Eurasian Pattern Research Articles

Warm Arctic-Cold Eurasia pattern helps predict spring wildfire burned area in West Siberia.

Extreme wildfires have devastating impacts on multiple fronts, and associated carbon greatly heats the earth's climate. Whether and how to predict wildfires becomes a critical question. In this study, we find that the preceding-winter "warm Arctic-cold Eurasia" (WACE) pattern significantly enlarges the spring burned area in West Siberia. The winter WACE and accompanying snow reduction result in dryness and vegetationexposure in West Siberia in spring, increasing fire risks. A multiple linear regression model is constructed that successfully predicts the spring burned area in West Siberia one season in advance (R-squared coefficient=0.64). The same predictors also well predict the corresponding fire carbon emissions. Independent predictions for spring burned area in 2019 and 2020 are very close to observations, with a mean absolute percentage error of only 3.0%. The findings of this study provide a possibility for guarding humans against extreme wildfires and predicting sharp rises in carbon emissions.

Asymmetric impact of ENSO on the late winter Warm Arctic-Cold Eurasian pattern

Asymmetric impact of ENSO on the late winter Warm Arctic-Cold Eurasian pattern

Different responses of surface air temperature over Eurasia in early and late winter to the autumn Kara–Laptev Sea ice

The Arctic climate is changing rapidly, along with intensified melting of sea ice, which has significant impacts on surface air temperature (SAT) in Eurasia. This study reveals that the subseasonal response of SAT to the autumn Kara–Laptev Sea ice (KLSIC) differs significantly between early and late winter. The response of SAT to KLSIC forms a warm Arctic–cold Eurasia pattern in early winter. Conversely, the negative anomaly response of SAT to KLSIC in late winter is only distributed in the band range of Eurasia, without significant positive SAT anomaly over the Arctic Ocean. After further examination of the separate physical mechanisms involved in early and late winter, it is found that a decrease in KLSIC in autumn can lead to a strengthened Ural high and Siberian high in the Arctic–Eurasia region, which is conducive to cold events in the mid-latitudes of Eurasia in early winter. For late winter, a westward shift in the response of atmospheric circulation to KLSIC leads to a negative anomaly feedback of North Sea surface temperature, which triggers the propagation of Rossby waves to the Sea of Japan through the wave activity flux. Meanwhile, the deep trough of East Asia is strengthened and extends to the southeast, guiding northern cold air to the western Pacific. Our results highlight that different subseasonal effects of sea ice should be considered in Eurasian climate prediction, rather than only consider the effects in winter mean.

Modulation of the impact of winter-mean warm Arctic-cold Eurasia pattern on Eurasian cold extremes by the subseasonal variability

Utilizing ERA5 data, this study provides evidence that both the winter-mean state and subseasonal variability (SSV) of the warm Arctic-cold Eurasia (WACE) pattern significantly influence the frequency of cold extremes in Eurasia. The positive phase of winter-mean WACE (WACEMean) or a stronger SSV of WACE (WACESSV) corresponds to a higher occurrence of cold extremes over central Eurasia and East Asia. Furthermore, the study reveals that the impact of WACEMean on the cold extremes is modulated by WACESSV. During years characterized by a positive WACEMean and enhanced WACESSV, the associated winter-mean anticyclonic anomalies, combined with amplified subseasonal circulation fluctuations over the northern Eurasia continent, contribute to a significant increase in the blocking frequency over the Ural–Siberia region. This, in turn, contributes to an intensified occurrence of cold extremes in central Eurasia and East Asia. In contrast, during the years with a positive WACEMean but reduced WACESSV, in the absence of significant changes in the subseasonal circulation fluctuations, the winter-mean anticyclonic anomalies over the northern Eurasia continent do not exert a significant impact on Ural–Siberian blocking frequency by themselves. Consequently, there are no notable anomalies in the frequency of cold extremes over central Eurasia and East Asia. Finally, this study reveals that the differences in the distribution of the frequency anomalies in the blocking between the two sets of years are attributed to the constructive and destructive superposition of anomalies in subseasonal circulation fluctuations related to the WACEMean and WACESSV.

