Global Simulation of Snow Algal Blooming by Coupling a Land Surface and Newly Developed Snow Algae Models

Abstract

AbstractSnow 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 geographical variability, we improved an existing snow algae model using a land surface model calibrated with a reanalysis dataset of the global atmosphere. 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 snowfalls, and if the snow cover persists long enough to allow prolonged algal growth. This simulation has the potential to be used for global prediction of future red snow phenomena, which are likely to synchronize with global climate change.