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The summer surface air temperatures (SAT) over Eurasia exhibit a non‐uniform multidecadal pattern since the 1990s, with amplified warming over Europe–West Asia (EWA) and Northeast Asia (NEA) but weak warming over Central Asia. However, current climate models may inadequately capture this regional pattern. In this study, we evaluated the performance of 44 coupled models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating the decadal variability of Eurasian temperatures. Results show that all the CMIP6 models generally reproduce the largest SAT trends from 1985 to 2020 over EWA and NEA. However, the models fail to capture the non‐uniform warming pattern and the SAT magnitudes are underestimated in most CMIP6 models. We compare "good" and "poor" ensemble, which represent the best and worst simulations of the non‐uniform warming, in order to understand the inter‐model spread. The BMME models capture the teleconnection wave trains from northwest Europe to East Asia, and the associated summer North Atlantic Oscillation like circulation changes. In contrast, the WMME models fail to reproduce such teleconnections. The contrast between the BMME and WMME simulations give a measure of confidence that the non‐uniform warming pattern over Eurasia is tightly coupled with the upper‐tropospheric wave‐like pattern over Eurasia. If such atmospheric circulation changes cannot be reproduced, the non‐uniform warming pattern over Eurasia will not be captured. Our results suggest a fundamental pattern of atmospheric circulation changes that determine the non‐uniform warming variations in model simulations. Plain Language Summary: Previous studies have documented pronounced multidecadal temperature variations in summer during the late 20th century over Eurasia, with accelerated warming over Europe–West Asia (EWA) and Northeast Asia (NEA), but weak warming over Central Asia. Whether Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models are able to adequately reproduce this non‐uniform pattern remain unknown. Here we quantitatively evaluated the performance of 44 CMIP6 models in simulating the summer surface air temperatures decadal variations over Eurasia since 1950 and further investigated the key factors in causing the differences in the simulation ability among the models. Our results show that a good performance of the model is closely related to its ability in simulating the Silk Road Pattern, which can induce the intrinsic teleconnection wave trains, causing the anticyclonic circulations around EWA and NEA, and increase warm advection and downward shortwave radiation, leading to amplified warming there. Our findings provide a perspective of physical linkage to understand the model uncertainty in simulating the non‐uniform multidecadal pattern over Eurasia. Key Points: Evaluation of Coupled Model Intercomparison Project Phase 6 (CMIP6) models for the summer non‐uniform multidecadal temperature variations over EurasiaThe magnitudes of non‐uniform warming variations are substantially underestimated in most CMIP6 modelsSimulation of the upper‐tropospheric wave‐like pattern is key and significantly affects the model's performance in simulating the surface air temperatures [ABSTRACT FROM AUTHOR]

A zonal dipole pattern of the interannual variability of Eurasian snow cover during late autumn has attracted growing interest due to its extensive influences on large‐scale atmospheric circulations and climate anomalies, but it remains unknown what influences the formation of this pattern. This study revealed the potential drivers and the related physical processes of the dipole mode of the snow cover variability during 1979–2018. Results showed that the atmospheric circulation anomalies play a crucial role in forming the dipole mode, which could be further attributed to the influences of the atmospheric teleconnection patterns and the variations of sea surface temperature (SST) and sea ice concentration. Specifically, the anomalous circulations related to the teleconnections of the Eastern Atlantic pattern, East Atlantic–Western Russia pattern, and Scandinavian pattern could lead to the anomalies of air temperature and snowfall that directly shape the variability of snow cover. In addition, a dipole structure of the SST anomalies over the North Atlantic exerts an important effect on the snow cover variability through exciting an eastward propagating Rossby wave train prevailing over Eurasia. Moreover, the snow cover variability is closely linked to the sea ice variations over the Barents Sea that can regulate the anomalous circulations over Eurasia by altering the atmospheric dynamic and thermodynamic conditions. These influencing factors jointly account for about 66% of variances in the dipole mode of snow cover variability, suggesting that our findings can substantially improve the understanding of the Eurasian snow cover variations. Plain Language Summary: This study investigated the possible influencing factors responsible for the formation of the west‐east dipole structure of Eurasian snow cover variability during late autumn that has notable impacts on the atmospheric circulations and climate anomalies in the following season. Results suggested that the anomalous circulations associated with the atmospheric teleconnections of the Eastern Atlantic pattern, East Atlantic‐Western Russia pattern, and Scandinavian pattern can effectively regulate the snow cover variability related to the dipole pattern through inducing the anomalies of surface air temperature and snowfall. In addition, the North Atlantic sea surface temperature anomalies play a considerable role in forming the dipole mode by exciting a wave train type anomalous circulation over Eurasia. Furthermore, the variations of sea ice concentration in the Barents Sea could lead to the snow cover variability through modulating the temperature gradient over mid‐high latitudes and the resultant circulation anomalies over Eurasia. The synergetic effect of these influencing factors explains about two‐thirds of the snow cover variability related to the dipole mode, indicating the important contribution of our results to understanding the Eurasian autumn snow cover anomaly. Key Points: The west‐east dipole pattern is the intrinsic mode of the Eurasian snow cover variability during late autumnThe dipole mode is closely associated with the Eastern Atlantic pattern, East Atlantic‐Western Russia pattern, and Scandinavian patternAnomalies of North Atlantic sea surface temperature and Barents sea ice can exert considerable effects on the dipole mode [ABSTRACT FROM AUTHOR]