Warm Arctic–Cold Eurasia pattern driven by atmospheric blocking in models and observations

In recent decades, Arctic-amplified warming and sea-ice loss coincided with a prolonged wintertime Eurasian cooling trend. This observed Warm Arctic–Cold Eurasia pattern has occasionally been attributed to sea-ice forced changes in the midlatitude atmospheric circulation, implying an anthropogenic cause. However, comprehensive climate change simulations do not produce Eurasian cooling, instead suggesting a role for unforced atmospheric variability. This study seeks to clarify the source of this model-observation discrepancy by developing a statistical approach that enables direct comparison of Arctic-midlatitude interactions. In both historical simulations and observations, we first identify Ural blocking as the primary causal driver of sea ice, temperature, and circulation anomalies consistent with the Warm Arctic–Cold Eurasia pattern. Next, we quantify distinct transient responses to this Ural blocking, which explain the model-observation discrepancy in historical Eurasian temperature. Observed 1988–2012 Eurasian cooling occurs in response to a pronounced positive trend in Ural sea-level pressure, temporarily masking long-term midlatitude warming. This observed sea-level pressure trend lies at the outer edge of simulated variability in a fully coupled large ensemble, where smaller sea-level pressure trends have little impact on the ensemble mean temperature trend over Eurasia. Accounting for these differences bring observed and simulated trends into remarkable agreement. Finally, we quantify the influence of sea-ice loss on the magnitude of the observed Ural sea-level pressure trend, an effect that is absent in historical simulations. These results illustrate that sea-ice loss and tropospheric variability can both play a role in producing Eurasian cooling. Furthermore, by conducting a direct model-observation comparison, we reveal a key difference in the causal structures characterizing the Warm Arctic–Cold Eurasia Pattern, which will guide ongoing efforts to explain the lack of Eurasian cooling in climate change simulations.

Identification of Shortcomings in Simulating the Subseasonal Reversal of the Warm Arctic–Cold Eurasia Pattern

AbstractSubseasonal reversal of warm Arctic–cold Eurasia (SR‐WACE) pattern has significant impacts on transitions of weather and climate extremes in Eurasia. This study explored the performances of climate models to simulate the main features of SR‐WACE. For real‐time predictions, most of the state‐of‐the‐art climate models showed limited ability to accurately forecast SR‐WACE in advance. Furthermore, most of the historical simulations from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) had also difficulties in well simulating the SR‐WACE. Further exploration showed that the simultaneous reversal of the Ural blocking high (UB) and Siberian high (SH) is the key atmospheric driver of the SR‐WACE occurrences, which were verified by both of the real‐time predictions and historical simulations. Our results implied that the simulation of SR‐WACE was a huge challenge and the critical solutions included improving simulation of subseasonal reversals of UB and SH in the atmosphere.

Observed winter Barents Kara Sea ice variations induce prominent sub-decadal variability and a multi-decadal trend in the Warm Arctic Cold Eurasia pattern

The observed winter Barents-Kara Sea (BKS) sea ice concentration (SIC) has shown a close association with the second empirical orthogonal function (EOF) mode of Eurasian winter surface air temperature (SAT) variability, known as Warm Arctic Cold Eurasia (WACE) pattern. However, the potential role of BKS SIC on this WACE pattern of variability and on its long-term trend remains elusive. Here, we show that from 1979 to 2022, the winter BKS SIC and WACE association is most prominent and statistically significant for the variability at the sub-decadal time scale for 5–6 years. We also show the critical role of the multi-decadal trend in the principal component of the WACE mode of variability for explaining the overall Eurasian winter temperature trend over the same period. Furthermore, a large multi-model ensemble of atmosphere-only experiments from 1979 to 2014, with and without the observed Arctic SIC forcing, suggests that the BKS SIC variations induce this observed sub-decadal variability and the multi-decadal trend in the WACE. Additionally, we analyse the model simulated first or the leading EOF mode of Eurasian winter SAT variability, which in observations, closely relates to the Arctic Oscillation (AO). We find a weaker association of this mode to AO and a statistically significant positive trend in our ensemble simulation, opposite to that found in observation. This contrasting nature reflects excessive hemispheric warming in the models, partly contributed by the modelled Arctic Sea ice loss.

