Substantial inter-model variation in OAE efficiency between the CESM2/MARBL and ECCO-Darwin ocean biogeochemistry models

Abstract. Induction of a surface-ocean DIC (dissolved organic carbon) deficit through alkalinity-based or direct CO₂ removal methods has been recognized as a promising approach to meet the projected need for negative emissions. The difficulty of directly measuring the counter-factual CO₂ flux due to rapid spreading of the DIC-deficient plume has put ocean circulation models in the center of the Measurement, Reporting and Verification (MRV) challenge. Confidence in the results of such models is essential for the emerging industry to access carbon credit markets and grow at the required pace, to reach substantial negative emissions by 2050, as envisioned by the Intergovernmental Panel on Climate Change (IPCC).

The kinetics and equilibration time of such a DIC deficit have been shown to vary substantially depending on the location and season of the initial induction point. A major component of this variance is the vertical transport and mixing of the DIC-deficient plume; however, air-sea CO₂ gas exchange and carbonate chemistry are also important.

Currently, it is poorly understood how much the results of DIC-deficit pulse simulations depend on the models chosen. To help close this knowledge gap, we investigate two global circulation models, the CESM2/MARBL model (1°) and the data-assimilative ECCO-Darwin model (1/3°). We perform pulse injection simulations at twelve locations with both models, matched precisely in terms of injection patch geometry, release year and season. We analyze the differences in CO₂ uptake curves, vertical mixing, gas exchange and carbonate chemistry.

We show that in some locations, such as subtropical regions, substantial differences exist between these two models — well beyond the expected intrinsic variation of each model. Furthermore, we demonstrate that the majority of the differences are attributable to the representation of vertical transport, followed by the effect of wind parameterizations. A small amount of difference is attributable to carbonate chemistry parameterization. In some locations, there exists good agreement between the models. In most injection locations, the largest differences between models are found in the first 7 years post alkalinity injection, followed by slow convergence towards the expected theoretical maximums.