@Article{Fu_JGRO_20221001,
 author		= {Weiwei Fu and J. Keith Moore and Fran{\c}ois Primeau and Nathan Collier and Oluwaseun O. Ogunro and Forrest M. Hoffman and James T. Randerson},
 title		= {Evaluation of Ocean Biogeochemistry and Carbon Cycling in {CMIP} {E}arth System Models With the {I}nternational {O}cean {M}odel {B}enchmarking ({IOMB}) Software System},
 journal	= JGRO,
 volume		= 127,
 number		= 10,
 pages		= {e2022JC018965},
 doi		= {10.1029/2022JC018965},
 day		= 1,
 month		= oct,
 year		= 2022,
 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$^\circ$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 $27.8 \pm 0.5$~Pg\,C lower than a data-constrained estimate of $33.0 \pm 4.0$~Pg\,C. At the same time, the change in the natural carbon inventory from CMIP is estimated to be a source of $0.7 \pm 0.3$~Pg\,C, which is considerably smaller in magnitude than a data-constrained estimate of $5.0 \pm 3.0$~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.}
}