The Siberian Storm Track Weakens the Warm Arctic–Cold Eurasia Pattern

Abstract With a particular focus on the Siberian storm track, this study provides new insights into variations in the warm Arctic–cold Eurasia (WACE) temperature anomaly pattern by using reanalysis data. The results show that the Siberian storm track has a significant out-of-phase relationship with both the WACE pattern and Ural blocking on the interannual time scale. The strengthened WACE pattern can weaken the Siberian storm track through a suppression of the low-level atmospheric baroclinicity over midlatitude Eurasia. The weakened Siberian storm track can contribute to the WACE pattern through feedback forcing from synoptic-scale eddies, which can also create favorable conditions for the development of Ural blocking. Composite temporal evolution reveals that the strongest cold Arctic–warm Eurasia pattern is preceded by the peak of the Siberian storm track. The Ural cyclonic circulation reaches its maximum amplitude on the peak day of the Siberian storm track strength and continues to persist for one day with the maximum amplitude due to the feedback forcing resulting from the Siberian storm track. On the intraseasonal time scale, the occurrence of the Siberian storm track activity can serve as an early indication of the diminished Ural blocking and WACE pattern. Significance Statement Because of the high impacts of the warm Arctic–cold Eurasia (WACE) pattern on public safety, socioeconomic development, and the economy, it is crucial to enhance our understanding of variations in the WACE pattern. This paper specifically investigates the impact of internal atmospheric variability on the WACE pattern, focusing on a pronounced negative correlation between the Siberian storm track and the WACE pattern. Daily composites also reveal that Siberian storm track activities can promote a strong cold Arctic–warm Eurasia pattern by maintaining the strength of the quasi-stationary Ural cyclonic circulation. As such, paying close attention to Siberian storm track activities may hold the promise to improve the prediction of the strength of the WACE pattern.

Different influences of La Niña types on the winter sub-seasonal Eurasian cold anomalies linked to Ural blocking

The effects of different types of La Niña on winter sub-seasonal cold anomalies or cold extremes over Eurasia and Siberia are examined through exploring changes in Ural blocking (UB). It is found that the Central Pacific (CP) La Niña can significantly influence surface air temperature over Eurasia mainly by regulating the movement, persistence, zonal scale and location of the cyclonic anomaly associated with the UB. This influence is much greater than that resulting from an Eastern Pacific (EP) La Niña. A long-lived and quasi-stationary cyclonic anomaly with a large zonal scale of UB is induced to the southeast of the Ural Mountains for CP-type La Niña conditions, which leads to a strong warm Arctic-cold Eurasia pattern with an intense sub-seasonal cold anomaly or cold event in the broad region of Eurasia due to strongly reduced downward infrared radiation over Eurasia. In contrast, for EP-type La Niña winter the cyclonic anomaly, while still present, is much weaker, short-lived and eastward propagating, resulting in only a very weak cold anomaly or cold event over a small region of Eurasia. The reduced (enhanced) eastward movement and increased (decreased) persistence of the cyclonic anomaly with large (small) zonal scale of UB are shown to be associated with reduced (enhanced) meridional potential vorticity gradient in the midlatitudes (30o-50oN) to the east of 60°E during the CP-type (EP-type) La Niña winter.

The Leading Modes of Northern Eurasian Winter Snowfall Variability and the Potential Influencing Factors

Abstract This study investigates the dominant modes of the interannual variability of the northern Eurasian winter snowfall during 1982–2020 and explores their potential influencing factors and the associated physical processes. The first and second empirical orthogonal function (EOF) modes feature coherent snowfall anomalies over the high latitudes of Eurasia and western Siberia, respectively. Further analyses indicate that the anomalous atmospheric circulations play a major role in forming the snowfall variability, which could be further attributed to the influences of the atmospheric teleconnection patterns and Arctic sea ice variations. Specifically, the anomalous circulations related to the first EOF mode are mainly contributed by the effects of the teleconnections of the Polar–Eurasian and Scandinavian patterns. The formation of the second EOF mode has a close connection with the North Atlantic Oscillation and the Eurasian pattern. In addition, the sea ice variations over Baffin Bay exert a considerable influence on the snowfall anomalies related to the second EOF mode by exciting a wave train–like anomalous circulation. This effect is further verified by a numerical simulation. An empirical statistical model based on the above influencing factors can well explain the temporal evolutions of the two dominant modes, verifying the important value of our results to improve the understanding of interannual variability of northern Eurasian winter snowfall.

