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As one of the most significant circulation systems over the Northern Hemisphere in the cold season, the East Asian winter monsoon (EAWM) has been broadly investigated from the seasonal-mean perspective, while subseasonal variations in the EAWM still remain ambiguous. Based on Season-reliant Empirical Orthogonal Function (S-EOF) analysis, this study shows that the subseasonal strength reversal of the EAWM (SR-EAWM), featuring a weaker (or stronger) EAWM in early winter (December) and a stronger (or weaker) EAWM in late winter (January–February), is a distinct leading mode of the month-to-month variation of the EAWM. The weak-to-strong SR-EAWM is characterized by an anomalous low over Eurasia and a weakened East Asian major trough (EAT) in early winter, with an intensified Siberian High and a deepened EAT in late winter. The SR-EAWM is preceded by surface air temperature anomalies over Davis Strait (DST) and those over central-eastern North America (CENAT) in September–October. The DST mainly influences the SR-EAWM in early winter through a "sea ice bridge" of the November Baffin Bay sea ice concentration anomaly (BBSIC). The BBSIC could intensify the DST in December by altering surface heat flux, thus exciting a downstream atmospheric response and modulating the strength of the EAT in early winter. The CENAT affects the SR-EAWM in late winter by inducing an "ocean bridge" of the western North Atlantic sea surface temperature anomaly (WNASST). The WNASST can persist into late winter and then significantly affects the SR-EAWM by regulating Eurasian circulation anomalies and the downstream EAT. The bridge roles of the BBSIC and WNASST can be further verified by a linear baroclinic model. Finally, two physical-empirical models are established using the DST/BBSIC and the CENAT indices, respectively. Both exhibit promising prediction skills. The results highlight that the DST, BBSIC, and CENAT are crucial predictability sources for the SR-EAWM. [ABSTRACT FROM AUTHOR]

This study reveals a marked enhancement in the relationship between the variations in location of the winter East Asian Polar Front Jet (EAPJ) and the surface air temperature (SAT) in Eurasia since the mid-1990s. Before the mid-1990s, an evident wave train related to the meridional location of the EAPJ exhibited an anticyclonic anomaly over northern Europe and a cyclonic anomaly in northwestern Asia. With an equatorward shift of the EAPJ after the mid-1990s, the wave train experiences a notable adjustment that is conducive to East Asian cooling, displaying an anticyclonic anomaly around the Kara-Laptev Seas and a cyclonic anomaly near northeastern Asia. Arctic warming anomalies and sea ice loss contributed significantly to these decadal changes. Simulation experiments forced by observed Arctic sea-ice variability further confirm this result. Since the mid-1990s, Arctic sea ice loss (or Arctic warming anomaly) has contributed to a reduction in westerly winds in high latitudes by modulating the meridional temperature gradient. The deaccelerated winds intensify the Arctic cold air propagating to the south, enhancing the atmospheric baroclinicity and the westerly flow in the upper level at the south side of the EAPJ, favoring the southward shift of the EAPJ. With the equatorward shift of the EAPJ, the corresponding SAT anomalies in East Asia are more salient. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Despite rapid global warming, Eurasia experienced unusual winter cooling from around 1992–2012, whose cause is still debated. By analyzing observations and model simulations, we show that the winter cooling from 1992 to 2012, as well as the enhanced winter warming from 1971–1991, over Eurasia partly resulted from internally-generated multidecadal variations related to variations in sea ice cover (SIC) and surface air temperature (Tas) over the Barents-Kara Seas (BKS). The BKS SIC and Tas variations concur with a multidecadal trend towards an anticyclonic (cyclonic) anomaly circulation over the Ural Mountains during 1992–2012 (1971–1991) that advected cold (warm) air from the Arctic (southwest Eurasia) into central Asia, contributing to the cooling (warming) over most Eurasia during 1992–2012 (1971–1991). These multidecadal variations in BKS SIC and Tas largely disappear, and the associated anomaly circulation and its influence on central Eurasia (CE) weaken when sea ice-air interactions are absent, although reduced multidecadal cooling over CE still exists in simulations without Arctic sea ice-air coupling. Because of the 10–20 day lifetime of Ural blocking, daily Arctic sea ice-air interactions, which are absent in all simulations with prescribed sea ice, are crucial for models to realistically simulate Ural blocking events and their decadal frequency and other changes that connect the BKS and CE Tas anomalies. BKS multidecadal warming is insufficient to induce CE cooling when Arctic sea ice-air interactions are turned off in our simulations. In contrast to the multidecadal BKS sea-ice decline, global-warming induced long-term sea-ice loss does not cause cooling over CE, likely due to other associated changes. As sea ice continues to melt away, its ability to cause such multidecadal variations and cooling over Eurasia will diminish. [ABSTRACT FROM AUTHOR]

