Our results show that the realistic representation of vegetation variability has significant effects on the prediction skill at seasonal and decadal time scales. Both seasonal and decadal experiments show considerable sensitivity of the modeled surface climate bias with large improvements in boreal winter (December-January-February; DJF) 2m Temperature (T2M), mean sea level pressure and zonal wind over middle-to-high latitudes of the Northern Hemisphere. Consistently, it is found a significant improvement of the skill in predicting DJF T2M, especially over Euro-Asian Boreal forests, which is shown to be at least in part due to the more realistic representation of the interannual albedo variability that is related to the changes in vegetation shading over snow. Remarkably, from the region with the most considerable T2M improvement over Siberia originates a large-scale ameliorating effect on circulation encompassing Northern Hemisphere middle-to-high latitudes from Siberia to the North Atlantic. The results indicate that the coupling from the land-surface might operate by amplifying locally the signal originating from the North Atlantic sector therefore producing improved T2m skill locally when the NAO teleconnection is active. Concurrently, the improved skill over Euro-Asian domain appears to feedback to the large-scale circulation in such a way to enhance the representation of the circulation pattern and associated interannual anomalies.

