The relationship between Eurasian snow cover extent (SCE) and Northern Hemisphere atmospheric circulation is studied in reanalysis during 1979–2014 and in CMIP5 preindustrial control runs. In observations, dipolar SCE anomalies in November, with negative anomalies over eastern Europe and positive anomalies over eastern Siberia, are followed by a negative phase of the Arctic Oscillation (AO) one and two months later. In models, this effect is largely underestimated, but four models simulate such a relationship. In observations and these models, the SCE influence is primarily due to the eastern Siberian pole, which is itself driven by the Scandinavian pattern (SCA), with a large anticyclonic anomaly over the Urals. The SCA is also responsible for a link between Eurasian SCE anomalies and sea ice concentration (SIC) anomalies in the Barents–Kara Sea. Increasing SCE over Siberia leads to a local cooling of the lower troposphere and is associated with warm conditions over the eastern Arctic. This is followed by a polar vortex weakening in December and January, which has an AO-like signature. In observations, the association between November SCE and the winter AO is amplified by SIC anomalies in the Barents–Kara Sea, where large diabatic heating of the lower troposphere occurs, but results suggest that the SCE is the main driver of the AO. Conversely, the sea ice anomalies have little influence in most models, which is consistent with the different SCA variability, the colder mean state, and the underestimation of troposphere–stratosphere coupling simulated in these models.

The research leading to these results has received funding from the European Union 7th Framework Programme under grant agreement #308299 (NACLIM). Javier García- Serrano also received funding from H2020-funded DPETNA grant (MSCA-IF-EF655339). We thank the European Center for Medium Range Weather Forecast for providing the ERA-Interim reanalysis, the Rutgers University for providing the observed snow cover fields, the National Snow and Ice Data Center for providing the sea ice extent. For their role in producing, coordinating, and making available CMIP5 model outputs, we acknowledge the climate modeling groups, the World Climate Research Programme's Working Group on Coupled Modelling and the Global Organization for Earth System Science Portals. This study benefited from the IPSL mesocenter facility which is supported by CNRS, UPMC, Labex L-IPSL, which is funded by the ANR (Grant #ANR-10-LABX-0018), and by the European FP7 IS-ENES2 project (Grant #312979).

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