Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: Empirical and model results. Issue 7 (11th July 2017) - Duarte, Pedro; Meyer, Amelie; Olsen, Lasse M.; Kauko, Hanna M.; Assmy, Philipp; Rösel, Anja; Itkin, Polona; Hudson, Stephen R.; Granskog, Mats A.; Gerland, Sebastian; Sundfjord, Arild; Steen, Harald; et al.
Abstract: Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and biogeochemical properties at time scales of a few weeks and to use the model to analyze ice algal bloom dynamics in different types of ice. Ocean and atmospheric forcing data and observations of the evolution of the sea ice properties collected from 18 April to 4 June 2015, during the Norwegian young sea ICE expedition, were used to test the CICE model. Our results show the following: (i) model performance is reasonable for sea ice thickness and bulk salinity; good for vertically resolved temperature, vertically averaged Chl a concentrations, and standing stocks; and poor for vertically resolved Chl a concentrations. (ii) Improving current knowledge about nutrient exchanges, ice algal recruitment, and motion is critical to improve sea ice biogeochemical modeling. (iii) Ice algae may bloom despite some degree of basal melting. (iv) Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution. (v) Different ice algal bloom and net primary production (NPP) patterns were identified in the ice types studied, suggesting that ice algal maximal growth rates will increase, while sea ice vertically integrated NPP and biomass will decrease as a result of the predictable increase in the area covered by refrozen leads in the Arctic Ocean. Plain Language Summary: Important changes in the ice regime of the Arctic Ocean have occurred over the last decades with reductions in the summer sea ice extend and thickness. These changes and the importance of sea ice to the global climate system, the ecology of the Arctic Ocean, and the global biogeochemical cycles have justified the development of mathematical models to forecast sea ice evolution regarding its physical, chemical, and biological properties. In this work we test one such model—the Los Alamos Sea Ice Model—with data collected during the Norwegian young sea ICE expedition. Our results show that the model is capable of predicting accurately sea ice thickness, temperature, and salinity during a period of several weeks. However, it is not so accurate for biological variables. We suggest some aspects that may be investigated in trying to improve model performance, with emphasis on a better understanding of the behavior of ice algae that have an overwhelming importance for the Arctic marine food webs. Our results point to future changes in Arctic sea ice primary production associated with a more dynamic ice cover and a higher frequency of refrozen leads. Key Points: Sea ice physical variables can be accurately simulated at time scales of 2 months using a 1‐D vertically resolved state of the art model Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution The predictable increase in the area of refrozen leads may have a negative effect on vertically integrated ice algal primary production