Snowmelt runoff onset timing represents a critical hydrological parameter, particularly in mountainous regions where seasonal snow serves as a natural reservoir for downstream water resources. Despite this importance, high-resolution observations of snowmelt runoff onset across complex terrain are limited, due to challenges from sparse in situ monitoring networks, intermittent optical remote sensing data, and coarse passive microwave remote sensing data.</p> <p>To address this gap, we prepared a global snowmelt runoff onset timing dataset (<a href="https://doi.org/10.5281/zenodo.16953614">https://doi.org/10.5281/zenodo.16953614</a>) for the 10-year period spanning 2015 to 2024, with 80-meter spatial resolution and 9.2-day average temporal resolution. We created this dataset by identifying backscatter minima indicative of runoff onset in a time series of Sentinel-1 C-band SAR images, with detection constrained by a custom MODIS-derived snow phenology dataset.</p> <p>We validated our dataset using in situ snow pillow estimates of runoff onset from 735 automated weather stations in the Western United States, finding a median timing difference of -1.0 days and a median absolute deviation of 9.0 days. The local agreement between our runoff onset estimates and snow pillow runoff onset estimates varies with site-specific variables like forest cover fraction, SWE, and dataset temporal resolution. We characterized these dependencies to provide empirically-derived thresholds for quality filtering as well as guidance for interpretation and use of our products.</p> <p>The dataset includes global annual runoff onset products for each water year, annual local temporal resolution products for each water year, and 10-year composites of median runoff onset, median absolute deviation, and local temporal resolution. This unique combination of high spatial resolution, global coverage, and decade-long temporal coverage provides unprecedented detail for the study of snowmelt runoff onset across snow-covered regions. Our snowmelt runoff onset dataset enables an improved understanding of mountain hydrological processes and informs water resource management in snow-dominated watersheds.