Abstract
Information on snow properties is of critical relevance for a wide range of scientific studies and operational applications, mainly for hydrological purposes. However, the ground-based monitoring of snow dynamics is a challenging task, especially over complex topography and under harsh environmental conditions. Remote sensing is a powerful resource providing snow observations at a large scale. This study addresses the potential of using Sentinel-2 high-resolution imagery to assess moderate-resolution snow products, namely H10—Snow detection (SN-OBS-1) and H12—Effective snow cover (SN-OBS-3) supplied by the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) project of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). With the aim of investigating the reliability of reference data, the consistency of Sentinel-2 observations is evaluated against both in-situ snow measurements and webcam digital imagery. The study area encompasses three different regions, located in Finland, the Italian Alps and Turkey, to comprehensively analyze the selected satellite products over both mountainous and flat areas having different snow seasonality. The results over the winter seasons 2016/17 and 2017/18 show a satisfying agreement between Sentinel-2 data and ground-based observations, both in terms of snow extent and fractional snow cover. H-SAF products prove to be consistent with the high-resolution imagery, especially over flat areas. Indeed, while vegetation only slightly affects the detection of snow cover, the complex topography more strongly impacts product performances.
Highlights
The knowledge of the extent and location of snow cover is of key importance to enhance the understanding of the present and future climate, hydrological cycle, and ecological dynamics, at both local and global scales [1,2]
This study aims to investigate the potential use of S-2 data to assess the reliability of moderate-resolution products of snow extent and fractional snow cover (FSC), that are the snow-related quantities most commonly used as input for hydrologic, meteorological and climate modelling [2]
After introducing forthe thegeneration generationofof the satellite snow products investigated in this study, the processing of in-situ data and imagery used to validate
Summary
The knowledge of the extent and location of snow cover is of key importance to enhance the understanding of the present and future climate, hydrological cycle, and ecological dynamics, at both local and global scales [1,2]. Information on the spatial and temporal distribution of snow cover is critical for several research purposes and operational applications [6]. The monitoring of a snow-covered area is generally hindered by the complex interactions among site-dependent factors, especially in mountainous and forested regions. Meteorological forcings (i.e., precipitation regime, average air temperature, solar radiation) [7,8,9] and local topography (i.e., elevation, slope orientation and mean aspect) [10,11,12] are the most explanatory variables affecting spatial and temporal variability and persistence of snow cover. The definition of the topographic control on snow distribution is made challenging by the presence of vegetation, which intercepts snowfall and impacts the intensity of meteorological forcings [13,14,15]
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