Simulation parameters and outputs for a rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism

DOI

In the associated study [1], two time-lapse temperature gradient metamorphism series of three-dimensional micro-computed tomography images of snow (obtained by [2]) have been used to model the decrease of specific surface area (SSA) over time based on the pore-scale physics. We conducted finite element simulations of one-way coupled heat and mass diffusion in order to estimation the spatial pattern of water vapor deposition and sublimation, which controls the evolution of the SSA over time. We notably studied the influence of the condensation coefficient, a key but poorly constrained physical parameter.

This dataset provides the parameters used for the mesh generation and the finite element simulations. It also includes the ice fraction, specific surface area per unit volume and surface average of mean curvature and vapor field obtained as outputs from the mesh process and the simulations.

[1]: Braun, A., Fourteau, K., and Löwe, H.: A rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1947, 2023. [2]: Pinzer, B. R., Schneebeli, M., and Kaempfer, T. U.: Vapor flux and recrystallization during dry snow metamorphism under a steady temperature gradient as observed by time-lapse micro-tomography, The Cryosphere, 6, 1141–1155, https://doi.org/10.5194/tc-6-1141-2012, 2012.

Identifier
DOI https://doi.org/10.16904/envidat.492
Metadata Access https://www.envidat.ch/api/action/package_show?id=53044b16-6ecb-41dc-a5dd-12ac261469b1
Provenance
Creator Anna, Braun, 0000-0002-2357-9452; Kévin, Fourteau, 0000-0002-9905-2446; Henning, Löwe, 0000-0001-7515-6809
Publisher EnviDat
Publication Year 2024
Funding Reference Swiss National Science Fondation, 200020_178831
Rights odc-odbl; ODbL with Database Contents License (DbCL)
OpenAccess true
Contact envidat(at)wsl.ch
Representation
Resource Type Dataset
Discipline Environmental Sciences
Spatial Coverage (5.956W, 45.818S, 10.492E, 47.808N)
Temporal Coverage Begin 2022-01-01T00:00:00Z
Temporal Coverage End 2023-12-31T00:00:00Z