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 the 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.

High-latitude low clouds in the Northern winter have been known to be closely related to the Arctic surface air temperature by controlling downward longwave radiation, but Earth system models often fail to accurately simulate this relationship. In this study, we conducted a series of model experiments to examine the role of winter high-latitude low-level clouds in determining the Arctic surface temperature. Our findings show that low-level clouds play a significant role in regulating the Arctic surface temperature. We used the NCAR CAM6 model and compared the results of an unforced simulation run with those of an experiment using an empirical low-level cloud scheme to alleviate the typical overestimation of the low cloud fraction of state-of-the-art general circulation models at high latitudes. The unforced simulation exhibited excessive downward longwave radiation in the Arctic, resulting in a significant warm bias compared to reanalysis data. On the other hand, the experiment using a modified scheme more closely resembled the reanalysis data in terms of low-level cloud simulation. Overall, our study underscores the importance of accurately representing low-level clouds in high-latitude regions to reduce surface temperature bias in the model.

Many global climate models (GCMs) have difficulty in simulating climate variabilities over high northern latitudes. One of the main reasons is the inability of GCMs to simulate proper cloud fraction and the amount of liquid-containing cloud over the region. This study assessed the impact of cloud simulation in high latitudes by comparing the long-term parallel simulations of Community Atmosphere Model version 6 (CAM6) and CAM5, the previous version. The results show that the CAM6 simulation exhibits a considerable improvement in the Arctic, especially by reducing the cold bias of CAM5 throughout the year. Over the sub-Arctic region, however, CAM6 produces an excessive cold bias in summer and a warm bias in winter compared to the observation, which is closely related to the overestimation of cloud fraction and the amount of cloud liquid. In summer, the overestimation of the cloud in CAM6 tends to alleviate the cold bias compared to CAM5 due to an increase in downward longwave radiation over the high latitudes, while causing the excessive cold bias by blocking downward shortwave radiation over the sub-Arctic land area. In winter, when there is little incidence of shortwave radiation, the overestimation of the cloud in CAM6 increases the downward longwave radiation, which alleviates the cold bias in CAM5 over the Arctic but induces an excessive warm bias over the sub-Arctic land. The excessive cloudiness in CAM6 could weaken the high-latitude internal variability, exacerbating the deteriorating climate variability and long-term trend simulations in the region.

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