This study assesses the skill of multimodel forecasts of 10-m wind speed, significant wave height, and mean wave period in the North Atlantic for the winter months. The 10-m winds from four North American multimodel ensemble models and three European Multimodel Seasonal-to-Interannual Prediction project (EUROSIP) models are used to force WAVEWATCH III experiments. Ten ensembles are used for each model. All three variables can be predicted using December initial conditions. The spatial maps of rank probability skill score are explained by the impact of the North Atlantic Oscillation (NAO) on the large-scale wind–wave relationship. Two winter case studies are investigated to understand the relationship between large-scale environmental conditions such as sea surface temperature, geopotential height at 500 hPa, and zonal wind at 200 hPa to the NAO and the wind–wave climate. The very strong negative NAO in 2008/09 was not well forecast by any of the ensembles while most models correctly predicted the sign of the event. This led to a poor forecast of the surface wind and waves. A Monte Carlo model combination analysis is applied to understand how many models are needed for a skillful multimodel forecast. While the grand multimodel ensemble provides robust skill, in some cases skill improves once some models are not included.