Key processes associated with the leading intraseasonal variability mode of wintertime surface air temperature (SAT) over Eurasia and the Arctic region are investigated in this study. Characterized by a dipole distribution in SAT anomalies centered over north Eurasia and the Arctic, respectively, and coherent temperature anomalies vertically extending from the surface to 300 hPa, this leading intraseasonal SAT mode and associated circulation have pronounced influences on global surface temperature anomalies including the East Asian winter monsoon region. By taking advantage of realistic simulations of the intraseasonal SAT mode in a global climate model, it is illustrated that temperature anomalies in the troposphere associated with the leading SAT mode are mainly due to dynamic processes, especially via the horizontal advection of winter mean temperature by intraseasonal circulation. While the cloud–radiative feedback is not critical in sustaining the temperature variability in the troposphere, it is found to play a crucial role in coupling temperature anomalies at the surface and in the free atmosphere through anomalous surface downward longwave radiation. The variability in clouds associated with the intraseasonal SAT mode is closely linked to moisture anomalies generated by similar advective processes as for temperature anomalies. Model experiments suggest that this leading intraseasonal SAT mode can be sustained by internal atmospheric processes in the troposphere over the mid- to high latitudes by excluding forcings from Arctic sea ice variability, tropical convective variability, and the stratospheric processes. [ABSTRACT FROM AUTHOR]

An unprecedented cold event occurred in Central and eastern Eurasia during the 2020/21 winter, including five episodes of consecutive cold spells (EP1–5). Through analysis of both observational and simulations, we show that the concurrent Arctic sea-ice loss and extratropical Pacific decadal oscillation (EPDO) warming are potential drivers for the cold event. Their relative contributions to the intraseasonal evolutions of atmospheric circulation and concomitant cold surges are thoroughly investigated. The circulation anomalies highlight the gradual development of the negative Arctic oscillation, accompanied by strengthened Siberian high and deepened Aleutian low. Stratospheric pathways were integrally involved in the dynamical response and the timing of episodes. Our results suggest that the sea-ice, irrespective of seasonality, and autumn EPDO experiments can generally capture the spatial patterns of atmospheric circulation and temperature in observation, albeit weaker in magnitude. Autumn (winter) sea-ice loss led to the EP1–3 (EP2–3) cold spells, and autumn EPDO led to the EP1–3 cold surges; whereas the EP4–5 cold spells induced by autumn SIC and PDO were not statistically robust. The Eurasian cooling response to winter PDO is weak due to the extensive warming over southern China and Eurasian highlatitudes that offsets the midlatitude cooling. The largest coolings were found in SIC and EPDO combined experiments, suggesting their synergic importance in driving such cold events. Our results have implications for the potential predictability of winter extreme events over Eurasia in the context of ongoing sea-ice decline and a recent shift to the positive PDO phase. [ABSTRACT FROM AUTHOR]

Based on 36-yr hindcasts from the fifth-generation seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (SEAS5), the most predictable patterns of the wintertime 2-m air temperature (T2m) in the extratropical Northern Hemisphere are extracted via the maximum signal-to-noise (MSN) empirical orthogonal function (EOF) analysis, and their associated predictability sources are identified. The MSN EOF1 captures the warming trend that amplifies over the Arctic but misses the associated warm Arctic–cold continent pattern. The MSN EOF2 delineates a wavelike T2m pattern over the Pacific–North America region, which is rooted in the tropical forcing of the eastern Pacific-type El Niño–Southern Oscillation (ENSO). The MSN EOF3 shows a wavelike T2m pattern over the Pacific–North America region, which has an approximately 90° phase difference from that associated with MSN EOF2, and a loading center over midlatitude Eurasia. Its sources of predictability include the central Pacific-type ENSO and Eurasian snow cover. The MSN EOF4 reflects T2m variability surrounding the Tibetan Plateau, which is plausibly linked to the remote forcing of the Arctic sea ice. The information on the leading predictable patterns and their sources of predictability is further used to develop a calibration scheme to improve the prediction skill of T2m. The calibrated prediction skill in terms of the anomaly correlation coefficient improves significantly over midlatitude Eurasia in a leave-one-out cross-validation, implying a possible way to improve the wintertime T2m prediction in the SEAS5. [ABSTRACT FROM AUTHOR]

