We collected weekly measurements of snow microstructural properties over two winters at Col de Porte in the French Alps, a relatively warm alpine site, using complementary techniques including X-ray tomography, the SnowMicroPen, and optical instruments. The dataset captures snowpack evolution at fine vertical resolution and is a valuable resource for snow model evaluation and instrument comparisons. It also provides guidance for future snow monitoring campaigns in warm mountain environments.

This work aims to pave the way towards an objective description of snow microstructure in snowpack models. We investigate the temporal evolution of several grain-size and grain-shape descriptors under a large range of dry snow metamorphism scenarios. Our results reveal that the evolution of several geometrical descriptors is more diverse than generally assumed, and that future models could benefit from representing multiple grain-size and shape descriptors.

A quasi-static model is used to simulate the distribution of liquid water in the pore space of snow for various water contents. Liquid water is gradually introduced and then removed from a set of 34 3D tomography snow images by capillarity during wetting and drying simulations. This work constitutes an exploratory numerical work (i) to study the water retention curves and (ii) the effective transport properties of wet snow and how they are influenced by the water distribution at the pore scale.

Snow microstructure undergoes constant shape transformations known as snow metamorphism. Observing first-hand snow metamorphism is key to improving the modelling of these transformations. In this work, we monitor snow microstructure evolution during metamorphism by X-ray tomography. We provide a data set at high spatial and temporal resolution of 3D images of snow microstructure evolving through a wide range of experimental conditions, along with videos showing these transformations.

Four different macroscopic heat and mass transfer models have been derived for a large range of condensation coefficient values by an upscaling method. A comprehensive evaluation of the models is presented based on experimental datasets and numerical examples. The models reproduce the trend of experimental temperature and density profiles but underestimate the magnitude of the processes. Possible causes of these discrepancies and potential improvements for the models are suggested.