighted in Fig. 3 in which we display spatial composites of gridded rAWSSI values over the full range of PCH and PCT standard anomaly values in the mid-troposphere (500 hPa). The results for the two polar-cap values are similar in that warmer temperatures and higher geopotential heights across the Arctic favor a more widespread increase in severe winter weather across the continental mid-latitudes, while colder PCTs and lower PCHs favor a limited enhancement of severe winter weather.

rAWSSI values (shaded) are composited according to standardized 500 hPa anomalies of PCH (a, b) and PCT (c, d). Negative polar cap anomalies (−3.0 to −0.5) are plotted on the left (a, c), positive values (0.5 to 3.0) on the right (b, d). Hatching indicates significance at p < 0.05.

As in C18 we also computed the lead-lag between mid-tropospheric PCHs and the rAWSSI, displayed in Supplementary Fig. 5. We found the reanalysis-based index produced similar results to the station-based index, with the peak in correlation occurring when PCHs lead US severe winter weather by about three days. The correlations are weaker with rAWSSI, likely owing to values averaged over a larger area in the reanalysis data compared with the station data.

PCH/PCT anomalies and hemispheric rAWSSI

Having demonstrated the consistency between PCH/PCT and for both the station-based AWSSI and the new rAWSSI for US cities, we now expand our analysis to the entire NH to test whether the strong relationship between Arctic geopotential heights/temperatures and severe winter weather in the northern and eastern US exists elsewhere across Canada, Europe and Asia.

Analysis from Fig. 3 indicates a statistically significant correspondence between warm and cold PCH/PCT anomalies and the rAWSSI. As seen in Fig. 3a, c, over the Arctic, negative PCH/PCT anomalies (cold Arctic) are associated with positive rAWSSI values over the Arctic (i.e., more severe winter weather), while severe winter weather is near normal to slightly below normal in the eastern US, Europe and northeastern Asia. In contrast, when positive PCH/PCT anomalies are widespread across the Arctic, severe winter weather is normal to above normal across much of the NH continents, including northern Europe, northern Asia, most of Canada and the northern US east of the Rocky Mountains, while severe winter conditions over the Arctic itself are less likely (Fig. 3b, d). The increased probability of severe winter weather is most sensitive to a warm Arctic in a band between 40 and 60°N across North America, Europe and Asia.

PCH/PCT anomalies and severe winter weather in Europe and Asia

Having demonstrated that the relationship between Arctic atmospheric variability and the occurrence of severe winter weather is robust not only in North America but also across much of northern Eurasia, we extend the composite analysis for selected individual cities across Europe and Asia. Figure 4 is similar to Fig. 2 in displaying composites of rAWSSI corresponding with varying PCH/PCT anomalies for three major northeastern European cities (a larger set of nine cities is shown in Supplementary Figs. 6 and 7). As was the case in the US, the relationship between PCH/PCT and rAWSSI is strongest across northeastern locations (e.g., Scandinavia) and weakest across western Europe (e.g., London and Paris). Also, the relationship between PCHs and severe winter weather in Europe is consistent throughout the depth of the atmosphere while the relationship between PCT and severe winter weather is weaker in the mid to lower troposphere and stronger from the mid-troposphere through the lower stratosphere and even into the mid-stratosphere.

Same as Fig. 2 but for Copenhagen, Stockholm and Helsinki.

Figure 5 displays the same analysis of PCH/PCT for three cities in Russia; an expanded set of eight cities in eastern Europe, Siberia and northeast Asia is shown in Supplementary Figs. 8 and 9. Cities in eastern Europe and Russia exhibit a strong relationship between PCHs and the likelihood of severe winter weather. The large population centers in northeast Asia also experience more severe winter weather when the pan-Arctic is relatively warm, but the relationship is weaker near the coast than in other Eurasian cities that experience more continental climates. Also consistent with results for the US and Europe, the relationship between Arctic air temperatures and severe winter weather across Asia is stronger from the mid-troposphere through the low- to mid-stratosphere and weaker in the lower troposphere.