Dynamics of Spring Snow Cover Variability over Northeast China

Spring snow cover variability over Northeast China (NEC) has a profound influence on the local grain yield and even the food security of the country, but its drivers remain unclear. In the present study, we investigated the spatiotemporal features and the underlying mechanisms of spring snow cover variability over NEC during 1983–2018 based on the satellite-derived snow cover data and atmospheric reanalysis products. The empirical orthogonal function (EOF) analysis showed that the first EOF mode (EOF1) explains about 50% of the total variances and characterizes a coherent snow cover variability pattern over NEC. Further analyses suggested that the formation of the EOF1 mode is jointly affected by the atmospheric internal variability and the sea surface temperature (SST) anomaly at the interannual timescale. Specifically, following a negative phase of the atmospheric teleconnection of the Polar–Eurasian pattern, a prominent cyclonic circulation appears over NEC, which increases the snowfall over the east of NEC by enhancing the water vapor transport and decreases the air temperature through reducing the solar radiation and intensifying the cold advection. As a result, the snow cover has increased over NEC. Additionally, the tripole structure of the North Atlantic spring SST anomaly could excite a wave-train-type anomalous circulation propagating to NEC that further regulates the snow cover variability by altering the atmospheric dynamic and thermodynamic conditions and the resultant air temperature and snowfall. Our results have important implications on the understanding of the spring snow cover anomaly over NEC and the formulation of the local agricultural production plan.

Interannual variation of the Warm Arctic–Cold Eurasia pattern modulated by Ural blocking and the North Atlantic Oscillation under changing sea ice conditions

Together with rapid Arctic warming and sea ice decline, especially over the Barents–Kara seas (BKS), extreme cold winters have occurred frequently in mid-latitudes, particularly in Central Eurasia. A pattern with two distinct winter temperature anomalies centered over the BKS and Central Eurasia is known as the Warm Arctic–Cold Eurasia (WACE) pattern. The impacts of sea ice loss over the BKS and internal atmospheric variability on past WACE formation remain under discussion mainly due to the large internal atmospheric variability in the mid-latitudes. This study analyzed a large-ensemble historical experiment prescribing observed sea ice condition to investigate the role of internal atmospheric variability in the observed interannual variation of the WACE pattern. Comparison of ensemble members suggests that internal atmospheric variability is important for regulating the magnitude of the WACE pattern. Besides the strong effect of local sea ice loss, winter temperature over the BKS increases due to warm advection driven by the Ural blocking and positive phase of the North Atlantic Oscillation. A decrease in winter temperature over Central Eurasia is mainly attributable to the cold advection enhanced by Ural blocking rather than the remote effect of sea ice decline over the BKS. Our study reveals the importance of internal atmospheric variability in elucidating the observed interannual variation of the WACE pattern.

The warm Arctic-cold north american pattern in CanESM5 large ensemble simulations: Eurasian influence and uncertainty due to internal variability

This study examines the warm Arctic-cold North American pattern (WACNA) and its connection with the warm Arctic-cold Eurasia pattern (WACE) using ERA5 reanalysis and a 50-member ensemble of historical climate simulations produced by CanESM5, the Canadian model participated in CMIP6. The results indicate that a negative WACE-like pattern typically precedes a positive WACNA pattern by one month, and the presence of a negative Asian-Bering-North American (ABNA)-like circulation pattern connects Eurasia and North America, along with the Pacific-North American (PNA)-like pattern. The negative ABNA-like pattern can be attributed to anomalous heating in southern Siberia, which is associated with the negative WACE pattern and its featured Eurasian warming. The negative PNA-like pattern is influenced by negative SST anomalies in the tropical Pacific, resembling tropical ENSO variability. Anomalous temperature advection in the lower troposphere follows the circulation anomaly, which supports the formation of WACNA. Conversely, processes with circulation anomalies of opposite sign result in a negative WACNA pattern. The tropical ENSO variability does not significantly impact the WACNA pattern and its linkage with WACE. CanESM5 simulates the WACNA pattern and WACE-WACNA connection well, with some discrepancies in the magnitude of anomalies compared to ERA5 reanalysis. The uncertainty in the simulated WACNA pattern due to internal climate variability is dominated by two modes of inter-member variability: a southeast-northwest phase shift and a local variation in amplitude.

