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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/tc-2019-175
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-175
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 04 Sep 2019

Submitted as: research article | 04 Sep 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal The Cryosphere (TC).

Use of Sentinel-1 radar observations to evaluate snowmelt dynamics in alpine regions

Carlo Marin1, Giacomo Bertoldi2, Valentina Premier1, Mattia Callegari1, Christian Brida2, Kerstin Hürkamp3, Jochen Tschiersch3, Marc Zebisch1, and Claudia Notarnicola1 Carlo Marin et al.
  • 1Institute for Earth Observation, Eurac Research, Viale Druso, 1 I-39100 Bolzano, Italy
  • 2Institute for Alpine Environment, Eurac Research, Viale Druso, 1 I-39100 Bolzano, Italy
  • 3Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Radiation Medicine, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany

Abstract. Knowing the timing and the evolution of the snow melting process is very important, since it allows the prediction of: i) the snow melt onset; ii) the snow gliding and wet-snow avalanches; iii) the release of snow contaminants and iv) the runoff onset. The snowmelt can be monitored by jointly measuring snowpack parameters such as the snow water equivalent (SWE) or the amount of free liquid water content (LWC). However, continuous measurements of SWE and LWC are rare and difficult to be obtained. On the other hand, active microwave sensors such as the Synthetic Aperture Radar (SAR) mounted on board of satellites, are highly sensitive to LWC of the snowpack and can provide spatially distributed information with a high resolution. Moreover, with the introduction of Sentinel-1, SAR images are regularly acquired every 6 days over several places in the world. In this paper we analyze the correlation between the multi-temporal SAR backscattering and the snowmelt dynamics. We compared Sentinel-1 backscattering with snow properties derived from in situ observations and process-based snow modeling simulations for five alpine test sites in Italy, Germany and Switzerland considering two hydrological years. We found that the multi-temporal SAR measurements allow the identification of the three melting phases that characterize the melting process i.e., moistening, ripening and runoff. In detail, we found that the C-band SAR backscattering decreases as soon as the snow starts containing water, and that the backscattering increases as soon as SWE starts decreasing, which corresponds to the release of meltwater from the snowpack. We discuss the possible reasons of this increase, which are not directly correlated to the SWE decrease, but to the different snow conditions, which change the backscattering mechanisms. Finally, we show a spatially-distributed application of the identification of the runoff onset from SAR images for a mountain catchment, i.e., the Zugspitze catchment in Germany. Results allow to better understand the spatial and temporal evolution of melting dynamics in mountain regions. The presented investigation could have relevant applications for monitoring and predicting the snowmelt progress over large regions.

Carlo Marin et al.
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Short summary
In this paper, we use for the first time the Synthetic Aperture Radar (SAR) time series acquired by Sentinel-1 to monitor the snowmelt dynamics in alpine regions. We found that the multi-temporal SAR allow the identification of the three phases that characterize the melting process i.e., moistening, ripening and runoff in a spatial distributed way. We believe that he presented investigation could have relevant applications for monitoring and predicting the snowmelt progress over large regions.
In this paper, we use for the first time the Synthetic Aperture Radar (SAR) time series acquired...
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