Same as Fig. 2 but for Moscow, Novosibirsk and Tomsk.

In summary, our analysis for cities in the northeastern US, northeastern Europe, and northern Asia reveals a robust and nearly linear relationship between pan-Arctic geopotential height/temperature anomalies and the likelihood of severe winter weather: a colder Arctic is associated with less frequent severe winter weather while a warmer Arctic is related to more frequent severe winter weather, especially from the mid-troposphere through the mid-stratosphere. In cities with maritime climates, including parts of the western U.S., western Europe, and East Asia, winter weather is less influenced by Arctic variability, according to our results presented in Figs. 2– 5 and Supplementary Figs. 3– 4 and 6– 9.

Regional Arctic warming and regional severe weather

In the cases of positive PCH (Fig. 3b) and PCT (Fig. 3d) anomalies, the associated values of rAWSSI have clear regional variations across the Arctic. In particular, the largest negative values (red shading) are not uniformly spread across the Arctic but rather are strongest in three regions—the Kara Sea, the Chukchi-Bering Seas, and the vicinity of Greenland—indicating that these areas experience relatively mild winter weather when PCH/PCT anomalies are positive. In contrast, positive PCH/PCT anomalies also correspond with maximum positive rAWSSI values (severe winter conditions) over midlatitude continents. Regional variations in Arctic tropospheric warming may influence the location and severity of winter conditions in midlatitudes, so to investigate these further, we composited hemispheric rAWSSI values corresponding with above- and below-normal temperatures at 500 hPa over four of the marginal Arctic seas (Fig. 6).

rAWSSI anomalies are composited for regional 500 hPa standard temperature anomalies less than −0.5 over (a) Barents-Kara Seas, (c) Baffin Bay, (e) between Greenland and Iceland, (g) Chukchi and Bering Seas and (i) pan-Arctic. (b), (d), (f), (h), and (j) are the same but for regional 500 hPa standard temperature anomalies greater than +0.5.

First, we analyze in the North Atlantic sector where we find that when temperature anomalies are negative over the Barents-Kara Seas (Fig. 6a), the largest average rAWSSI positive anomalies are located in the same general area along with a region of negative rAWSSI downstream in Siberia. In contrast, when temperature anomalies are positive (Fig. 6b), rAWSSI anomalies are negative over the Barents-Kara Seas, while the largest positive rAWSSI values are located downstream across Siberia and northeastern Eurasia, suggesting a higher likelihood of severe winter conditions in northern and eastern Asia when above-normal Arctic tropospheric temperatures are focused in the Barents-Kara Seas region. This finding is consistent with extensive previous literature (e.g., Honda et al. 61; Kim et al. 48; Li et al. 62; Yin et al. 63).

Figure 6c presents the rAWSSI values associated with negative 500 hPa temperature anomalies in the vicinity of Greenland. Similar to what is observed for the Barents-Kara, in the region east of Greenland, negative temperature anomalies are nearly co-located with strongly positive rAWSSI values, suggesting harsh winter conditions occur in the same general region of northeastern Canada as negative temperatures centered along Baffin Bay. However, when temperatures over the area are abnormally warm (Fig. 6d), negative rAWSSI anomalies occur in and around Baffin Bay, while severe winter weather is more likely across much of northern North America and northern Eurasia. This suggests relatively mild conditions near Greenland are associated with severe winter weather in the high latitudes of Canada, Europe, and Siberia. The inverse relation found between Greenland temperature anomalies and those of northern Eurasia and parts of eastern North America is consistent with variability in the AO and/or the North Atlantic Oscillation, which is often associated with the presence or absence of Greenland blocking 64. Similar results are found with mid-tropospheric temperature anomalies east of Greenland (Fig. 6 e, f), though when temperature anomalies are positive, the largest negative rAWSSI values are over Greenland along with positive and larger rAWSSI values over northern Eurasia.

When regional temperature anomalies are focused over the Chukchi-Bering Seas, displayed in Fig. 6 g, h, we find once again that when temperatures are abnormally cold, severe winter weather is more likely in the North Pacific side of the Arctic, including Alaska and eastern Siberia, but more muted across the NH continents, particularly across central Canada. In contrast, when temperatures are abnormally warm in the Chukchi-Bering Seas region (Fig. 6i), rAWSSI values are strongly positive over North America north of ~40oN, suggesting a higher likelihood of severe winter conditions. This result is consistent with previous analysis from Kug et al. 49.

Finally, for completeness, we present rAWSSI values associated with pan-Arctic 500 hPa temperature anomalies (Fig. 6 i, j). It is apparent that the rAWSSI values associated with regional temperature anomalies appear to combine approximately linearly to produce the pan-Arctic patterns, more so across North America than Eurasia. When warming is pan-Arctic, the increase in severe winter weather across northern Eurasia and northeastern North America is more damped than might be expected by linearly adding the regional contributions, especially in comparison with warming focused over the Barents-Kara Seas (see Supplementary Fig. 10). These results are consistent with analyses of atmospheric responses to pan-Arctic sea-ice anomalies by Screen 65 and Cohen et al. 9.

Trends in PCHs/PCTs and rAWSSI

One notable finding from C18 was that daily AWSSI exhibited a negative trend over the period of AAW (post-1990) during early winter in eastern US cities, but during late winter (after mid-January) the trend became positive, indicating an increase in severe winter weather. Meanwhile, the corresponding trends in PCH anomalies were positive in the entire troposphere throughout the winter season. In the stratosphere, however, PCHs decreased during early winter then increased in late winter, thus the PCH trends in the troposphere and stratosphere were of opposite sign during early winter but were of the same sign during late winter. These findings suggested that the trends in severe winter weather are sensitive to the strength of the stratospheric polar vortex (SPV): in early winter when the SPV strengthens, severe winter weather decreases, while in late winter when the SPV generally weakens, and vortex disruptions (sudden stratospheric warmings, splits, and displacements) are more likely, severe winter weather increases in most northeastern US cities.

Here we update this analysis using rAWSSI at gridpoints that include the same US cities as in C18 (see Supplementary Figs. 11 and 12), with the example of Chicago IL displayed in Fig. 7. Similar to results in C18, we find that during the period of AAW, tropospheric trends in PCH/PCT were positive throughout the winter (red shading), while in the stratosphere, PCHs/PCTs decreased in the early winter then mostly increased middle to late winter. Consistent with Fig. 2, trends in severe winter weather in Chicago were sensitive to the depth of Arctic warming. When Arctic warming was confined to mid- to low-troposphere, severe weather generally decreased, but conversely when Arctic warming extended into the upper troposphere and lower stratosphere, severe winter weather increased. This result is consistent with previous studies suggesting that deep Arctic warming corresponds with an increased frequency of SPV disruptions both in the mid-stratosphere 66 and lower stratosphere 67. Corresponding trends in rAWSSI are generally neutral or negative during the early winter then tend to become positive during late winter when both PCH and PCT trends are positive in the upper troposphere and stratosphere.

Decadal trends in annual-average daily anomalies in PCH (shading, top) and PCT (shading, bottom) from the surface to the mid-stratosphere (10 hPa) and annual trends in the daily averaged change in the rAWSSI (black lines) for Chicago during the winters 1990/91–2022/23.

We expand this analysis to include cities across Eurasia (Figs. 8 and 9). Figure 8 is the same as Fig. 7 but for Stockholm (the full set of European cities shown in Supplementary Figs. 13 and 14). Western locations in Europe exhibit little coherence between trends in PCHs and rAWSSI owing to the strong influence of marine weather systems from the North Atlantic. Locations farther east, however, behave similarly to central US cities, especially those cities in Scandinavia.

Same as Fig. 7 but for Stockholm.

Same as Fig. 7 but for Tomsk.

