A Comprehensive Snow Monitoring System to Detect the Impact of Rain-on-snow (ROS) at Ny-Ålesund, Svalbard

In recent decades, the Svalbard archipelago has experienced the fastest warming on Earth, with rates approximately four times higher than the global average. Due to Arctic amplification, the weakening of the polar vortex, rising sea surface temperatures, and retreating sea ice have led to increasingly frequent intrusions of warm, moist air masses from the North Atlantic, resulting in winter temperature anomalies often accompanied by liquid precipitation. In turn, winter rain-on-snow (RoS) events have become more frequent and intense in recent years, causing complex and unprecedented interactions with ecosystems, hydrology, transportation, and infrastructure. Precipitation can substantially alter the physical state of snow cover by increasing liquid water content (LWC) and enhancing surface runoff, while refreezing of meltwater can form basal and internal ice layers, limiting accessibility to the underlying tundra for wildlife such as reindeer. In addition, RoS can also promote early seasonal snowmelt, altering nutrient release timing in Arctic ecosystems and increasing risk to local communities due to flooding and avalanches.

Although remote sensing and atmospheric reanalyses have proven effective for detecting RoS, accurate and reliable in situ measurements remain critical for bridging the multiscale gap . Ground-based snow data not only provide essential validation, but also offer the spatial and temporal resolution needed to resolve rapid, small-scale physical processes within the snowpack. To this end, a comprehensive snow observation system was installed in Ny-Ålesund (Western Spitsbergen, Svalbard) at the end of 2020, providing continuous, high-resolution measurements of several key parameters, including snow depth, SWE, albedo, and vertical profiles of snow temperature and LWC. Over the past five years, the system has been able to record both the seasonal evolution of the snowpack, generally lasting from November to the end of May, and the short-lived perturbations triggered by RoS events, improving our understanding of Arctic snowpack dynamics during extreme events. Here we present the instrumental setup, the main observational results collected between 2020 and 2025, and discuss the diagnostic parameters relevant for RoS process studies and model evaluation.