Geosciences:Special Issue : Progresses and Gaps on Monitoring of Snow and Its Components at the Local, Regional to Global Scale and Its Applications

Snow plays an essential role in the climatic and environmental challenges of the 21st century. The snow cover represents a key source of global water resources and climate regulation, and has shown high sensitivity to the warming climate. The quantity and quality of collected snow information is also constantly increasing with the possible novel automated methods provided by recent technological development for cheaper and easier monitoring. During the last several decades, instrumentation and measurement techniques—especially remote sensing—have advanced quickly, providing a significant amount of new information about the extent and properties of snow (e.g., snow water equivalent (SWE), albedo, reflectance, microstructure, impurities). In addition, novel technologies such as unmanned aerial vehicles (UAVs) and webcams provide new opportunities and challenges. Optimization and agreement on sampling strategies are important in order to get spatially distributed data at different scales and ensure broad use of the acquired data. Data management has become an important issue after general open data policy, where data sets should be available and usable for other users. A large variety of NWP and hydrological models or operational applications routinely make use of snow data to improve their performance. The forecasting of snow-related hazards in Europe is mostly performed at the country or regional level, and heavily relies on the concurrent meteorological factors and snowpack properties, which are usually acquired from point measurements or physical models. A big challenge is bridging information from microstructural scales of the snowpack up to the grid resolution in models, and then to provide knowledge-based information on potential impacts to society, economy, and safety (e.g., hydro-power, water resources management , transportation, tourism, flooding, and avalanches).