To examine the effect of the snow‐albedo feedback (SAF) on the current surface climate across terrestrial regions at mid–high latitudes, we perform a series of idealized sensitivity experiments using an atmospheric general circulation model (AGCM), in which the snow albedo is assumed to be considerably smaller than that in the control experiment. When the snow albedo is reduced, the fall and spring surface air temperatures (SATs) in northern Eurasia are considerably higher than those in the control experiment. Particularly, the spring SAT at terrestrial high latitudes rises by more than 10°C, due to low snow albedo. Despite the small surface snow albedo during both fall and spring, the fall temperature difference between the two experiments is smaller than that during spring. The feedback with the hydrological effect, which accelerates snowmelt, is either nonexistent or weak during periods of seasonally low air temperatures. This result indicates that the hydrological effect significantly influences the SAF, and different magnitudes of the hydrological effect including cloud differences are a possible source of SAF uncertainty between models. The radiative albedo effect also impacts the evolution of the snow area in central Asia and eastern Europe through changes in lateral water vapour transport. Furthermore, the experiments indicate that the cooling effect of snow on land is necessary for the strength of the Siberian High and the pattern of Arctic Oscillation, suggesting that snow cover may also significantly extend the duration of Arctic Oscillation effects. [ABSTRACT FROM AUTHOR]

In sharp contrast to rapid global warming, the surface air temperature (SAT) in Northeast Asia (NEA) has exhibited strong cooling in June since 2010. Our results show that this cooling is a possible response to declining Bering Sea sea ice concentrations (BSICs) in March. A physical process analysis shows that decreasing BSICs provoke a south‐eastward‐propagating Rossby wave train and induce a strong anomalous anticyclone over the midlatitude Northwest Atlantic, resulting in tripolar anomalous sea surface temperature (SST) pattern with warm anomalies in the midlatitude Northwest Atlantic. These persistent tripolar SST anomalies generate a new Rossby wave across Eurasia in June, which enhances the cyclonic atmosphere circulation anomaly over NEA and leads to the cold SAT anomalies observed in this area. Correspondingly, in response to the sharp decline in BSIC in March, the NEA has exhibited an unprecedented cooling trend in June over the most recent decade. Plain Language Summary: In contrast to rapid global warming, the surface air temperature (SAT) over Northeast Asia (NEA) in June has exhibited a strong cooling trend since 2010, which has had an important impact on local agriculture. Here we show that reduced Bering Sea sea ice concentrations (BSICs) in March promote cold SATs in the following June in NEA. Declining BSICs in March excite a Rossby wave train that propagates eastward, causing a strong anomalous anticyclone (cyclone) over the midlatitude North Atlantic (subpolar Atlantic) and a tripolar anomalous sea surface temperature (SST) pattern by modifying the surface heat flux. The tripolar SST pattern in the North Atlantic develops in April and May due to the downstream development of the wave train; it persists in June mainly due to the ocean memory effect and subsequently generates a new Rossby wave across Eurasia via eddy‐mediated processes, provoking a cyclonic atmospheric circulation anomaly over NEA and leading to the observed cold SAT anomalies. Accompanying the significant BSIC decline in March since 2010, the atmospheric regime and SST variations over the North Atlantic in association with the cold SAT anomalies observed in NEA in June have strengthened and thus induced strong cooling over NEA. Key Points: Unusual cooling has been observed in June over Northeast Asia (NEA) under the most recent global warmingThis June cooling in NEA is consistent with declining Bering Sea sea ice concentrations (BSICs) in MarchThe Rossby wave train and the sea surface temperature anomalies in Northwest Atlantic bridge the declining BSIC in March and the cooling over NEA in June [ABSTRACT FROM AUTHOR]