When a photon hits the snow, what does it see ?

Scientists from the Institut des géosciences de l’environnement of Grenoble (IGE – CNRS/Inrae/IRD/UGA/Grenoble INP-UGA) and the Centre d’études de la neige (CEN – CNRM/Météo-France/CNRS) have studied the interactions between sunlight and snow at the micrometer scale, which determines the snow ‘whiteness’ and consequently has a crucial impact in the Earth’s climate. In an article published the 7 July 2023 in Nature Communications, these scientists have defined and quantified a new concept : the optical shape of snow. The impact of this breakthrough is important for improving the accuracy of climate models.

 

Once deposited on the ground, snow is a material composed of air and ice crystals, whose shape and arrangement vary greatly at the micrometer scale. This is known as the microstructure of snow (Figure 1). This "skeleton" of ice and air governs the propagation of light within the snowpack through optical phenomena such as refraction and internal reflections in the ice phase. However, despite its extreme complexity and irregularity, natural snow is still represented in a simplistic manner in almost all optical models, including those implemented in climate models. These models typically depict snow as a collection of ice particles with perfect geometric shapes, mainly spheres. Among the many implications for the energy balance of snow, this simplification leads to significant uncertainties in climate modeling, with potential impacts of up to 1.2°C on global air temperature.

This is what fresh snow looks like at the micrometer scale. We call this arrangement of ice and air snow microstructure

In this new study, the authors have accurately simulated the light propagation in a collection of 3D images of the snow microstructure obtained by X-ray tomography, using a ray-tracing model.
Their results show that for sunlight, snow is not equivalent to spheres or other simple shapes, contrary to what is currently done in many snow optical models (Figure 2). For the first time, accurate values for the optical shape of snow have been deduced, values hat can be used directly in climate models, instead of the sphericity assumption. According to their estimate, the uncertainties related to the optical shape of snow in these models would be divided by 3. At the same time, these results show that, despite the very different microstructures of snow, the distance travelled by sunlight in ice is, on average, always the same. In other words, snow is fundamentally ergodic.

The optical shape of snow, defined and quantified by two parameters : the absorption enhancement parameter B and the geometric asymmetry parameter gG. The take-home message here : snow covers an area of the figure totally different from that covered by simple geometric shapes.

This work represents a paradigm shift in the way snow is represented in optical models. Beyond climate simulations, these results can be beneficial wherever snow optics are important, from snow photochemistry to remote sensing algorithms.

Reference

Unraveling the optical shape of snow
Alvaro Robledano, Ghislain Picard, Marie Dumont, Frédéric Flin, Laurent Arnaud et Quentin Libois.
Nature Communications, 7 juillet 2023

Scientific contact

– Alvaro Robledano, PhD fellow at IGE / OSUG

This article was initially published by UGA