Investigating controls on sea ice algal production using E3SMv1.1-BGC. Issue 82 (21st September 2020)

• Record Type: Journal Article
• Authors: Jeffery, Nicole; Maltrud, Mathew E.; Hunke, Elizabeth C.; Wang, Shanlin; Wolfe, Jon; Turner, Adrian K.; Burrows, Susannah M.; Shi, Xiaoying; Lipscomb, William H.; Maslowski, Wieslaw; Calvin, Kate V.
• Is Part Of: Annals of glaciology. Volume 61:Issue 82(2020)
• Page Start: 51
• Page End: 72
• Publication Date: 2020-09-21
• Subjects: Sea ice, -- biogeochemistry, -- modeling, -- primary production, -- polar; Glaciology -- Periodicals; 551.3105 qA613
• DOI: 10.1017/aog.2020.7
• Languages: English
• ISSNs: 0260-3055

Abstract

Abstract: We present the analysis of global sympagic primary production (PP) from 300 years of pre-industrial and historical simulations of the E3SMv1.1-BGC model. The model includes a novel, eight-element sea ice biogeochemical component, MPAS-Seaice zbgc, which is resolved in three spatial dimensions and uses a vertical transport scheme based on internal brine dynamics. Modeled ice algal chlorophyll-a concentrations and column-integrated values are broadly consistent with observations, though chl-a profile fractions indicate that upper ice communities of the Southern Ocean are underestimated. Simulations of polar integrated sea ice PP support the lower bound in published estimates for both polar regions with mean Arctic values of 7.5 and 15.5 TgC/a in the Southern Ocean. However, comparisons of the polar climate state with observations, using a maximal bound for ice algal growth rates, suggest that the Arctic lower bound is a significant underestimation driven by biases in ocean surface nitrate, and that correction of these biases supports as much as 60.7 TgC/a of net Arctic PP. Simulated Southern Ocean sympagic PP is predominantly light-limited, and regional patterns, particularly in the coastal high production band, are found to be negatively correlated with snow thickness.