As we found for North American cities, when the SPV strengthens in early winter, severe winter weather decreases, while in late winter when the SPV generally weakens and is more likely to be disrupted, severe winter weather increases in many northern and eastern European cities. The relationship is even more robust in central Asian locations (Fig. 9, Supplementary Figs. 15 and 16), where positive PCH trends in early winter are associated with negative trends in rAWSSI. Later in winter when positive PCH trends extend into the stratosphere, trends in rAWSSI generally become more positive. Similarly, when Arctic warming is shallow, severe winter weather generally decreases, while deep Arctic warming is associated with increased severe winter weather. This relationship is consistent with previous studies suggesting a warmer and weaker SPV is often associated with severe winter weather in central Asia 66. In summary, we find a common relationship across the NH mid-latitude continents, suggesting that severe winter weather has become less likely in early winter but more likely in mid- to late-winter—especially in the central US states, Scandinavia, eastern Europe, and Siberia—when the SPV is increasingly likely to be disrupted in mid-late winter 68 and when Arctic warming is deep rather than shallow.

In conclusion, we find that during the period of AAW (post 1990), Arctic warming is generally confined to the low- to mid-troposphere during early winter (December through early January), while severe winter weather generally decreases across the US and Eurasia. By mid-January, Arctic warming typically extends into the upper troposphere and into the stratosphere along with a coincident jump in the occurrence of severe winter weather in the northeastern US, northern Europe and northern Asia. We find Asian cities in particular exhibit the greatest sensitivity to deep Arctic warming.

Why does Arctic warming transition from shallow to deep layers in mid-January? Trends in December 500 hPa geopotential heights indicate the largest positive height trends over the Barents/Kara/Laptev Seas (the region of greatest sea-ice melt in late fall and early winter 9) and Urals (Supplementary Fig. 17). Abnormal warmth and high geopotential heights in this region coupled with lower heights downstream over East Asia favor the excitement of upward Rossby wave activity flux (WAFz). We include daily trends of WAFz (see Supplementary Fig. 18), which increases in late December in the troposphere and then extends into the stratosphere early to mid-January. This leads to the expansion of warming into the upper troposphere and stratosphere along with increasing PCHs related to a weakening of the SPV. Though our observational analysis cannot demonstrate causal links, the findings are consistent with previous observational and modeling studies on the dynamical impacts of melting sea ice in the Barents-Kara Seas during late fall and early winter 9, 48, 57, 58, 59, 60, 61, 62, 63.

Hemispheric trends in rAWSSI

In Fig. 10, we present the trends in rAWSSI for three different periods of winters: 1950/51–2022/23 (the entire ERA5 reanalysis period); 1990/91–2022/23, and 2000/01–2022/23 (spanning two periods of AAW following Cohen et al. 69). Over the entire reanalysis period (Fig. 10a) the trends in rAWSSI were negative everywhere, with the exception of a local positive trend in central Asia. This indicates severe winter weather generally decreased, with largest declines over the Arctic Ocean, particularly in the Barents-Kara Seas. During the years since 1990 when AAW began to emerge, areas of positive trends in rAWSSI appear over northeast Asia and the high elevations of North America. Since 2000, the area exhibiting an increase in rAWSSI became more widespread over northern North America and Greenland but diminished over Asia, suggesting a higher likelihood of severe winter weather over North America and Greenland during the recent acceleration of Arctic tropospheric warming.

Decadal trends in rAWSSI during three different time intervals: winters of (a) 1950/51–2022/23, (b) 1990/91–22/2023, and (c) 2000/01–2022/23.

Supplementary Figs. 19 and 20 display winter-mean trends in the two components of rAWSSI contributed by temperature only and snow only. Trends in temperature only were similar to those for the total rAWSSI, exhibiting negative trends only over the full reanalysis period. In later periods, positive trends in the index (colder temperatures) appeared across the continents and were most widespread across Asia since 1990 and across North America since 2000. Patterns of the snowfall-only contribution to rAWSSI trends differed from the total and temperature-only rAWSSI patterns in that large regions of positive trends in snowfall were observed since 2000 across both North America and Eurasia. Why do we observe that increasing trends in snowfall were more widespread than trends in severe cold and the total rAWSSI during the period of AAW is an interesting question. One plausible explanation is that increased evaporation from warmer oceans into a warmer atmosphere is contributing to greater snowfall in regions where temperatures remain below freezing, especially in the interior of the continents, a hypothesis supported by Liu et al. 70.

