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Recent studies propose that the Asian--Bering--North American (ABNA) teleconnection is a distinct atmospheric pattern that is related to Eurasian and North American winter climate besides the Pacific--North America (PNA) pattern, while its origin remains elusive. This study investigates the interannual variability of the ABNA during the past 42 winters (1979-2020) and the associated prior surface boundary forcings. The ABNA explains coherent surface air temperature changes in northern Asia, eastern Siberia--Alaska, and eastern North America, even after removing the impacts of the PNA, the Arctic Oscillation, the North Atlantic Oscillation, and the North Pacific Oscillation. Surface boundary conditions linked to the ABNA could be traced back to a Eurasian snow cover dipole pattern (ESCDP) and a Maritime Continent sea surface temperature anomaly (MCSST) in November. The ESCDP leads to a displacement of the Arctic stratospheric polar vortex via troposphere--stratosphere coupling. The anomalous polar vortex propagates downward in the following winter and generates the tropospheric ABNA pattern. The MCSST induces a diabatic heating anomaly, which is associated with a tropical western Pacific precipitation anomaly (TWPP) in winter. The TWPP excites a poleward Rossby wave train that propagates across the North Pacific and directly strengthens the ABNA. The above physical processes can be well reproduced by a linear baroclinic model (LBM). Based on the ESCDP and MCSST predictors, an empirical model is established and shows a promising prediction skill of the ABNA during the hindcast period. This can provide a useful strategy for seasonal prediction of winter climate in the Northern Hemisphere extratropics. [ABSTRACT FROM AUTHOR]

Significant surface air temperature warming during summer 1979–2020 is not uniformly distributed in the northern midlatitudes over land but rather is confined to several longitudinal sectors including Europe, central Siberia and Mongolia, and both coasts of North America. These hot spots are accompanied by a chain of high pressure ridges from an anomalous, circumglobal Rossby wave train in the upper troposphere. From reanalysis data and several baseline experiments from phase 6 of the Coupled Model Intercomparison Project (CMIP6), we find that the circulation trend pattern is associated with fluctuations of the Atlantic multidecadal variability (AMV) and the interdecadal Pacific oscillation. The phase shift of AMV in the 1990s is particularly noteworthy for accelerating warming averaged over the northern midlatitude land. The amplitude of the observed trend in both surface air temperature and the upper-level geopotential height generally falls beyond the range of multidecadal trends simulated by the CMIP6 preindustrial control runs, supporting the likelihood that anthropogenic forcing played a critical role in the observed trend. On the other hand, the fidelity of the simulated low-frequency modes of variability and their teleconnections, especially on multidecadal time scales, is difficult to assess because of the relatively short observational records. Our mechanistic modeling results indicate that synoptic eddy–mean flow interaction is a key to the formation of the anomalous wave train but how the multidecadal modes can modulate the synoptic eddies through atmosphere–ocean and atmosphere–land interactions remains poorly understood. This gap in our knowledge makes it challenging to quantify the roles of the low-frequency modes and external forcings in causing the observed multidecadal trends. [ABSTRACT FROM AUTHOR]

Record-breaking heatwaves and wildfires immersed Siberia during the boreal spring of 2020 following an anomalously warm winter. Springtime heatwaves are becoming more common in the region, with statistically significant trends in the frequency, magnitude, and duration of heatwave events over the past four decades. Mechanisms by which the heatwaves occur and contributing factors differ by season. Winter heatwave frequency is correlated with the atmospheric circulation, particularly the Arctic Oscillation, while the frequency of heatwaves during the spring months is highly correlated with aspects of the land surface including snow cover, albedo, and latent heat flux. Idealized AMIP-style experiments are used to quantify the contribution of suppressed Arctic sea ice and snow cover over Siberia on the atmospheric circulation, surface energy budget, and surface air temperature in Siberia during the winter and spring of 2020. Sea ice concentration contributed to the strength of the stratospheric polar vortex and Arctic Oscillation during the winter months, thereby influencing the tropospheric circulation and surface air temperature over Siberia. Warm temperatures across the region resulted in an earlier-than-usual recession of the winter snowpack. The exposed land surface contributed to up to 20% of the temperature anomaly during the spring through the albedo feedback and changes in the ratio of the latent and sensible heat fluxes. This, in combination with favorable atmospheric circulation patterns, resulted in record-breaking heatwaves in Siberia in the spring of 2020. [ABSTRACT FROM AUTHOR]

The western Pacific pattern (WP) is one of the most important atmospheric teleconnections over the Northern Hemisphere (NH) in boreal winter and plays key roles in regulating weather and climate variations over many parts of the NH. This study evaluates the ability of the coupled models participating in CMIP5 and CMIP6 to capture the spatial pattern, dominant frequency, and associated climate anomalies of the winter WP. Ensemble means of the CMIP5 and CMIP6 models well capture spatial structures of the WP, with slightly higher skills for the CMIP6. However, the northern (southern) center of the WP is shifted westward (eastward) relative to the observations, and the strength of the northern center is overestimated in most CMIP5 and CMIP6 models. CMIP6 shows an improvement in simulating the dominant periodicity of the WP. WP-related climatic anomalies in most parts of the NH can be well simulated. However, there exists a large spread across the models in simulating surface air temperature (SAT) anomalies in the Russian Far East and northwest North America, which is attributable to the diversity of the intensity of the WP's northern lobe. Most CMIP5 and CMIP6 models largely overestimate the WP-related precipitation anomalies over Siberia, which is partly due to the overestimation of mean precipitation there. Furthermore, most models simulate a close relation of the WP and Arctic Oscillation (AO), which does not exist in observation. The CMIP5 and CMIP6 models with weak WP–AO relations have better ability than the models with strong WP–AO relations in capturing the WP-related SAT and precipitation anomalies over the NH, especially over Eurasia. [ABSTRACT FROM AUTHOR]

The effect of Eurasian spring snowmelt on surface air temperature (SAT) in late spring (April-May) and early summer (June-July) and the relevant physical mechanisms during 1981-2016 are investigated. Results show that the first mode of the interannual Eurasian spring snowmelt represents an east-west dipole anomaly pattern, with an intense center over Siberia and another moderate center around eastern Europe. The European spring snowmelt shows an insignificant relation to the local SAT, whereas the Siberian spring snowmelt has a significant impact on the SAT in late spring and early summer. More Siberian spring snowmelt contributes to higher SAT in late spring and lower SAT in early summer via different mechanisms. In late spring, increased Siberian spring snowmelt corresponds to less local surface albedo and cloud cover, leading to the surface absorbing more shortwave radiation and thereby higher SAT. The subsurface and deep soil moisture anomalies generated from Siberian spring snowmelt can persist into early summer. Excessive Siberian spring snowmelt corresponds to positive soil moisture anomalies, contributing to decreased sensible heat and increased cloud cover in early summer. Increased cloud cover leads to the surface receiving less shortwave radiation. Thus, lower SAT appears over Siberia in early summer due to reduced sensible heat and shortwave radiation. However, the simulation of Eurasian spring snowmelt variability and its influences on SAT via the snow hydrological effect is still a challenge for the climate models that participated in phase 6 of the Coupled Model Intercomparison Project. [ABSTRACT FROM AUTHOR]