[A-CC26] Glaciology

[ACC26-08] Regional simulation of glacier algal growth and evaluation by satellite observations on Qaanaaq Ice Cap, northwestern Greenland

*Yukihiko Onuma¹, Giacomo Traversa² (1.Japan Aerospace Exploration Agency, 2.National Research Council of Italy)

Keywords:Snow and glacier algae, Glacier, Numerical modeling, Satellite observation

Biological processes on snow and glacier surfaces in the Cryosphere play a key role in causing albedo reduction known as “Glacier surface darkening” due to blooms of snow and glacier phototrophs. Because the darkening phenomenon varies temporally and spatially due to their biological properties including growth, death, and migration, the phenomenon is caused by various biological processes, separated from accumulation processes of the other impurities such as aeolian mineral dust and black carbon. To reveal the processes of glacier surface darkening, many Japanese glaciologists have conducted field observations of the Qaanaaq Ice Cap in northwestern Greenland in the framework of Japanese Arctic research projects such as Arctic Challenge for Sustainability Ⅱ (ArCS Ⅱ). Many previous studies have revealed many processes of glacier surface darkening and their effects on glacier melting. However, these results were mainly obtained from field observations at the ice cap. In addition, although a numerical model has been developed to simulate blooms of snow algae at the global scale with over ten kilometers, it has not been applied to regional scales such as glaciers, which require a resolution of several tens of meters. Therefore, the process of glacier surface darkening in the ice cap has not been spatially evaluated yet. In this study, numerical simulation using the global snow algae model Bio-MATSIRO was conducted with 30 m spatial resolution in the Qaanaaq Ice Cap. To conduct the high-resolution simulation, the topographic information, such as elevation, in the ice cap were obtained as boundary conditions for the simulation from ArcticDEM Mosaic and Sentinel-2 Level-2A images in the ice cap. The meteorological conditions as model input data were derived by downscaling atmospheric reanalysis data ERA5-Land to 30 m using the obtained topographic information. Using the topological and atmospheric conditions, we simulated spatio-temporal changes in the abundance of glacier algae Ancylonema nordenskioldii in the Qaanaaq Ice Cap during the summer of 2023. The simulated algal abundance will be validated using data from field observations in August 2023 and satellite observations by PRISMA and EnMAP, installed with hyperspectral sensors. The results will be introduced at the meeting because this research will be conducted mainly during the period of February 1^st to March 31^st 2024 in the framework of the ArCS II International Early Career Researchers Program.