Intensification of Arabian Sea cyclone genesis potential and its association with Warm Arctic Cold Eurasia pattern

The present study examines the drivers of the observed increasing trend in the Genesis Potential Index (GPI) of the post-monsoon season (October-November-December) tropical cyclones in the Arabian Sea (AS) during the period, 1998–2021. The increase in atmospheric moisture loading, ocean heat content in the upper 300 m (OHC300) and reduction in vertical wind shear are the major factors which caused the intensification in cyclone GPI in the recent decades. The increase in atmospheric moisture loading and OHC300 are consistent with the overall observed ocean warming trend of the region. However, the reduction in vertical wind shear has resulted from an anomalous large-scale upper atmospheric anticyclonic circulation over central India. Further investigation shows a concurrent transition of the Warm Arctic Cold Eurasia (WACE) pattern to its positive phase which strengthened and shifted the Subtropical Jet (STJ) poleward. This resulted in the anticyclonic circulation anomaly and altered the upper tropospheric zonal winds over the AS cyclone genesis region, weakening the vertical wind shear. The study demonstrates a possible physical mechanism through which remote forcing due to changes in the northern high-latitude climate can influence the AS cyclone genesis.

Decadal Changes in the Linkage Between Autumn Sea Ice and the Winter Eurasian Temperature in the 20th Century

AbstractThe Warm Arctic‐Cold Eurasia pattern in recent decades has attracted extensive attention and has been partly attributed to rapid sea‐ice loss; however, such a link has been unstable over the past century. Here, we use centennial reanalyzes to investigate the multi‐decadal changes in the linkage between autumn Barents‐Kara sea‐ice and winter Eurasian temperature during the 20th century. Results show a negative Arctic‐Eurasian connection in 1901–1945 (P1), an inconspicuous connection in 1946–1985 (P2), and a significantly positive correlation in 1986–2013 (P3), with distinct stratospheric and tropospheric pathways mechanisms. The contrasting relationships between P1 and P3 are likely due to the different magnitudes of sea‐ice loss and the predominant roles of the atmosphere or sea‐ice in driving different Eurasian temperature effects. As further verification, the best group of Coupled Model Intercomparison Project simulations, which captured the realistic stratospheric pathway in recent decades, can reproduce the historical decadal changes in the Arctic‐Eurasian linkage.

Subseasonal transition of Barents–Kara sea-ice anomalies in winter related to the reversed warm Arctic–cold Eurasia pattern

Subseasonal reversal of the warm Arctic–cold Eurasia pattern (WACE) could trigger an extreme cold/warm transition in winter and sandstorms in spring over eastern China. An associated subseasonal transition of the sea-ice anomaly also occurs in the Barents–Kara seas (BKS) driven by such remarkable high-latitude atmospheric pattern reversals. Under a warm Arctic and enhanced Ural high, abnormal downward turbulent heat flux and increased downward infrared radiation in the BKS are conducive to sea ice melting. The surface southerly wind drives the sea ice to drift from the thin to perennial ice area and further enlarges the open ocean surface. The opposite mechanism occurs in the opposite phase of WACE, causing positive BKS sea-ice anomalies. When WACE reverses on the subseasonal scale, the above mechanisms occur in early and late winter, respectively, resulting in a significant subseasonal transition of BKS sea-ice anomalies. More importantly, in the last decade, with a more frequent reversal of WACE, the subseasonal transition between early winter and late winter in BKS sea ice has enhanced. The findings of this study establish a comprehensive schematic of the subseasonal reversal of WACE and contribute to better understanding and predicting extreme climate in eastern China.