The second empirical orthogonal function mode (EOF2) of winter surface air temperature (SAT) over 0°–180° E, 40°–90° N during 1979–2005 is defined as warm Arctic-cold Eurasia (WACE) pattern. The present study evaluates the performance of 25 Coupled Model Inter-comparison Project Phase 5 (CMIP5) models in simulating the WACE pattern based on historical runs. There exist large inter-model spreads in the simulation of the WACE pattern. Analyses show that the ability of a CMIP5 model in capturing the WACE pattern is connected with the model's performance in representing the observed atmospheric circulation anomalies related to the winter sea ice concentration (SIC) variation over Barents–Kara Seas. Sea ice loss over Barents–Kara Seas can induce significant positive geopotential height anomalies over Arctic region and negative geopotential height anomalies around the Baikal Lake, resulting in warm anomalies over Barents–Kara Seas and cold anomalies over Eurasia. Further analysis shows that CMIP5 model's performance in representing the SAT anomalies related to the WACE pattern is partly due to simulation of the amplitude of winter SIC variability over Barents–Kara Seas. Larger standard deviations of winter SIC over Barents–Kara Seas can instigate stationary wave-train more easily, which further induces the SAT anomalies. [ABSTRACT FROM AUTHOR]

The surface air temperature in the northern mid-latitudes during winter showed a significant cooling trend from the late 1990s to the early 2010s, in spite of increasing greenhouse gas concentrations. This unexpected cooling, which was particularly strong across Eurasia, has been partly attributed to Arctic sea-ice loss. Here, the statistical relationship between Arctic sea-ice loss and surface air-temperature change during winter in Eurasia, which is often referred to as the warm Arctic–cold Eurasia pattern, is re-evaluated by using a break-point trend analysis and maximum covariance analysis. A significant time-lagged covariability is observed between the Arctic sea-ice concentration over the Barents–Kara seas and the Eurasian surface air temperature during winter, with the former leading the latter by approximately two months. More importantly, the timing of an abrupt decline in the autumn Arctic sea ice that occurred in the late 1990s is coincident with the beginning of the Eurasian winter cooling. This concurrent trend change is statistically significant and robustly found in both the break-point analysis and maximum covariance analysis. These results suggest that both the interannual variability and decadal trend change seen for the surface air temperature during Eurasian winters are likely influenced by regional sea-ice changes over the Barents–Kara seas. [ABSTRACT FROM AUTHOR]

Siberia is a region where despite global warming a winter cooling trend has been observed over last decades. This cooling trend and its potential linkage to Arctic sea ice loss are controversially discussed. However, recent winters have not been taken into account so far. Here, we analyse ERA‐Interim reanalysis data until 2017 and ERA20C reanalysis to investigate the robustness of the winter surface air temperature trends to updated and extended time periods. Our results show that winter temperatures in Siberia were above normal after 2013 leading to strongly reduced cooling trends since 1980. The trend before 2014 was dominated by four cold winters between 2010 and 2013. These cold winters were mainly caused by strong negative phases of the North Atlantic Oscillation (NAO), except for the winter 2011/2012, where the NAO was positive and a strongly negative phase of the Pacific Decadal Oscillation (PDO) in combination with low sea ice in the Barents Sea caused the cold winter. Both NAO and PDO shift from more negative to positive phases in 2014 and contribute to a return to warmer Siberian temperatures. Furthermore, the NAO shows no trend between 1980 and 2017 indicating that the suggested linkage between Arctic sea ice loss and a negative trend in this mode is not robust. However, continuously low Arctic sea ice in recent years and a slightly negative trend in the PDO since 1980 contribute to the remaining observed cold trends over parts of Eurasia between 1980 and 2017. [ABSTRACT FROM AUTHOR]

A winter Eurasian cooling trend and a large decline of winter sea ice concentration (SIC) in the Barents–Kara Seas (BKS) are striking features of recent climate changes. The question arises as to what extent these phenomena are related. A mechanism is presented that establishes a link between recent winter SIC decline and midlatitude cold extremes. Such potential weather linkages are mediated by whether there is a weak north–south gradient of background tropospheric potential vorticity (PV). A strong background PV gradient, which usually occurs in North Atlantic and Pacific Ocean midlatitudes, acts as a barrier that inhibits atmospheric blocking and southward cold air intrusion. Conversely, atmospheric blocking is more persistent in weakened PV gradient regions over Eurasia, Greenland, and northwestern North America because of weakened energy dispersion and intensified nonlinearity. The small climatological PV gradients over mid- to high-latitude Eurasia have become weaker in recent decades as BKS air temperatures show positive trends due to SIC loss, and this has led to more persistent high-latitude Ural-region blocking. These factors contribute to increased cold winter trend in East Asia. It is found, however, that in years when the winter PV gradient is small the East Asian cold extremes can even occur in the absence of large negative SIC anomalies. Thus, the magnitude of background PV gradient is an important controller of Arctic–midlatitude weather linkages, but it plays no role if Ural blocking is not present. Thus, the "PV barrier" concept presents a critical insight into the mechanism producing cold Eurasian extremes and is hypothesized to set up such Arctic–midlatitude linkages in other locations. [ABSTRACT FROM AUTHOR]