Hemispheric trends in variability

Our final analysis is to investigate trends in the variability of severe winter weather, an indication of “weather whiplash” or the likelihood of abrupt changes in weather conditions. Supplementary Fig. 21 displays the decadal trend in the standard deviation of daily rAWSSI calculated as a five-day running mean over the same three time periods used for our rAWSSI trend analysis. Over the entire reanalysis period (Supplementary Fig. 21a) the trends in standard deviation were negative but weak, with most negative values occurring over the Arctic. Since 1990 (Supplementary Fig. 21b), trends over the Arctic were more strongly negative, indicating a decline in variability, along with mixed trends over the continents. Since 2000 (Supplementary Fig. 21c) trends over the Arctic became increasingly negative, but those over large swaths of the continents exhibited increased variability, especially across the midlatitudes of North America. This finding suggests a higher likelihood of volatile weather swings known as weather whiplash as AAW intensifies, consistent with Francis et al. 71, 72.

One possible explanation for these findings is that an increase in SPV variability can contribute to more severe winter weather across the NH 66, 67. To explore this potential connection, we analyzed trends in daily variability of 5-day running means in 10 hPa temperatures (Supplementary Fig. 22) and 10 hPa geopotential heights (Supplementary Fig. 23). Variability in both variables increased for all periods analyzed (blue shading), supporting a possible association between increased variability in the SPV and increased variability in severe winter weather over the continents. In particular, the region of increased variability in the polar stratosphere during the period of AAW extends from Central Asia to central North America resembling the stretched pattern of the SPV that occurred more frequently during the period of AAW 67. One notable exception is decreased variability (red shading) over the northern Atlantic, Barents-Kara Seas, and the Baltics region since 2000. Interestingly this is also the region of greatest warming in boreal winter in the troposphere.

Conclusions

In this study we build upon our earlier work that investigated the association between Arctic atmospheric conditions—anomalously low/high geopotential heights and cold/warm phases—and the prevalence of severe winter weather across a selection of major US cities. The earlier work was based on a metric called the AWSSI 73, an indicator that combines extreme cold and snowfall into a daily index that is accumulated through the winter season. Anomalies in the index were analyzed in combination with daily assessments of anomalies in polar-cap geopotential heights and temperatures (PCHs/PCTs) from the surface upward through the stratosphere. This prototype study revealed a strong relationship between abnormally high geopotential heights and/or warm temperatures and a tendency for increased severe winter weather in eastern US cities. This new study expands the analysis to the entire globe by calculating the index from reanalysis fields, the rAWSSI. The reanalysis-based index exhibited nearly identical relationships to those found using the station-based index across the US, thereby validating its consistency, as well as similar relationships across Europe and Asia. One important new finding is that the relationship between deep Arctic warming throughout the atmospheric column and continental severe winter weather is much stronger than for shallow (near-surface) Arctic warming. Extending the analysis further, we assessed relationships between anomalies in mid-tropospheric PCT (at 500 hPa) over selected Arctic regions and the rAWSSI, we investigated trends in the index together with trends in PCHs and PCTs, and we analyzed changes in variability over differing time intervals since 1950.

The main findings from this expanded analysis are summarized below:

