| 31 Aug 2026
Characterizing snow grain size and shape evolution across 20 scenarios of dry snow metamorphism
Abstract. Snow microstructure evolves continuously during dry snow metamorphism, governing many effective physical properties of snow. Accurately representing this evolution in snowpack models requires objective descriptors of grain size and grain shape together with reliable temporal evolution laws. However, the evolution of snow microstructure has not been systematically characterized over the full range of dry snow metamorphism conditions. Here, we investigate the temporal evolution of several grain-size and grain-shape descriptors during dry snow metamorphism using a unique 4D X-ray tomography dataset comprising 20 experiments covering a broad range of temperatures, temperature gradients, and initial snow types. We analyze specific surface area (SSA), optical and microwave grain sizes, correlation length, structural anisotropy, three curvature-based grain-shape descriptors, as well as the full chord length and mean curvature distributions. Our results reveal that SSA evolution is far more diverse than generally assumed, including transient increases under strong temperature gradients. Optical and microwave grain-size descriptors often differ in both absolute value and temporal evolution, suggesting that snowpack models should predict both rather than a single grain-size descriptor. Vertical structural anisotropy does not systematically develop under temperature gradients, contrary to the common assumption. Overall, the initial snow microstructure strongly controls grain-shape evolution and, to a lesser extent, grain-size evolution, while both are also influenced by temperature gradient and mean temperature. These results provide new experimental constraints for developing and evaluating snow microstructure representations and temporal evolution laws in snowpack models. Future snowpack models could benefit from predicting the full chord length and mean curvature distributions rather than only scalar descriptors.
General comments
The paper builds on a recent publication by the same main author (Earth Syst. Sci. Data, 18, 2875–2889, 2026 https://doi.org/10.5194/essd-18-2875-2026) that presented an extensive set of time-laps micro-CT images of 20 snow metamorphism experiments spanning a range of initial snow types, temperatures and temperature gradients. Here, several shape descriptors are introduced, computed, and their evolution over time is analyzed in function of the experimental parameters. The results are put into perspective with existing work and suggestions on how shape descriptors might be used in future snowpack models are made.
While subsets of shape descriptors have been presented for similar experiments before, the paper makes significant progress through its completeness, both regarding the experimental and the shape descriptor broadness. For the latter, the combination of scalar descriptors and statistical distributions seems particularly promising, albeit the approach is not completely new.
The paper is generally well written and the approaches and results are nicely presented. Clarity could be improved for a few statements and the discussion, namely when comparing the results with other publications, could benefit by considering the specific remarks provided in the first part of attached pdf-file. For minor suggestions and technical corrections, see also the annotated paper preview in the second part of the pdf.
I suggest the paper be revised accordingly before accepting it for publication.