Articles | Volume 16, issue 12
https://doi.org/10.5194/tc-16-4811-2022
https://doi.org/10.5194/tc-16-4811-2022
Research article
 | 
02 Dec 2022
Research article |  | 02 Dec 2022

Stochastic analysis of micro-cone penetration tests in snow

Pyei Phyo Lin, Isabel Peinke, Pascal Hagenmuller, Matthias Wächter, M. Reza Rahimi Tabar, and Joachim Peinke

Model code and software

pplin13/Snow_RCodes: Stochastic analysis of micro-cone penetration tests in snow (v0.1.0) pplin13 https://doi.org/10.5281/zenodo.7358919

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Short summary
Characterization of layers of snowpack with highly resolved micro-cone penetration tests leads to detailed fluctuating signals. We used advanced stochastic analysis to differentiate snow types by interpreting the signals as a mixture of continuous and discontinuous random fluctuations. These two types of fluctuation seem to correspond to different mechanisms of drag force generation during the experiments. The proposed methodology provides new insights into the characterization of snow layers.