It is now widely understood that seasonal snow cover in the Western United States is melting earlier than in past decades. This could have significant consequences for human populations and ecosystems dependent on regularity in timing and magnitude of downstream flows that originate as snow. However, while earlier melt is well established, less is known about intra-annual changes in the spatial and temporal distribution of accumulation and ablation (melt) cycles in the core winter months and spring months, i.e. the ‘persistence’ of seasonal snow cover. This is significant because changes to the persistence of seasonal snow in the winter and spring could have important implications for other snow cover characteristics such as albedo, as well as ancillary hydrologic factors such as soil moisture and runoff. To understand these changes in persistence, this project focuses on study basins in different climatic zones of the Columbia river basin, capturing the shift from maritime snowpack in the west to alpine snowpack in the east. The research relies on a combination of time series analysis of NRCS SNOTEL stations and snow courses and use of an optical remote sensing product which is based on the MODIS MOD10A1 dataset. To compensate for significant winter and spring cloud cover, particularly in the Pacific Northwest, a temporal and spatial gap filling approach utilizing higher spatial resolution products (e.g. Landsat and Sentinel 2) is implemented primarily in Google Earth Engine. The seasonal snow persistence from the MODIS-based product is evaluated using additional Landsat, Sentinel 2 and Planet Labs data, as well as data from the in situ monitoring stations. Finally, changes in intra-annual seasonal snow cover persistence are characterized for core winter, spring and early summer months along an elevational gradient and across study sub-basins.