Evaluation of Ocean Biogeochemistry and Carbon Cycling in CMIP Earth System Models With the International Ocean Model Benchmarking (IOMB) Software System

Weiwei Fu; J. Keith Moore; Francois Primeau; Nathan Collier; Oluwaseun O. Ogunro; Forrest M. Hoffman; James T. Randerson

doi:10.1029/2022JC018965

Evaluation of Ocean Biogeochemistry and Carbon Cycling in CMIP Earth System Models With the International Ocean Model Benchmarking (IOMB) Software System

Weiwei Fu, J. Keith Moore, Francois Primeau, Nathan Collier, Oluwaseun O. Ogunro, Forrest M. Hoffman, James T. Randerson

Computational Earth Sciences Group

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

20 Scopus citations

Abstract

The International Ocean Model Benchmarking (IOMB) software package is a new community resource that we use here to evaluate surface and upper ocean biogeochemical variables and integrated anthropogenic carbon uptake from earth system models (ESMs) contributing to the 5th and 6th phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). IOMB generates graphics and tables for systematically comparing model predictions against multiple datasets. Our analysis reveals some improvement in the multi-model mean from CMIP5 to CMIP6 for most of the variables we examined. Compared to data-constrained estimates of ocean anthropogenic carbon uptake for the 1994–2007 period, negative biases exist for many models between 30 and 50°S. Global model estimates of anthropogenic carbon uptake for the same period do not change significantly from CMIP5 to CMIP6, with the combined ensemble mean estimate of 27.8 ± 0.5 Pg C lower than a data-constrained estimate of 33.0 ± 4.0 Pg C. At the same time, the change in the natural carbon inventory from CMIP is estimated to be a source of 0.7 ± 0.3 Pg C, which is considerably smaller in magnitude than a data-constrained estimate of 5.0 ± 3.0 Pg C. With chlorofluorocarbon (CFC) predictions available for several models, we demonstrate that negative anthropogenic dissolved inorganic carbon biases coincide with negative biases in CFC concentration, highlighting the importance of weak exchange between the surface and interior ocean in regulating rates of anthropogenic carbon uptake. To examine the robustness of this attribution across the CMIP models, we calculate the global vertical temperature gradient between 200 and 1,000 m as a metric for global stratification and exchange between the surface and deeper waters. We find a linear relationship between the bias of the vertical temperature gradients and the bias in global anthropogenic carbon uptake, consistent with the hypothesis that model biases in anthropogenic carbon uptake are related to biases in surface-to-interior exchange by physical processes.

Original language	English
Article number	e2022JC018965
Journal	Journal of Geophysical Research: Oceans
Volume	127
Issue number	10
DOIs	https://doi.org/10.1029/2022JC018965
State	Published - Oct 2022

Funding

The authors acknowledge support from the Reducing Uncertainty in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area (SFA), which is sponsored by the Regional and Global Model Analysis (RGMA) program area of the Earth and Environmental Systems Sciences Division (EESSD) of the Biological and Environmental Research (BER) office of the U.S. Department of Energy (DOE) Office of Science. FWP acknowledges support from DOE Office of Biological and Environmental Research Award Number DE-SC0021267. We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling, which is responsible for CMIP. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP5, CMIP6, and ESGF. We thank DOE's RGMA program area, the Data Management Program, and NERSC for making this coordinated CMIP6 analysis activity possible. The authors acknowledge support from the Reducing Uncertainty in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area (SFA), which is sponsored by the Regional and Global Model Analysis (RGMA) program area of the Earth and Environmental Systems Sciences Division (EESSD) of the Biological and Environmental Research (BER) office of the U.S. Department of Energy (DOE) Office of Science. FWP acknowledges support from DOE Office of Biological and Environmental Research Award Number DE‐SC0021267. We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling, which is responsible for CMIP. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP5, CMIP6, and ESGF. We thank DOE's RGMA program area, the Data Management Program, and NERSC for making this coordinated CMIP6 analysis activity possible.

Keywords

IOMB
anthropogenic carbon inventory
benchmark
biogeochemical variable
vertical temperature gradient

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10.1029/2022JC018965

Cite this

Fu, W., Moore, J. K., Primeau, F., Collier, N., Ogunro, O. O., Hoffman, F. M., & Randerson, J. T. (2022). Evaluation of Ocean Biogeochemistry and Carbon Cycling in CMIP Earth System Models With the International Ocean Model Benchmarking (IOMB) Software System. Journal of Geophysical Research: Oceans, 127(10), Article e2022JC018965. https://doi.org/10.1029/2022JC018965

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author = "Weiwei Fu and Moore, {J. Keith} and Francois Primeau and Nathan Collier and Ogunro, {Oluwaseun O.} and Hoffman, {Forrest M.} and Randerson, {James T.}",

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AU - Collier, Nathan

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AU - Randerson, James T.

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AB - The International Ocean Model Benchmarking (IOMB) software package is a new community resource that we use here to evaluate surface and upper ocean biogeochemical variables and integrated anthropogenic carbon uptake from earth system models (ESMs) contributing to the 5th and 6th phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). IOMB generates graphics and tables for systematically comparing model predictions against multiple datasets. Our analysis reveals some improvement in the multi-model mean from CMIP5 to CMIP6 for most of the variables we examined. Compared to data-constrained estimates of ocean anthropogenic carbon uptake for the 1994–2007 period, negative biases exist for many models between 30 and 50°S. Global model estimates of anthropogenic carbon uptake for the same period do not change significantly from CMIP5 to CMIP6, with the combined ensemble mean estimate of 27.8 ± 0.5 Pg C lower than a data-constrained estimate of 33.0 ± 4.0 Pg C. At the same time, the change in the natural carbon inventory from CMIP is estimated to be a source of 0.7 ± 0.3 Pg C, which is considerably smaller in magnitude than a data-constrained estimate of 5.0 ± 3.0 Pg C. With chlorofluorocarbon (CFC) predictions available for several models, we demonstrate that negative anthropogenic dissolved inorganic carbon biases coincide with negative biases in CFC concentration, highlighting the importance of weak exchange between the surface and interior ocean in regulating rates of anthropogenic carbon uptake. To examine the robustness of this attribution across the CMIP models, we calculate the global vertical temperature gradient between 200 and 1,000 m as a metric for global stratification and exchange between the surface and deeper waters. We find a linear relationship between the bias of the vertical temperature gradients and the bias in global anthropogenic carbon uptake, consistent with the hypothesis that model biases in anthropogenic carbon uptake are related to biases in surface-to-interior exchange by physical processes.

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Evaluation of Ocean Biogeochemistry and Carbon Cycling in CMIP Earth System Models With the International Ocean Model Benchmarking (IOMB) Software System

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Keywords

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