Abstract. Long-term phenological data in alpine regions are often limited to a few locations and thus, little is known about climate-change induced plant phenological shifts above the treeline. Because plant growth initiation in seasonally snow-covered regions is largely driven by snowmelt timing and local temperature, it is essential to simultaneously track phenological shifts, snowmelt, and near-ground temperatures. In this study, we make use of ultrasonic snow height sensors installed at climate stations in the Swiss Alps to reveal phenological advance of grassland ecosystems and relate them to climatic changes over 25 years (1998 – 2023). When snow is absent, these snow height sensors additionally provide information on plant growth at a uniquely fine temporal scale. We applied a two-step machine learning algorithm to separate snow- from plant-height measurements, allowing us to determine melt-out for 122 stations between 1560-2950 m a.s.l., and to extract seasonal plant growth signals for a subset of 40 stations used for phenological analyses. We identified the start of growth, and calculated temperature trends, focusing particularly on thermal conditions between melt-out and growth initiation. We observed an advance of green-up by -2.4 days/decade coinciding with strong warming of up to +0.8°C/decade. Although the timing of snowmelt has not changed significantly over the study period in this focal region, phenological responses to early melt-out years varied due to differing influences of photoperiodic and thermal constraints, which were not equally important across elevations and communities. Phenological shifts of alpine grasslands are thus likely to become even more pronounced if snowmelt timing advances in the future as predicted. As climate change continues to reshape mountain ecosystems, understanding the interplay between phenological changes and species turnover will be essential for predicting future biodiversity patterns and informing conservation strategies in alpine regions.