Developing a Snow Algae Model to Reconstruct Blooming at the Global
Scale Using a Land Surface Model
Abstract
Snow algae are found from spring to summer on snowfields and glaciers
throughout the world. Their blooming darkens snow surfaces, reducing
snow surface albedo and accelerating melting. Uncertainties remain,
however, regarding the blooming season and global distribution of these
algae. To reproduce snow algal bloom temporal and spatial variability,
we improved an existing snow algae model using a land surface model
calibrated with a global atmospheric reanalysis dataset. Snowfall and
daylight length data for selected model locations were also
incorporated. To evaluate its performance, we used in situ
observational data from 15 polar to alpine area sites. The improvements
made in this study allowed the reconstruction of detailed snow algal
blooming reports from various locations worldwide, and the results
suggested that the major factors affecting the appearance of snow algal
blooming were the snow melting period duration and algal growth
interruption by new snow cover. We then incorporated the updated snow
algae model into a land surface model and performed a global simulation.
In this case, our simulation suggested that red snow could appear on
snowfields during the melting season but only in the absence of frequent
new snow falls, and if the snow cover persists long enough to allow
prolonged algal growth.