Preprints
https://doi.org/10.5194/tc-2021-108
https://doi.org/10.5194/tc-2021-108

  11 May 2021

11 May 2021

Review status: a revised version of this preprint was accepted for the journal TC and is expected to appear here in due course.

Effect of snowfall on changes in relative seismic velocity measured by ambient noise correlation

Antoine Guillemot1, Alec van Herwijnen2, Eric Larose1, Stephanie Mayer2, and Laurent Baillet1 Antoine Guillemot et al.
  • 1Laboratoire ISTerre, Univ. Grenoble Alpes, CNRS, Univ. Savoie Mont Blanc, 38000 Grenoble, France
  • 2WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland

Abstract. In mountainous, cold temperate and polar sites, the presence of a snow cover can affect relative seismic velocity changes (dV/V) derived from ambient noise correlation, but this relation is relatively poorly documented and ambiguous. In this study, we analyzed raw seismic recordings from a snowy flat field site located above Davos (Switzerland), during one entire winter season (from December 2018 to June 2019). We identified three snowfall events with a substantial response of dV/V measurements (drops of several percent between 15 and 25 Hz), suggesting a detectable change in elastic properties of the medium due to the additional fresh snow. To better interpret the measurements, we used a physical model to compute frequency dependent changes in the Rayleigh wave velocity computed before and after the events. Elastic parameters of the ground subsurface were obtained from a seismic refraction survey, whereas snow cover properties were obtained from the snow cover model SNOWPACK. The decrease in dV/V due to a snowfall were well reproduced, with the same order of magnitude as observed values, confirming the importance of the effect of fresh and dry snow on seismic measurements. We also observed a decrease in dV/V with snowmelt periods, but we were not able to reproduce those changes with our model. Overall, our results highlight the effect of the snowcover on seismic measurements, but more work is needed to accurately model this response, in particular for the presence of liquid water in the snowpack.

Antoine Guillemot et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2021-108', Anonymous Referee #1, 17 Jun 2021
    • AC1: 'Reply on RC1', Antoine Guillemot, 23 Aug 2021
  • RC2: 'Comment on tc-2021-108', Anonymous Referee #2, 21 Jun 2021
    • AC2: 'Reply on RC2', Antoine Guillemot, 23 Aug 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2021-108', Anonymous Referee #1, 17 Jun 2021
    • AC1: 'Reply on RC1', Antoine Guillemot, 23 Aug 2021
  • RC2: 'Comment on tc-2021-108', Anonymous Referee #2, 21 Jun 2021
    • AC2: 'Reply on RC2', Antoine Guillemot, 23 Aug 2021

Antoine Guillemot et al.

Antoine Guillemot et al.

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Short summary
Ambient noise correlation is a broadly used method in seismology to monitor tiny changes in subsurface properties. Some environmental forcings may influence this method, including snow. During one winter season, we studied this snow effect on seismic velocity of the medium, recorded by a pair of seismic sensors. We detected and modeled a measurable effect during early snowfalls : the new fresh snow layer modifies rigidity and density of the medium, thus decreasing the recorded seismic velocity.