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An enhanced Warm Arctic—Cold Eurasia (WACE) pattern has been a notable feature in recent winters of the Northern Hemisphere. However, divergent results between model and observational studies of the WACE still remain. This study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating the WACE pattern in winter of 1980–2014 and explores the key factors causing the differences in the simulation capability among the models. The results show that the multimodel ensemble (MME) can better simulate the spatial distribution of the WACE pattern than most single models. Models that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well, especially the latter, usually can/cannot simulate the WACE pattern well. This mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea—Kara seas (BKS) region. Further analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking (UB), which can transport heat to the BKS region, causing the warm Arctic, and strengthen the westerly trough downstream, cooling central Eurasia. Therefore, simulation of UB is key and significantly affects the model's performance in simulating the WACE. [ABSTRACT FROM AUTHOR]

Since the 1980s, rapid Arctic sea ice loss has been observed, and its potential influences on the midlatitude weather and climate have been extensively examined, but strongly debated. This study instead investigates influences of Arctic sea ice loss on the Eastern Hemisphere westerly wind on the poleward side of the polar front jet (PFJ), which has significantly weakened in winter but strengthened in summer since 1980s. Observational analyses indicate that the Eastern Hemisphere PFJ anomalies in winter and summer are strongly correlated with Northern Hemisphere (NH) atmospheric circulation, surface air temperature and precipitation changes, and that the winter PFJ variability is significantly correlated to Barents-Kara sea ice anomalies from autumn and winter at interannual time scales. About 58% of the observed winter PFJ weakened trend during 1979–2014 is congruent with the autumn sea ice index over the Barents-Kara Seas. Atmospheric model ensemble simulations from four models show that Arctic sea ice loss contributes to Arctic warming in winter and reduces the northern Eurasia-pole temperature contrast, leading to an significant weakening winter PFJ. Ensemble mean effects of four models and each model due to Arctic sea ice loss explain about 10–20% of the observed winter PFJ weakening trend, because the model simulations underestimate observed impacts of sea ice reduction on Arctic troposphere warming. In summer, the strengthening PFJ is mostly controlled by increasing greenhouse gases and sea surface temperature changes outside the Arctic, but is little affected by Arctic sea ice loss. Our observational and numerical results consistently suggest that a dynamical pathway linking observed Arctic sea ice loss to northern Eurasian winter is through its weakening effect on the westerly wind on the poleward side of the PFJ. [ABSTRACT FROM AUTHOR]

Based 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. Plain Language Summary: Observations and idealized model simulations have shown that strong Ural blocking (UB) anomalies in November can induce the "warmer Arctic, colder Eurasia" anomaly in the following December. In this study, a large number of coupled simulations are employed. The results show that the impact of November UB on early‐winter Arctic‐Eurasian temperature is sensitive to the intensity of November mid‐latitude (around 60°N) westerly jet over Eurasia. When November UB anomalies are accompanied by a significantly weakened mid‐latitude westerly jet, early‐winter would experience a warmer Arctic‐colder Eurasia pattern. The significantly weakened westerly wind waveguide is favorable for stronger upward propagation of planetary waves caused by UB anomalies, which leads to persistent atmospheric response in the following December. Key Points: Early‐winter atmospheric response to November Ural blocking (UB) anomalies is sensitive to the background state of westerly jetStrong UB with sufficiently weakened westerly jet in November can induce a warmer Arctic‐colder Eurasia pattern in DecemberThe weakened westerly wind waveguide promotes stronger upward propagation of planetary waves forced by UB anomalies [ABSTRACT FROM AUTHOR]

The large ensembles of the IPSL-CM6A-LR model output for the historical forcing experiment were employed to investigate the role of internal variability in the formation of the recent "warm Arctic–cold Eurasia" trend pattern in winter surface air temperature (SAT). The ensemble-mean SAT shows a positive trend over Arctic during 1990–2014, indicating a positive contribution of anthropogenic forcing to the warming Arctic. Over the region of central Eurasia, the ensemble-mean SAT trend is opposite to the observed trend. The winter SAT trends display remarkable inter-member diversity over the Barents–Kara Seas (BKS) region and central Eurasia, suggesting an important role played by internal variability. In addition to anthropogenic forcing, the results suggest that the barotropic anticyclone over northern Eurasia arising from internal variability can also contribute positively to the warming anomalies over the BKS region. On the other hand, through a fingerprint pattern matching method, it is found that the observed cooling trend over central Eurasia tends to be predominantly due to the internal variability. Finally, the results estimate that the internal variability can contribute to about 50–60% of the observed warming trend over the BKS region. [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]

The high latitudes are a hotspot for past and future climate change as forced climate signals have begun to emerge from internal variability in recent decades. New tools, such as initial condition large ensembles, provide a simulated range of possible climate realities that allow for separating the externally forced and internally variable components of the climate system. In addition, interactions between environmental variables and atmospheric circulation patterns can be detected in an unforced climate scenario and removed to isolate thermodynamic influences on the climate system. In the Arctic, this separation between dynamic and thermodynamic influences can be used to examine the impact of permafrost degradation on surface air temperatures (SAT). While impacts from permafrost degradation and subsequent carbon release have been thoroughly studied, geophysical influences have not received as much attention. This study employs the Community Earth System Model's Large Ensemble to simulate and analyze these geophysical impacts over three time periods: 1976–2005, 2021–2050, and 2071–2100. As soil is thawing earlier and freezing later, we focus on spring and autumn to determine permafrost's thermodynamic influence on SAT across Eurasia. We find that large internal variability, primarily due to atmospheric dynamics, affects spring SATs through 2100 while variability in autumn SATs will decrease over time due to increasing thermodynamic surface factors. These thermodynamic surface influences are most prominent in areas of continuous and discontinuous permafrost and lesser in non-permafrost regions, likely the result of a changing seasonal surface energy budget resulting from degradation and loss of permafrost. [ABSTRACT FROM AUTHOR]

The 2019/2020 wintertime (December–March) anomalies of sea level pressure, temperature, and precipitation are analyzed. The contribution of the 40-year linear trend in these parameters associated with global climate change and of the interannual variability associated with the Arctic Oscillation (AO) is assessed. In the 2019/2020 winter, extreme zonal circulation was observed. The mean wintertime AO index was 2.20, which ranked two for the whole observation period (started in the early 20th century) and was outperformed only by the wintertime index of 1988/1989. It is shown that the main contribution to the 2019/2020 wintertime anomalies was provided by the AO. A noticeable contribution of the trend was observed only in the Arctic. Extreme anomalies over Northern Eurasia were mainly associated with the AO rather than the trend. However, the AO-related anomalies, particularly air temperature anomalies, were developing against the background of the trend-induced increased mean level. [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 interannual variability of the global mean monthly anomalies of near-surface air temperature, sea-level pressure, wind speed near the surface, amount of precipitation and total cloudiness was investigated. The amplitudes of the anomalies of these hydrometeorological characteristics between opposite phases of the Global Atmospheric Oscillation (GAO) were calculated. The regional element of the GAO in the tropics of the Indian and Pacific Oceans is the Southern Oscillation. The results show that the oscillations of these characteristics are associated with the GAO not only in the tropical belt of the Earth but also in the middle and high latitudes, especially in the Arctic and northern Eurasia. The physical mechanism by which the transition of the GAO from the negative to the positive phase influences the weakening of the Pacific trade winds, and, as a consequence, the onset of El Niño is described. [ABSTRACT FROM AUTHOR]