A new forecasting model to anticipate episodes of red snow

A new forecasting model to anticipate episodes of red snow


A group of researchers from the Institute of Industrial Science of the University of Tokyo (Japan) has developed a new model capable of modeling and predicting episodes of red snow, a surprising phenomenon that occurs in regions with polar or alpine climates. during the melting season. The results were published on January 6 in the journal JGR Biogeosciences.

When spring approaches and the snow that fell during winter begins its seasonal melting, the piercing brilliance of white gold sometimes gives way to a strange red coloration. The immaculate landscape then takes on a more exotic, even Martian air. This phenomenon is due to the presence of microscopic algae that proliferate on the surface of the snow when it melts.

Algae with very specific consequences

By darkening the substrate, these photosynthetic organisms increase the amount of solar energy absorbed at the surface and therefore the rate at which the snowpack melts. If the red color is characteristic of the Chlamydomonas nivalis species, snow algae blooms can cause quite varied colorations, ranging from blood red to emerald green, passing through coppery orange.

Until now, it was not possible to predict operationally where and when these blooms would appear. The phenomenon was simply reported at the time it occurred. However, in a context of global warming and shrinking snow-covered surfaces, understanding and anticipating the evolution of these algae represents a growing scientific and economic challenge.

The need to take into account episodes of red snow

In order to fill these gaps, a team of Japanese researchers has developed the first numerical model capable of modeling snow algae blooms and predicting their appearance based on weather conditions and snowpack properties. “Our goal with this research was to try to predict the location and timing of red snow events and their effects on global snow cover,” said Yukihiko Onuma, lead author of the study.

Developed on the basis of previous work, the model incorporates new data on the development of these organisms that require the presence of liquid water, light and nutrients on the surface of the snow. In addition, it turns out that the duration of the thaw plays a strong role, because the quantity of algae increases exponentially over the days, provided however that no layer of fresh snow is deposited in the meantime. Finally, the duration of sunshine also intervenes by stimulating photosynthesis.

When the scientists compared their model to measurements from fifteen snow algae observation sites around the world, they found good agreement between the predictive calculations and the observations. “Our simulation of snow algal blooms could be used for global prediction of future red snow events that are likely to synchronize with global climate change,” the study notes in its summary.