Snow is a ubiquitous material in the Earth Cryosphere, and its contribution to the climatic system, at all scales, is strong.
Physical properties of snow are largely determined by its microstructure. The general term microstructure thereby contains a crystallographic aspect, covering the c-axis orientational disorder, and a geometrical aspect, covering the porous-structural disorder. The crystallographic aspect is of key relevance to understand mechanical behavior and densification of snow in view of polar climatology. The geometrical aspect constitutes a key link to in-situ and remote sensing observation methods that probe the microstructure mainly by electromagnetic means.
Methods to predict snow avalanches, to estimate the snow cover on Earth, to measure its temperature, to simulate snowpack evolution, etc., are increasing their reliability together with their complexity. By doing so, to account for an accurate representation of snow, microstructure is becoming a key challenge in the different related research fields.
Snow microstructure can be characterized by various parameters regarding the field of application. For instance, the Specific Surface Area (SSA) seems appropriate when dealing with the characterization of albedo, the optic diameter can be more adapted to the interpretation of remote sensing data, and the full texture can be required when trying to estimate the mechanical response.
This Research Topic therefore aims at gathering various contributions with a common interest in snow microstructure characterization, evolution, modeling, etc., in order to provide a “state of the art” in this domain.
We welcome studies that address Snow Microstructure with a focus on:
- New proxies of snow microstructure;
- Experimental characterization of snow microstructure and its evolution in field and lab conditions;
- Modelling of snow microstructure evolution and numerical homogenization of snow physical properties; and
- Impact of snow microstructure on alpine and arctic processes under various time and spatial scales.
Snow is a ubiquitous material in the Earth Cryosphere, and its contribution to the climatic system, at all scales, is strong.
Physical properties of snow are largely determined by its microstructure. The general term microstructure thereby contains a crystallographic aspect, covering the c-axis orientational disorder, and a geometrical aspect, covering the porous-structural disorder. The crystallographic aspect is of key relevance to understand mechanical behavior and densification of snow in view of polar climatology. The geometrical aspect constitutes a key link to in-situ and remote sensing observation methods that probe the microstructure mainly by electromagnetic means.
Methods to predict snow avalanches, to estimate the snow cover on Earth, to measure its temperature, to simulate snowpack evolution, etc., are increasing their reliability together with their complexity. By doing so, to account for an accurate representation of snow, microstructure is becoming a key challenge in the different related research fields.
Snow microstructure can be characterized by various parameters regarding the field of application. For instance, the Specific Surface Area (SSA) seems appropriate when dealing with the characterization of albedo, the optic diameter can be more adapted to the interpretation of remote sensing data, and the full texture can be required when trying to estimate the mechanical response.
This Research Topic therefore aims at gathering various contributions with a common interest in snow microstructure characterization, evolution, modeling, etc., in order to provide a “state of the art” in this domain.
We welcome studies that address Snow Microstructure with a focus on:
- New proxies of snow microstructure;
- Experimental characterization of snow microstructure and its evolution in field and lab conditions;
- Modelling of snow microstructure evolution and numerical homogenization of snow physical properties; and
- Impact of snow microstructure on alpine and arctic processes under various time and spatial scales.