|Development and validation of a one-dimensional snow-ice algae model against observations in Resolute Passage, Canadian Arctic Archipelago|Pogson, L.; Tremblay, B.; Lavoie, D.; Michel, C.; Vancoppenolle, M. (2011). Development and validation of a one-dimensional snow-ice algae model against observations in Resolute Passage, Canadian Arctic Archipelago. J. Geophys. Res. 116(C4). dx.doi.org/10.1029/2010JC006119
In: Journal of Geophysical Research. American Geophysical Union: Richmond. ISSN 0148-0227; e-ISSN 2156-2202, meer
|Auteurs|| || Top |
- Pogson, L.
- Tremblay, B.
- Lavoie, D.
- Michel, C.
- Vancoppenolle, M.
Ice algae are an important component of the carbon cycle in the Arctic. We investigate the dynamics of an ice algae bloom by coupling an ice algae-nutrient model with a multilayer sigma coordinate thermodynamic sea ice model. The model is tested with the simulation of an algal bloom at the base of first-year ice over the spring. Model output is compared with data from Barrow Strait in the Canadian Arctic Archipelago. Snow cover, through its influence on ice melt, is a dominant factor controlling the decline of the bloom in the model, a finding that supports past studies. The results show that under a higher snow cover (20 cm), biomass in the early stages of the algal bloom is less than expected from the observed data. This discrepancy is due to the severely light-limited algal growth, despite the close match between simulated and observed under-ice photosynthetically active radiation. This result raises issues of how photosynthetic parameters as well as radiative transfer is represented in one-dimensional ice models. This study also shows that for higher algal concentrations, when biomass is split over multiple layers rather than concentrated in one layer at the ice base, there is a reduction in algae accumulation, a result of self shading. In addition, experiments show a sensitivity of total biomass to the oceanic heat flux and ice layer thickness, both of which affect biomass loss at the ice base. Being able to accurately model physical conditions is essential before the seasonal dynamics of ice algae can be accurately modeled, and some recommendations for improvement are discussed.