Mountain seasonal snow cover regulates freshwater supply for over one billion people, yet the seasonal snow zone—the transitional belt between permanent snow and snow-free terrain—lacks standardized metrics for characterizing its spatial extent and temporal dynamics. Nevertheless, how this zone responds to recent climate variability remains uncertain, particularly regarding areal extent versus vertical elevation range changes across diverse mountain systems. In this study, we developed a Snow Cover Frequency (SCF) framework by fusing Sentinel-2 and Landsat-8 imagery on Google Earth Engine and applied it to 179 Global Mountain Biodiversity Assessment (GMBA)-defined mountain units across the contiguous United States during 2018–2024 at 30 m resolution. Results showed that SCF-based classification effectively delineates mountain terrain into Permanent Snow Area (PSA), Seasonal Snow Area (SSA), and Non-Snow Area (NSA), with validation against 741 SNOTEL stations yielding overall accuracy of 0.85-0.90 and r = 0.687. Moreover, we found substantial interannual variability in snow cover extent, with SSA ranging from 794 to 945 × 10³ km² (±19%) and PSA exhibiting threefold variation (1.2-3.6 × 10³ km²), both displaying declining trajectories over the study period, consistent with NOAA continental snow extent records, though caution is warranted in extrapolating these short-term signals to long-term secular trends. Notably, we also found that SSA trends exhibit a statistically significant latitudinal gradient but no significant elevation dependence, indicating that broad-scale climate patterns exert stronger control on seasonal snow dynamics than local topographic factors. These findings provide a transferable framework for monitoring mountain snow zone shifts, which can serve as a significant guide to water resource management and climate adaptation planning for snow-dependent regions worldwide.
Wu et al. (Thu,) studied this question.