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For cities in the northern and eastern US, northern and eastern Europe, and northern Asia, a robust and quasi-linear relationship exists between pan-Arctic geopotential heights/temperatures and the likelihood of severe winter weather. A colder Arctic is related to less frequent severe winter weather in midlatitudes while a warmer Arctic is related to more frequent severe winter weather. Severe conditions in cities with maritime climates—including parts of the western US, western Europe, and East Asia—have a weaker relationship with Arctic conditions.
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The relationship between PCHs and severe winter weather is strong and consistent throughout the atmospheric column. The relationship between PCTs and severe winter weather, however, is strong in the upper troposphere and lower stratosphere but weaker in the low- to mid-troposphere.
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Regional positive anomalies in 500 hPa temperatures over major Arctic peripheral seas are associated with positive values of rAWSSI (amplified severe winter weather) southeastward or downstream of the selected Arctic regions.
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Analysis of trends calculated for winter days from 1990/91 through 2022/23 reveal positive tendencies in tropospheric PCHs and low- to mid-tropospheric PCTs throughout the winter. In early winter trends in stratospheric PCHs, along with upper-tropospheric and lower-stratospheric PCTs, are mostly negative, while trends in rAWSSI are generally neutral or negative. In mid- to late winter when AAW extends through a deep layer of the atmosphere, upper-level trends in PCHs/PCTs become positive as do those in rAWSSI. This relationship suggests that severe winter weather has become more likely—especially in central US states, Scandinavia, eastern Europe, and Siberia—during mid-late winter as Arctic warming deepens and when the SPV has become disrupted more frequently.
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Our analysis of temporal changes in rAWSSI variability (five-day running means of daily standard deviation) indicates reduced variability since 2000 over much of Europe and the Arctic while large swaths of the continents exhibit increasing variability, especially across East Asia and the midlatitudes of North America. This finding suggests an increased tendency for volatile and often destructive shifts in severe winter conditions—known as weather whiplash—in regions with large populations and extensive agriculture.

In this study, we have applied various metrics to assess spatial patterns, variability, and temporal changes in severe winter weather conditions across NH continents, particularly as they may relate to variability in the Arctic atmosphere. Each of these metrics paints a similar picture of association between amplified Arctic tropospheric warming and higher geopotential heights—a clear and direct result of increased heat-trapping greenhouse gas concentrations—and a higher likelihood of severe winter weather in midlatitudes, especially across eastern North America, northern Europe, and northeast Asia. And while the relationship between Arctic geopotential heights and severe winter weather is consistent throughout the atmospheric column, the relationship between Arctic temperatures and severe winter weather strengthens with altitude. Even though cold records are being broken less often as the globe warms, our findings indicate that severe winter weather has increased regionally in the era of rapid Arctic warming. This consequence of a warming globe is likely to continue as greenhouse gas concentrations increase further, and it will be especially evident in eastern, northern, and high-elevation areas of the NH continents.

Due to the statistical nature of our study, we cannot demonstrate causality; numerical modeling sensitivity studies will be required. Previous modeling efforts have established causality between Arctic tropospheric warming, mostly due to sea-ice loss, and increased severe winter weather across the midlatitude continents 74, 75, 76 while other studies failed to demonstrate robust connections 9. In an effort to achieve a consensus, the Polar Amplification Modeling Intercomparison Project (PAMIP) was established 77. Early results confirm that sea-ice loss can force an atmospheric response consistent with a negative AO, a weaker stratospheric polar vortex, and an increase in severe winter weather across the midlatitudes, particularly in Asia, but the simulated response is less robust than in observational analyses 78. According to recent PAMIP studies, this discrepancy is likely due to the weaker AAW produced by considering forcing only by sea-ice loss rather than the full spectrum of warming influences 57.

Our present observational study along with further modeling experiments may help resolve the existing controversy between a) the majority of observational studies and a minority of modeling studies that support the link between Arctic warming and continental severe winter weather, and b) the majority of modeling studies that do not support the link or only simulate a muted relationship. More specifically, when simulated Arctic warming is shallow, the influence on midlatitude severe winter weather is weak, but when simulated Arctic warming is deep, the influence is substantially stronger 57, 58, 59, 60. Therefore the divergence in conclusions from these studies may be related to the depth of Arctic warming. While we were unable to address causality in this study, our results and other recent modeling studies 57, 58, 59, 60 add to the foundation for future work, including a further extension of indices of severe weather to model projections of future global warming.

Global-average warming may be imperceptible to individuals, but associated changes in extreme weather are already directly and dramatically affecting millions, if not billions, of people across the globe. Understanding connections between global change and extreme weather will better assist decision-makers in preparing for future impacts of climate change. The broader impacts and societal relevance of this research, therefore, are potentially substantial and beneficial.

