Investigating controls on sea ice algal production using E3SMv1.1-BGC

• Published in: Annals of Glaciology
• Main Authors: Nicole Jeffery, Mathew E. Maltrud, Elizabeth C. Hunke, Shanlin Wang, Jon Wolfe, Adrian K. Turner, Susannah M. Burrows, Xiaoying Shi, William H. Lipscomb, Wieslaw Maslowski, Kate V. Calvin
• Format: Article in Journal/Newspaper
• Language: English
• Published: Cambridge University Press 2020
• Subjects: Sea ice; biogeochemistry; modeling; primary production; polar; Meteorology. Climatology; QC851-999; Arctic; Southern Ocean; Annals of Glaciology
• Online Access: https://doi.org/10.1017/aog.2020.7; https://doaj.org/article/783b1c3b51e64f3b857e0a0fc62fd5b4

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.