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

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

doi:10.1017/aog.2020.7

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

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

Earth Systems Modeling

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

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.

Original language	English
Pages (from-to)	51-72
Number of pages	22
Journal	Annals of Glaciology
Volume	61
Issue number	82
DOIs	https://doi.org/10.1017/aog.2020.7
State	Published - Sep 1 2020

Funding

This research was supported as part of the Energy Exascale Earth System Model (E3SM) project, funded by the US Department of Energy, Office of Science, Office of Biological and Environmental Research. Additional support was provided by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area (SFA), which is sponsored by the Regional and Global Model Analysis (RGMA) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the US Department of Energy Office of Science. The National Center for Atmospheric Research is a major facility sponsored by the National Science Foundation under Cooperative Agreement No. 1852977. The authors thank all the members of the E3SM project for their essential contributions and support. Special thanks to S. Elliott and two anonymous reviewers for their many insightful comments.

Keywords

Sea ice
biogeochemistry
modeling
polar
primary production

Access to Document

10.1017/aog.2020.7

Cite this

@article{29d1cb9bcc704337b49cef6ec1045704,

title = "Investigating controls on sea ice algal production using E3SMv1.1-BGC",

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.",

keywords = "Sea ice, biogeochemistry, modeling, polar, primary production",

author = "Nicole Jeffery and Maltrud, {Mathew E.} and Hunke, {Elizabeth C.} and Shanlin Wang and Jon Wolfe and Turner, {Adrian K.} and Burrows, {Susannah M.} and Xiaoying Shi and Lipscomb, {William H.} and Wieslaw Maslowski and Calvin, {Kate V.}",

note = "Publisher Copyright: Copyright {\textcopyright} The Author(s) 2020.",

year = "2020",

month = sep,

day = "1",

doi = "10.1017/aog.2020.7",

language = "English",

volume = "61",

pages = "51--72",

journal = "Annals of Glaciology",

issn = "0260-3055",

publisher = "Cambridge University Press",

number = "82",

}

TY - JOUR

T1 - Investigating controls on sea ice algal production using E3SMv1.1-BGC

AU - Jeffery, Nicole

AU - Maltrud, Mathew E.

AU - Hunke, Elizabeth C.

AU - Wang, Shanlin

AU - Wolfe, Jon

AU - Turner, Adrian K.

AU - Burrows, Susannah M.

AU - Shi, Xiaoying

AU - Lipscomb, William H.

AU - Maslowski, Wieslaw

AU - Calvin, Kate V.

PY - 2020/9/1

Y1 - 2020/9/1

N2 - 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.

AB - 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.

KW - Sea ice

KW - biogeochemistry

KW - modeling

KW - polar

KW - primary production

UR - http://www.scopus.com/inward/record.url?scp=85081357329&partnerID=8YFLogxK

U2 - 10.1017/aog.2020.7

DO - 10.1017/aog.2020.7

M3 - Article

AN - SCOPUS:85081357329

SN - 0260-3055

VL - 61

SP - 51

EP - 72

JO - Annals of Glaciology

JF - Annals of Glaciology

IS - 82

ER -

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

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this