Data and methods

In our earlier work, we developed two indicators of pan-Arctic atmospheric anomalies: the Polar Cap geopotential Height anomaly (PCH) index and the Polar Cap air Temperature anomaly (PCT) index (C18). The PCH and PCT indices measure the area-averaged geopotential height (m) and temperature (oC) anomalies poleward of 65°N and vertically from 1000 to 10 hPa. Both PCH and PCT are then normalized by their standard deviations, and thus are unitless. By definition, PCH values incorporate variations in air temperature and surface pressure, thus combining both thermodynamic and dynamic influences 79, while PCT reflects only thermodynamic effects.

An index of aggregate severe winter weather, the AWSSI, was developed by Mayes-Boustead et al. 73. The index is based on in-situ meteorological observations of anomalously heavy snowfall and low temperatures at individual stations across the US. It is reported as an accumulated daily value throughout the winter season (December, January, February) and informs comparisons of weather severity over time. The AWSSI is valuable because it integrates both intensity and duration of extremes in daily temperature, snowfall, and snow cover into one index to assess weather severity across seasons and locations. The index is incremented when daily thresholds of maximum and minimum temperature, snowfall, and snow depth are exceeded. For details of how the AWSSI is calculated please refer to the original formulation in Mayes-Boustead et al.

AWSSI are consistent among all stations or gridpoints and are not relative to a particular location’s climatology. Because AWSSI is not increased unless temperatures fall below freezing and unless snowfall or snow cover occurs, it is more indicative of winter weather variability in places that experience colder temperatures and/or heavy snowfall, such as areas farther north or at higher elevation.

To assess relationships between AWSSI and the PCH/PCT, C18 computed daily changes in the AWSSI at twelve selected cities across the US for all winter days (December, January, and February) from 1950 to 2016. The PCHs/PCTs were then composited by various thresholds from −3.0 to +3.0 standard deviations and the mean change in AWSSI at each station associated with the daily PCH/PCTs values at each isobaric level were summed and divided by the number of days to create composites at each station.

In the present study, we adapted this approach for use with reanalysis data, the rAWSSI, rather than data from meteorological stations, updated the analysis through winter 2022/2023, and expanded the coverage across the globe but limited our analysis to the NH for this study. The index was computed for all grid points in the ECMWF Reanalysis 5 (ERA5 50). The 2-meter air temperature, snowfall and snow depth fields from ERA5 were used to compute daily rAWSSI values at each grid point, then accumulated through each winter season (December, January, and February) from 1950 to 2023. The station-based observations used in the original AWSSI calculations were from the Midwestern Regional Climate Center, and values from reanalyses were matched to these locations using an inverse-distance weighted estimate from the ERA5 grid (Supplementary Fig. 2). The ERA5 gridded results show good agreement with the observed values, with weakest correlations in regions with routinely lower AWSSI/rAWSSI seasonal totals (e.g., Atlanta, Seattle in Supplementary Fig.

We note that in depicting the relationships in geographic plots (Figs. 1, 3, 6 and 10) we have masked the oceans below 60°N for clarity. In practice, the AWSSI is computed from surface observing stations, limiting coverage to land areas.

Data availability

ERA5 reanalysis obtained using Copernicus Climate Change Service at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-sing…. Original US station based AWSSI data are available at https://mrcc.purdue.edu/research/awssi. Gridded global rAWSSI data since 1950 are hosted at: https://published.aer.com/.

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Acknowledgements

JC and KP are supported by US National Science Foundation grant ARCSS-2115072. JF is supported by NSF grant ARCSS-2115068. We thank two anonymous reviewers for their constructive comments that materially improved the quality of the manuscript.

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Cohen, J., Francis, J.A. & Pfeiffer, K. Anomalous Arctic warming linked with severe winter weather in Northern Hemisphere continents. Commun Earth Environ 5, 557 (2024). https://doi.org/10.1038/s43247-024-01720-0

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DOI: https://doi.org/10.1038/s43247-024-01720-0

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