[A-CC25] Glaciology

[ACC25-09] Evaluation of snow algae distribution on Mt. Tateyama in 2022 using satellites.

*Hatakeyama Shiori¹, Masahiro Hori², Konosuke Sugiura², Yukihiko Onuma³ (1.University of Toyama, Graduate School of Science and Engineering, 2. University of Toyama, School of Sustainable Design, 3.Japan Aerospace Exploration Agency)

Keywords:snow algae, remote sensing, red snow

Snow algae inhabit the melting snow surface, and their blooms cause a decrease of the albedo of snow surface, which in turn accelerates the melting of glaciers, ice sheets, and snow cover. Around Mt. Tateyama, red snow caused by the growth of snow algae is reported in field study every year during the snowmelt season. However, few analyses of red snow distribution have been conducted using satellite imagery in this area. There are three reasons for this; first, the narrow distribution of red snow, second, shadows caused by steep mountain slope and the last, the mixing of other elements covering the snow surface (yellow snow, sulfur snow, black snow, and white snow). This study evaluates the regional red snow distribution around Mt. Tateyama, by analyzing satellite images with Spectral Mixing Analysis (SMA) method. We analyzed bottom of atmosphere reflectance taken from PlanetScope with a resolution of 3.7 meters. The results showed that the red snow covers were widely detected at Raichozawa and the back side of Tateyamaso (a mountain cottage) in June and July of 2022. The analysis results were almost consistent with the results of the field studies. The figure shows the distribution of red snow around Tateyama in June 2022 based on the SMA method. The red boxes in the live camera image correspond to the red boxes in the analysis results. We also conducted a sensitivity analysis with the SMA method by replacing the spectral reflectance of red snow, which is used in the SMA method, with different spectra having various R/G ratio (a measure of the chlorophyll-a and carotenoid amount) without changing the spectral reflectance of other snow elements. As a result, the retrieved arial percentage of red snow was found to be larger (smaller) when using reflectance with low (high) amount of chlorophyll-a and carotenoid present. In the future, we would like to verify that the amount of net chlorophyll-a and carotenoid present in a pixel does not depend on the spectral reflectance of red snow, and by considering the R/G ratio, which is closely related to the number of algal cells, we would like to estimate the amount of red snow algae (the number of cells) within a pixel using the SMA method.