日本地球惑星科学連合2022年大会

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[J] ポスター発表

セッション記号 A (大気水圏科学) » A-CG 大気海洋・環境科学複合領域・一般

[A-CG43] 北極域の科学

2022年5月29日(日) 11:00 〜 13:00 オンラインポスターZoom会場 (11) (Ch.11)

コンビーナ:Ono Jun(JAMSTEC Japan Agency for Marine-Earth Science and Technology)、コンビーナ:両角 友喜(北海道大学 大学院農学研究院)、島田 利元(宇宙航空研究開発機構)、コンビーナ:堀 正岳(東京大学大気海洋研究所)、座長:小野 純(国立研究開発法人 海洋研究開発機構)

11:00 〜 13:00

[ACG43-P04] Red snow distribubtion calcurated with a snow algae model on Harding Icefield in Alaska

*Nozomu Takeuchi1、Kaito Wada1 (1.Chiba University)

キーワード:snow algae, glacier, Alaska

Red snow is colored snow surface caused by blooms of photosynthetic microbes (snow algae) and occurs commonly on melting snowpacks and glaciers worldwide. As colored snow melt faster due to lower albedo, it is important to simulate their spatial and temporal variations on snowpacks or glaciers. A snow algae model is a simple numerical model to calculate snow algal growth on snow surface. In this study, we simulated red snow distribution on Harding Ice Field in Alaska using a snow algal model, local air temperature record, and digital elevation model and evaluated it with those obtained from satellite images. The model calculation revealed that the red snow surface appeared at the terminus area of outlet glaciers early summer, then expanded their distribution in the central part of the ice field. As compared with the red snow distribution derived from satellite images, the algal growth calculated by the model was slightly behind, suggesting that some of parameters of the model need to be adapted to this ice field.