The Warm Arctic—Cold Eurasia Pattern and Its Key Region in Winter in CMIP6 Model Simulations

The Warm Arctic—Cold Eurasia Pattern and Its Key Region in Winter in CMIP6 Model Simulations

The Role of Mid‐latitude Westerly Jet in the Impacts of November Ural Blocking on Early‐Winter Warmer Arctic‐Colder Eurasia Pattern

AbstractBased on statistical analysis using observations and idealized model simulations, previous studies have revealed the potential response of early‐winter atmospheric circulation and temperature anomalies to November Ural blocking (UB) anomalies. Using a large number of coupled simulations, this study found that the response is sensitive to the intensity of November mid‐latitude westerly jet over Eurasia. Stronger‐than‐normal November UB without a significantly weakened westerly jet could not cause significant atmospheric response in early‐winter. By contrast, stronger‐than‐normal November UB with a significantly weakened jet would be followed by a warmer Arctic‐colder Eurasia (WACE) pattern in December. The significantly weakened westerly jet favors stronger upward propagation of planetary waves, which causes stronger weakening and longer persistence of the stratospheric polar vortex. This stratospheric response persists into December and propagates downward into the troposphere interfering with planetary waves (especially wavenumber‐1). The lead‐lag UB‐WACE linkage modulated by mid‐latitude jet may have implications for sub‐seasonal predictability.

Contribution of Ural and Kamchatka Blockings to the Amplified Warm Arctic–Cold Eurasia Pattern under Arctic Sea Ice Loss and Eurasian Cooling

Abstract Previous studies have shown that sea ice loss over the Barents–Kara Seas (BKS) in early winter intensifies surface warming and favors more frequent Ural blocking (UB). Using three different blocking detection methods based on reanalysis and model simulation, we find that the increased occurrences of UB and Kamchatka blocking (KB) over Eurasia are concurrent with both the sea ice loss over the BKS and Eurasian cooling, emphasizing the synergic conditions of sea ice and atmospheric internal variability in facilitating the frequent blocking events. Under the sea ice loss and Eurasian cooling conditions, the KB manifests the strongest surface cold anomaly over northern Eurasia. In contrast, the UB shows either a robust or slightly stronger cold anomaly over Eurasia depending on the conditions above. Consequently, the surface impacts of two regional blockings given the combined conditions of BKS sea ice loss and Eurasian cooling contribute the most to the amplified dipole pattern of Eurasian surface air temperature (SAT). The enhanced dipole pattern shows distinct similarities to the warm Arctic and cold Eurasia (WACE) pattern, previously defined as the second principal mode of winter SAT variability over Eurasia. This implies the role of sea ice loss in reinforcing the internal variability of Eurasian SAT via multiple blocking activities, triggering cold extremes toward Eurasia. Climate simulations with Community Atmosphere Model version 5 (CAM5) can reproduce the observed linkage among sea ice, blocking, and the WACE pattern.

Distinct Mid-Latitude Eurasian Rossby Wave Trains Preceding Strong and Weak Cold Surges in Southern China

This study investigates the large-scale circulation anomalies of strong and weak cold surges in southern China. Results show that the strong and weak surges are associated with a distinct Rossby wave train across Eurasia projecting onto the Scandinavia (SCAND) and Eurasian (EU) patterns. On one hand, the strong surge is preceded by a positive SCAND pattern and a transition of the EU pattern from its negative to positive phase. The corresponding wave train propagates southeastward from East Asia to the North Pacific. This is associated with a strong intensification of the Siberian high, a deepened East Asian trough, and a sharp meridional pressure gradient between northern and southern China; these advect intense cold air masses from Siberia to southern China. On the other hand, the weak surge is preceded by a negative SCAND pattern and a positive EU pattern. The corresponding wave train does not propagate from East Asia to the North Pacific. This wave train has a weak impact on the East Asian winter monsoon circulation and corresponds to weak cold air advections towards southern China. Overall, the intra-seasonal variation of the Eurasian teleconnection patterns is crucial for a comprehensive understanding of the cold surge in southern China.