Seasonal snow-cover (SSC) substantially alters surface physical properties over the Northern Hemisphere (NH). It modulates processes within the energy and water cycles, thereby influencing climatology, hydrology, geomorphology and ecology. In spring and summer, snowmelt provides an essential resource for humankind. The identification, quantification and explanation of changing spatial and temporal distributions of SSC helps to predict future impacts on natural and human environments, and informs development of mitigation and adaptation strategies. Because SSC is spatially and temporally heterogeneous, meaningful estimation of trends in its distribution and duration is dependent on long records of remotely-sensed imagery. The Rutgers University Global Snow Laboratory and the United States' National Oceanic and Atmospheric Administration provide the longest such archive (NOAA-Rutgers Snow Archive, NRSA), dating from 1966. However, several studies have raised questions about the credibility of the signs and magnitudes of trends derived from the NRSA, suggesting that they may be artifacts of technological improvements introduced in 1999. This dissertation improves the spatial resolution at which NH SSC extent and duration trends during the NRSA's longest continuous section (since 1971) are reported, building on previous hemispheric and continental studies. It demonstrates that the magnitudes of area-related trends are sensitive to assumptions adopted when estimating SSC extent from the NRSA, and that these sensitivities vary spatially. The study assesses whether temporal trajectories of SSConset trends imply abrupt changes in 1999, particularly over more complex terrain, and finds no evidence of this. It also explores the broader climatological contexts of these trends, together with estimated departures from mean conditions. Evidence is presented at monthly intervals for causative chains linking advection of mid-tropospheric warming from lower to higher latitudes,