What controls primary production in the Arctic Ocean? Results from an intercomparison of five general circulation models with biogeochemistry

Abstract

[1] As a part of Arctic Ocean Intercomparison Project, results from five coupled physical and biological ocean models were compared for the Arctic domain, defined here as north of 66.6°N. The global and regional (Arctic Ocean (AO)-only) models included in the intercomparison show similar features in terms of the distribution of present-day water column-integrated primary production and are broadly in agreement with in situ and satellite-derived data. However, the physical factors controlling this distribution differ between the models. The intercomparison between models finds substantial variation in the depth of winter mixing, one of the main mechanisms supplying inorganic nutrients over the majority of the AO. Although all models manifest similar level of light limitation owing to general agreement on the ice distribution, the amount of nutrients available for plankton utilization is different between models. Thus the participating models disagree on a fundamental question: which factor, light or nutrients, controls present-day Arctic productivity. These differences between models may not be detrimental in determining present-day AO primary production since both light and nutrient limitation are tightly coupled to the presence of sea ice. Essentially, as long as at least one of the two limiting factors is reproduced correctly, simulated total primary production will be close to that observed. However, if the retreat of Arctic sea ice continues into the future as expected, a decoupling between sea ice and nutrient limitation will occur, and the predictive capabilities of the models may potentially diminish unless more effort is spent on verifying the mechanisms of nutrient supply. Our study once again emphasizes the importance of a realistic representation of ocean physics, in particular vertical mixing, as a necessary foundation for ecosystem modeling and predictions.

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

“…This observation is not necessarily new [Popova et al, 2012;Vancoppenolle et al, 2013], but one should be cautious when interpreting this result because these three simulated parameters were positively biased (i.e., means usually overestimated) (Figures 8 and 9). For example, the simulated, mean surface NO 3 was vastly overestimated, especially in the lowproductivity, nutrient-depleted interior regions of the Arctic Ocean, i.e., the Beaufort Sea and the central Arctic Basin where model and in situ iNPP agreed best (Figures 6b and 6e; Table 4).…”

“…Earlier intercomparison studies for the Arctic Ocean emphasized the importance of a realistic representation of ocean physics [Popova et al 2012], in particular vertical mixing and nutrient concentration, for accurate Arctic Ocean ecosystem modeling. Five BOGCMs manifested similar levels of light limitation owing to a general agreement on the simulated sea ice distribution [Popova et al 2012]. On the other hand, the ESMs participating in the Vancoppenolle et al [2013] study showed that Arctic phytoplankton growth was more limited by light related to sea ice than by nutrient availability for the period of 1980-1999.…”

“…Popova et al [2012] and Vancoppenolle et al [2013] reported the results from various BOGCMs and Earth System Models (ESMs) that were compared for the Arctic domain against satellite-derived NPP albeit with known issues. These latter two studies found reasonable agreement on the main features of pan-Arctic annual NPP and highlighted the disagreement among the models with respect to nutrient availability and source, as well as which factor, light or nutrients, controls the present-day and future Arctic Ocean NPP.…”

Role of sea ice in global biogeochemical cycles: emerging views and challenges

“…Seawater nutrient concentrations feature strong regional variations, but in the Arctic, those are not well constrained: the World Ocean Atlas Climatology [Garcia et al, 2006] has almost no data coverage in the Arctic Basin, and riverine inputs of nutrients are poorly understood [Popova et al, 2012]. Some general features can however be found in the literature.…”

“…The ice algae model of Jin et al [2006] has been included into a large-scale ocean modelling system running at regional scales [Deal et al, 2011;Jin et al, 2012], while an N-P-Z 3D ice-ocean model has been applied to the Hudson Bay [Sibert et al, 2011]. These studies indicate a moderate role for ice algae in the Arctic carbon cycle, reaching 15% of the total Arctic production [Deal et al, 2011].…”