Revisiting the trend in the occurrences of the “warm Arctic–cold Eurasian continent” temperature pattern

Yu, Lejiang; Zhong, Shiyuan; Sui, Cuijuan; Sun, Bо

doi:10.5194/acp-20-13753-2020

Cited by 7 publications

(4 citation statements)

References 60 publications

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“…The interannual WACE pattern has often been explained by the planetary wave train induced by anomalous heating over Gulf Stream 30 or the Arctic sea ice loss 5 – 8 . Likewise, the CAWE or the negative WACE pattern has been explained by the stationary wave initiated over the North Atlantic 10 , 31 , 32 .…”

Section: Summary and Discussionmentioning

confidence: 99%

Subseasonal relationship between Arctic and Eurasian surface air temperature

Kim

Son

Moon

et al. 2021

Sci Rep

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The subseasonal relationship between Arctic and Eurasian surface air temperature (SAT) is re-examined using reanalysis data. Consistent with previous studies, a significant negative correlation is observed in cold season from November to February, but with a local minimum in late December. This relationship is dominated not only by the warm Arctic-cold Eurasia (WACE) pattern, which becomes more frequent during the last two decades, but also by the cold Arctic-warm Eurasia (CAWE) pattern. The budget analyses reveal that both WACE and CAWE patterns are primarily driven by the temperature advection associated with sea level pressure anomaly over the Ural region, partly cancelled by the diabatic heating. It is further found that, although the anticyclonic anomaly of WACE pattern mostly represents the Ural blocking, about 20% of WACE cases are associated with non-blocking high pressure systems. This result indicates that the Ural blocking is not a necessary condition for the WACE pattern, highlighting the importance of transient weather systems in the subseasonal Arctic-Eurasian SAT co-variability.

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Section: Summary and Discussionmentioning

confidence: 99%

Subseasonal relationship between Arctic and Eurasian surface air temperature

Kim

Son

Moon

et al. 2021

Sci Rep

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“…Several studies have demonstrated an increasing occurrence of the so-called warm Arcticcold continents pattern in winter (Overland et al, 2011). Whether the pattern is due to sea ice loss and amplified warming in the Arctic (Cohen et al, 2013;Overland et al, 2021), SST-driven teleconnections from the North Pacific and North Atlantic (Yu et al, 2020), or inherent variability of the climate system (Blackport and Screen, 2020), in any case the pattern has partly compensated for the greenhouse warming over northern continental mid-latitudes in winter. Comparing the two halves of our study period, the November-March warming at the 850 hPa level (based on ERA5) has two prominent spatial patterns: (1) the Arctic has warmed faster than Europe, and (2) eastern Europe has warmed faster than western Europe.…”

Section: Discussionmentioning

confidence: 99%

Cold wintertime air masses over Europe: Where do they come from and how do they form?

Nygård

Papritz

Naakka

et al. 2023

Preprint

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Abstract. Despite the general warming trend, wintertime cold air outbreaks in Europe have remained nearly as extreme and as common as decades ago. In this study, we identify six principal 850 hPa cold anomaly types over Europe in 1979–2020 using self-organizing maps (SOMs). Based on extensive analysis of atmospheric large-scale circulation patterns combined with nearly two million kinematic backward trajectories, we show the origins and contributions of various physical processes to the formation of cold wintertime 850-hPa air masses. The location of the cold anomaly region is closely tied to the location of blocking; if the block is located farther in the east, also the cold anomaly is displaced eastwards. Considering air-mass evolution along the trajectories, the air parcels are typically initially (5–10 d before) colder than at their arrival in Europe, but also initially warmer air parcels sometimes lead to cold anomalies over Europe. Most commonly the effect of adiabatic warming on the temperature anomalies is overcompensated by advection from regions that are climatologically colder than the target region, supported by diabatic cooling along the pathway. However, there are regional differences: cold anomalies over western Europe and southeastern Europe are dominantly caused by advection, and over eastern Europe by both advective and diabatic processes. The decadal-scale warming in the site of air mass origin has been partly compensated by enhanced diabatic (radiative) cooling along the pathway to Europe. There have also been decadal changes in large-scale circulation patterns and air mass origin. Our results suggest that understanding future changes in cold extremes will require in-depth analyses on both large-scale circulation and the physical (adiabatic and diabatic) processes.

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“…The SOM has been increasingly used to distinguish the weather patterns of atmospheric circulation (Johnson, 2013; Bao and Wallace, 2015; Yu et al ., 2020; Yu et al ., 2021). In this study, the SOM training and analysis are based on daily spatial anomalies of T2M during early winter (defined as Dec 1–Jan 31) of the years 1979–2021.…”

Section: Methodsmentioning

confidence: 99%

Has substantial sea ice loss along the Siberian coast contributed to the 2020/2021 winter cold wave in China?

Wang

Liu

Cheng

et al. 2022

Intl Journal of Climatology

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In winter 2020/2021, several episodes of cold air outbreaks have wreaked havoc across much of China, resulting in exceptionally low temperatures over northern-to-southeastern China. Our analysis shows that the anomalous circulation leading to the cold wave in China was characterized as: (a) a strengthening of the Siberian high, (b) a deepening of the East Asian trough, and (c) a weakening of the stratospheric polar vortex. Prior to the winter, in summer and autumn, the largest sea ice loss along the Siberian coast was observed. We therefore address the question whether the substantial sea ice loss has contributed to the cold wave. First, applying singular value decomposition (SVD) analysis, we find strong coherence between the autumn Arctic sea ice coverage and temperatures over the central-to-east Asian region with the sea ice component (SVD1_SIC) reaching a record high in 2020 and displaying a decadal shift around 2005. Associated with both the interannual and decadal variations of the SVD1_SIC, there are similar circulation anomalies as described in (a), (b) and (c) above. Second, applying self-organizing maps, wintertime daily air temperatures are clustered into nine nodes with Node-1 mostly resembling "warm Arctic, cold Eurasia" pattern. The frequency of Node-1 shows a similar decadal shift as observed in SVD_SIC1 above, with a correlation of about 0.56. Associated with Node-1, the circulation anomalies are consistent with features highlighted in (a), (b) and (c) above. Thus, taking all the evidence into account, we conclude that the substantial sea ice loss along the Siberian coast contributed significantly to the 2020/2021 winter cold wave in China. The mechanism behind the contribution in this study highlights that the Arctic sea ice loss is favourable for certain circulation patterns on climate timescale, reinforcing disruptive chain of reactions on weather timescale, and leading to severe cold events.

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Revisiting the trend in the occurrences of the “warm Arctic–cold Eurasian continent” temperature pattern

Cited by 7 publications

References 60 publications

Subseasonal relationship between Arctic and Eurasian surface air temperature

Subseasonal relationship between Arctic and Eurasian surface air temperature

Cold wintertime air masses over Europe: Where do they come from and how do they form?

Has substantial sea ice loss along the Siberian coast contributed to the 2020/2021 winter cold wave in China?

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