CSIB v1 (Canadian Sea-ice Biogeochemistry): a sea-ice biogeochemical model for the NEMO community ocean modelling framework

• Published in: Geoscientific Model Development
• Main Authors: Hayashida, H, Christian, JR, Holdsworth, AM, Hu, X, Monahan, AH, Mortenson, E, Myers, PG, Riche, OGJ, Sou, T, Steiner, NS
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus GmbH 2019
• Subjects: arctic; biogeochemistry; numerical modelling; sea ice; primary production; dimethylsulfide; Arctic; ice algae; Sea ice
• Online Access: https://eprints.utas.edu.au/42065/; https://eprints.utas.edu.au/42065/1/137169%20-%20CSIB%20v1%20%28Canadian%20Sea-ice%20Biogeochemistry%29.pdf; https://eprints.utas.edu.au/42065/2/137169%20-%20supplement.pdf

Process-based numerical models are a useful tool for studying marine ecosystems and associated biogeochemical processes in ice-covered regions where observations are scarce. To this end, CSIB v1 (Canadian Sea-ice Biogeochemistry version 1), a new sea-ice biogeochemical model, has been developed and embedded into the Nucleus for European Modelling of the Ocean (NEMO) modelling system. This model consists of a three-compartment (ice algae, nitrate, and ammonium) sea-ice ecosystem and a two-compartment (dimethylsulfoniopropionate and dimethylsulfide) sea-ice sulfur cycle which are coupled to pelagic ecosystem and sulfur-cycle models at the sea-ice–ocean interface. In addition to biological and chemical sources and sinks, the model simulates the horizontal transport of biogeochemical state variables within sea ice through a one-way coupling to a dynamic-thermodynamic sea-ice model (LIM2; the Louvain-la-Neuve Sea Ice Model version 2). The model results for 1979 (after a decadal spin-up) are presented and compared to observations and previous model studies for a brief discussion on the model performance. Furthermore, this paper provides discussion on technical aspects of implementing the sea-ice biogeochemistry and assesses the model sensitivity to (1) the temporal resolution of the snowfall forcing data, (2) the representation of light penetration through snow, (3) the horizontal transport of sea-ice biogeochemical state variables, and (4) light attenuation by ice algae. The sea-ice biogeochemical model has been developed within the generic framework of NEMO to facilitate its use within different configurations and domains, and can be adapted for use with other NEMO-based sub-models such as LIM3 (the Louvain-la-Neuve Sea Ice Model version 3) and PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies).