Large‐scale modeling of primary production and ice algal biomass within arctic sea ice in 1992

Deal, Clara; Jin, Meibing; Elliott, Scott; Hunke, Elizabeth; Maltrud, Mathew; Jeffery, Nicole

doi:10.1029/2010jc006409

Cited by 69 publications

(113 citation statements)

References 40 publications

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“…In contrast, the nutrient control on ice algal production is less pronounced; although high ice algal GPP usually concides with high surface seawater nitrate, it is also present in a few areas where the nitrate levels are relatively low (Baffin Bay and Chukchi Sea; Figure 8b). Overall, ice algal production is mostly confined to shelf regions (water depth <100 m; Figure 3), consistent with previous model studies (Deal et al, 2011;Dupont, 2012;Jin et al, 2012Jin et al, , 2018 There are a few noteworthy similarities and differences in the spatial variability in modelled ice algal annual production between the present study and previous model studies. All studies show a moderate-to-high level of ice algal production in Baffin Bay.…”

Section: Spatial Variabilitysupporting

confidence: 91%

CSIB v1: a sea-ice biogeochemical model for the NEMO community ocean modelling framework

Hayashida

Christian

Holdsworth

et al. 2018

Preprint

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Abstract. Numerical models are a useful tool for studying marine ecosystems and associated biogeochemical processes in icecovered regions where observations are scarce. To this end, CSIB v1 (Canadian Sea-ice Biogeochemistry version 1), a new seaice 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 twocompartment (dimethylsulfoniopropionate and dimethylsulfide) sea-ice sulfur cycle which are coupled to pelagic ecosystem 5 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 dynamicthermodynamic sea-ice model (LIM2). This paper describes technical aspects of implementing sea-ice biogeochemistry into NEMO and provides discussion on the results of several model experiments. Results of the reference simulation were evaluated by comparing the model outputs to observations and previous modelling studies. Additional simulations were conducted to 10 assess the model sensitivity to 1) the temporal resolution of the snowfall forcing data, 2) the representation of light penetration through snow, 3) advective and eddy-diffusive 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 submodels such as LIM3 and PISCES.

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Section: Spatial Variabilitysupporting

confidence: 91%

CSIB v1: a sea-ice biogeochemical model for the NEMO community ocean modelling framework

Hayashida

Christian

Holdsworth

et al. 2018

Preprint

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“…Ice algae can also produce copious amounts of dimethylsulfoniopropionate (DMSP), the precursor of DMS, an osmotic regulator and a cryoprotectant [e.g., Tison et al, 2010]. Finally, iron concentrations in sea ice can be much higher than in the ocean and sea ice can act as a seasonal reservoir in the Southern Ocean [Lannuzel et al, 2007;2011]: growing sea ice incorporates large amounts of iron, later released into surface waters when the ice melts. This seasonal process may temporarily relieve iron limitation on phytoplankton growth, notably in the Southern Ocean [Lancelot et al, 2009], a key player in the marine carbon cycle [Sarmiento and Gruber, 2006;Sigman et al, 2010], but also in the Bering Sea [Aguilar-Islas et al, 2008] Sea ice proxies integrate information from biological, chemical and physical processes occurring in the polar oceans in an attempt to reconstruct past sea ice conditions [see Armand and Leventer, 2010, for a review].…”

Section: Introductionmentioning

confidence: 99%

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

Vancoppenolle

Meiners

Michel

et al. 2013

Quaternary Science Reviews

217

215

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International audienceObservations from the last decade suggest an important role of sea ice in the global biogeochemical cycles, promoted by (i) active biological and chemical processes within the sea ice; (ii) fluid and gas exchanges at the sea ice interface through an often permeable sea ice cover; and (iii) tight physical, biological and chemical interactions between the sea ice, the ocean and the atmosphere. Photosynthetic micro-organisms in sea ice thrive in liquid brine inclusions encased in a pure ice matrix, where they find suitable light and nutrient levels. They extend the production season, provide a winter and early spring food source, and contribute to organic carbon export to depth. Under-ice and ice edge phytoplankton blooms occur when ice retreats, favoured by increasing light, stratification, and by the release of material into the water column. In particular, the release of iron - highly concentrated in sea ice - could have large effects in the iron-limited Southern Ocean. The export of inorganic carbon transport by brine sinking below the mixed layer, calcium carbonate precipitation in sea ice, as well as active ice-atmosphere carbon dioxide (CO₂) fluxes, could play a central role in the marine carbon cycle. Sea ice processes could also significantly contribute to the sulphur cycle through the large production by ice algae of dimethylsulfoniopropionate (DMSP), the precursor of sulphate aerosols, which as cloud condensation nuclei have a potential cooling effect on the planet. Finally, the sea ice zone supports significant ocean-atmosphere methane (CH₄) fluxes, while saline ice surfaces activate springtime atmospheric bromine chemistry, setting ground for tropospheric ozone depletion events observed near both poles. All these mechanisms are generally known, but neither precisely understood nor quantified at large scales. As polar regions are rapidly changing, understanding the large-scale polar marine biogeochemical processes and their future evolution is of high priority. Earth system models should in this context prove essential, but they currently represent sea ice as biologically and chemically inert. Palaeoclimatic proxies are also relevant, in particular the sea ice proxies, inferring past sea ice conditions from glacial and marine sediment core records and providing analogues for future changes. Being highly constrained by marine biogeochemistry, sea ice proxies would not only contribute to but also benefit from a better understanding of polar marine biogeochemical cycles

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“…Decreased surface albedo (Perovich et al, 2011a), earlier melt onset, and a longer melt season (Markus et al, 2009, updated) have contributed to the observed increases in sea ice and snow melt (Perovich and Richter-Menge, 2009), and higher absorption and transmission of solar irradiance within and through Arctic sea ice Stroeve et al, 2014). Beyond the physical consequences of the observed changes, strong impacts on ecological interactions and biogeochemical processes are expected, such as changes in habitat conditions for ice-associated organisms or changes in primary production (Arrigo et al, 2012;Deal et al, 2011;Popova et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Seasonal cycle and long-term trend of solar energy fluxes through Arctic sea ice

Arndt

Nicolaus

2014

The Cryosphere

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Abstract. Arctic sea ice has not only decreased in volume during the last decades, but has also changed in its physical properties towards a thinner and more seasonal ice cover. These changes strongly impact the energy budget, and might affect the ice-associated ecosystems. In this study, we quantify solar shortwave fluxes through sea ice for the entire Arctic during all seasons. To focus on sea-ice-related processes, we exclude fluxes through open water, scaling linearly with sea ice concentration. We present a new parameterization of light transmittance through sea ice for all seasons as a function of variable sea ice properties. The maximum monthly mean solar heat flux under the ice of 30 × 10 5 Jm −2 occurs in June, enough heat to melt 0.3 m of sea ice. Furthermore, our results suggest that 96 % of the annual solar heat input through sea ice occurs during only a 4-month period from May to August. Applying the new parameterization to remote sensing and reanalysis data from 1979 to 2011, we find an increase in transmitted light of 1.5 % yr −1 for all regions. This corresponds to an increase in potential sea ice bottom melt of 63 % over the 33-year study period. Sensitivity studies reveal that the results depend strongly on the timing of melt onset and the correct classification of ice types. Assuming 2 weeks earlier melt onset, the annual transmitted solar radiation to the upper ocean increases by 20 %. Continuing the observed transition from a mixed multi-year/first-year sea ice cover to a seasonal ice cover results in an increase in light transmittance by an additional 18 %.

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Large‐scale modeling of primary production and ice algal biomass within arctic sea ice in 1992

Cited by 69 publications

References 40 publications

CSIB v1: a sea-ice biogeochemical model for the NEMO community ocean modelling framework

CSIB v1: a sea-ice biogeochemical model for the NEMO community ocean modelling framework

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

Seasonal cycle and long-term trend of solar energy fluxes through Arctic sea ice

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