EGU23-3146, updated on 22 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Numerical modeling of biological processes on snow and ice surfaces on the Greenland Ice Sheet

Yukihiko Onuma1, Masashi Niwano2, Rigen Shimada3, and Nozomu Takeuchi4
Yukihiko Onuma et al.
  • 1Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, Japan (
  • 2Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan (
  • 3Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, Japan (
  • 4Graduate School of Science, Chiba University, Chiba, Japan (

Biological processes on snow and glacier surfaces in the Arctic region play a key role causing albedo reduction called as “Bio-albedo effect” due to blooms of snow and glacier phototrophs. Because the bio-albedo effect varies temporally and spatially due to their biological properties including growth, death and migration, the biological processes need to be separated from accumulation processes of the other impurities such as aeolian mineral dust and black carbon. In addition, different processes causing the bio-albedo effect, which are known as red snow, dark ice and cryoconite holes, are observed in the Arctic snowpacks and glaciers. To understand the bio-albedo effect quantitatively, a numerical model to reproduce such biological processes as well as a physically based albedo model should be established. We recently established several numerical models: the snow algae model to simulate red snow phenomena caused by snow algal blooms (Onuma et al., 2020; 2022a), the glacier algae model to simulate dark ice phenomena caused by glacier algal blooms (Onuma et al., 2022b) and the cryoconite hole model to simulate vertical dynamics of cryoconite holes (Onuma et al., In prep.). In this study, we simulate spatio-temporal changes in algal abundance and bio-albedo effect in Greenland Ice Sheet since 2000 using regional climate or land surface models coupling with the established models. The simulated spatio-temporal changes are evaluated using a polar-orbit satellite, Global Change Observation Mission for Climate (GCOM-C) which carries an optical sensor capable of multi-channel observation at wavelengths from near-UV to thermal infrared wavelengths (380nm to 12µm). In addition, we also use GCOM-W satellite with a microwave sensor to discuss relationship between snow/ice surface melt periods and algal blooms. The detailed discussion will be presented at the meeting.

[1] Y. Onuma, N. Takeuchi, S. Tanaka, N. Nagatsuka, M. Niwano and T. Aoki, Physically based model of the contribution of red snow algal cells to temporal changes in albedo in northwest Greenland. The Cryosphere, 14, 2087-2101. doi:10. 5194/tc-14-2087-2020 (2020)

[2] Y. Onuma, K. Yoshimura and N. Takeuchi, Global simulation of snow algal blooming by coupling a land surface and newly developed snow algae models, Journal of Geophysical Research: Biogeosciences, 127 (2), e2021JG006339. doi:10.1029/2021JG006339 (2022a).

[3] Y. Onuma, N. Takeuchi, J. Uetake, M. Niwano, S. Tanaka, N. Nagatsuka and T. Aoki, Modeling seasonal growth of phototrophs on bare ice on the Qaanaaq Ice Cap, northwestern Greenland. Journal of Glaciology, 1-13. doi:10.1017/jog.2022.76 (2022b)

How to cite: Onuma, Y., Niwano, M., Shimada, R., and Takeuchi, N.: Numerical modeling of biological processes on snow and ice surfaces on the Greenland Ice Sheet, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3146,, 2023.