Snow Cover Phenology Monitoring and Dynamic Analysis Using Google Earth Engine in Western Iran’s Mountainous Regions

Abstract. Snow cover in mountainous regions plays a vital role in regional climate regulation, freshwater supply, and ecosystem stability. Phenological variations in snow cover—ranging from shifts in onset and melting periods to fluctuations in snow extent and depth— serve as sensitive indicators of climate change impacts. Over the past decade, numerous studies have reported a decline in snow persistence and volume in high-altitude zones, primarily driven by global warming. Satellite data analysis and modeling approaches have validated these trends, warning of serious consequences such as freshwater shortages, biodiversity loss, and disruptions to agricultural systems if such patterns persist. In this study, we employed MODIS satellite products and ground-based synoptic station data across West Azerbaijan Province, Iran. Using the Google Earth Engine (GEE) platform, snow cover dynamics were assessed over four years (2021–2024), focusing on the months from January through April. The analysis applied the Normalized Difference Snow Index (NDSI) and FLDAS parameters—including Snow Depth, Snow Cover, Snow Fall Rate, and Snow Water Equivalent—to derive time-series plots and spatial distribution maps. Results indicate a significant decline in snow cover, particularly in southern and southeastern parts of the province. The decreasing trend was corroborated through both remote sensing and ground station validation. This study highlights the necessity for continuous snow phenology monitoring and emphasizes the need for strategic planning and adaptive policy measures at regional and global scales to address the implications of changing snow dynamics.