The Global Climate Observing System has identified the need for systematic global daily snow cover data sets over land. Current in situ snow cover data sets have limited spatial coverage while satellite-based snow cover records have either limited historical extent or limited temporal and spatial resolution because of cloud cover or specific sensor availability. NOAA Advanced Very High Resolution Radiometer (AVHRR) data offers nearly complete daily global coverage of the Northern Hemisphere, extending back to the early 1980s with successors slated to continue into the next decade. In this paper, we apply a new algorithm, Snowcover, to estimate daily snow cover, including periods of cloudy conditions, from AVHRR Polar Pathfinder (APP) data over Northern Hemisphere land surfaces. This new snow cover product is compared to snow cover estimates derived from long-term in situ snow depth measurements over Canada and the northern Eurasia. The APP snow cover maps showed an 80% agreement rate or better at 95% of the in situ sites. This performance was comparable to the agreement of MODIS 0.05 degree snow cover products over the same sites; although the MODIS product was only retrieved ∼20% of the time corresponding to clear sky conditions in contrast to over 95% of the time with the APP snow product. The almost continuously temporal and spatial coverage for the past 23 years from 1982 to 2004 over Northern Hemisphere makes the new daily snow cover product especially suitable for analysis of large-scale patterns of spring snowmelt in association with variability of circumpolar climate and ecological parameters.