The additive value of multi-scale remote sensing snow products for alpine above-snow Cosmic Ray Neutron Sensing

Alpine snow cover is shaped by complex topography, wind and insulation patterns, causing strong lateral heterogeneity in snow water equivalent (SWE) within only a few meters distance. While common SWE observation methods are confined to a footprint area of a few square meters, above-snow cosmic ray neutron sensing (CRNS) detects secondary cosmogenic neutrons that can be translated to SWE from an area of several hectares. The large footprint size decreases the observation bias that is caused by the choice of measurement location in conventional methods. However, the large footprint size also decreases the control on other signal contributing factors. Cosmogenic neutrons are sensitive to all sources of ambient hydrogen, including soil moisture and vegetation. Partial snow cover poses an additional challenge, due to the dissimilar and non-linear contribution of snow-free and snow-covered areas. The predominant development of mountain snowpack into partial snow cover highlights the intricacy of the CRNS signal in the alpine domain. In this study, we explore the complementary value of close-range, mid-range and far-range remote sensing snow products for the characterization of alpine CRNS snow monitoring sites in Austria and Italy. Joined observations of satellite-based fractional snow cover (FSC) products of Sentinel-1 and -2 and MODIS, at a spatial resolution of 20 m, 60 m and 500 m, respectively, provide quasi-daily observations of the snow cover state within the CRNS footprint area. This allows us to identify site-specific snow season parameters and dynamics in the CRNS signal. Further, air-borne and terrestrial topographic lidar (ALS and TLS) campaigns under snow-free and snow-covered conditions provide detailed FCS, snow height distribution and topographic information at a high spatial resolution. The good compatibility of these products is shown by the overall low deviation between lidar derived FSC and Sentinel FSC products of ~11% and between lidar and MODIS FSC of ~13%. Paired with complementary, manual snow density measurements for the computation of distributed SWE and the calibration of the neutron count to SWE conversion, these observations allow us to evaluate the complexity and dynamics of the seasonal CRNS signal at alpine sites. The similarity in spatial resolution between CRNS and satellite-based remote sensing products points towards its high potential for bridging the gap between ground- and space-based snow observations. Dedicated neutron simulations and further investigations are needed to gain a better understanding of factors that contribute to neutron count dynamics in alpine terrain.