Reply on RC2

Abstract

Cone penetration tests have long been used to characterize the snowpack stratigraphy. With the development of sophisticated digital penetrometers such as the Snow MicroPenetrometer, vertical profiles of snow hardness can now be measured at a spatial resolution of a few microns. At this high vertical resolution and by using small penetrometer tips, more and more details of the penetration process get resolved, leading to much more stochastic signals. An accurate interpretation of these signals regarding snow characteristics requires employing advanced data analysis. Here, the failure of ice connections and the pushing aside of separated snow grains during cone penetration lead to a combination of a) diffusive noise, as in Brownian motion, and b) jumpy noise, as proposed by previous dedicated inversion methods. The determination of the Kramers-Moyal coefficients allows differentiating between diffusive and jumpy behaviors and determining the functional resistance dependencies of these stochastic contributions. We show how different snow types can be characterized by this combination of highly-resolved measurements and data analysis methods. In particular, we show that denser snow structures exhibited a more collective diffusive behavior supposedly related to the pushing aside of separated snow grains. On lighter structures with larger pore space, the measured hardness profile appeared to be characterized by stronger jump noise probably related to breaking single cohesive bonds. The proposed methodology provides new insights into the characterization of the snowpack stratigraphy with cone penetration tests.