Articles | Volume 16, issue 12
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


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-111', Adrian McCallum, 21 Jul 2022
    • AC1: 'Reply on RC1', Pyei Phyo Lin, 06 Sep 2022
  • RC2: 'Comment on tc-2022-111', Henning Löwe, 12 Aug 2022
    • AC2: 'Reply on RC2', Pyei Phyo Lin, 06 Sep 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by editor) (13 Oct 2022) by Melody Sandells
AR by Pyei Phyo Lin on behalf of the Authors (17 Oct 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish subject to technical corrections (03 Nov 2022) by Melody Sandells
AR by Pyei Phyo Lin on behalf of the Authors (07 Nov 2022)  Author's response    Manuscript
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.