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

Scientists from OSUG federation (Institut des géosciences de l’environnement of Grenoble [1] and the Centre d’études de la neige [2]) 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.

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, among other sites, at the European Synchrotron ESRF’s ID19 beamline, 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.

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.

References

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

This article was initially published by UGA.

Updated on 21 November 2023