The partitioning of CO2 between atmosphere and ocean depends to a large degree not only on the amount of dissolved inorganic carbon (DIC) but also of alkalinity in the surface ocean. That is also why, in the context of negative emission approaches ocean alkalinity enhancement is discussed as one potential approach. Although alkalinity is thus an important variable of the marine carbonate system little knowledge exists how its representation in models compares with measurements. We evaluated the large-scale alkalinity distribution in 14 CMIP6 models against the observational data set GLODAPv2 and showed that most models as well as the multi-model-mean underestimate alkalinity at the surface and in the upper ocean, while overestimating alkalinity in the deeper ocean. The decomposition of the global mean alkalinity biases into contributions from physical processes (preformed alkalinity), remineralization, and carbonate formation and dissolution showed that the bias stemming from the physical redistribution of alkalinity is dominant. However, below the upper few hundred meters the bias from carbonate dissolution can become similarly important as physical biases, while the contribution from remineralization processes is negligible. This highlights the critical need for better understanding and quantification of processes driving calcium carbonate dissolution in microenvironments above the saturation horizons, and implementation of these processes into biogeochemical models.
For the application of the models to assess the potential of ocean alkalinity enhancement to increase ocean carbon uptake and counteract ocean acidification, a back-of-the-envelope calculation was conducted with each model’s global mean surface alkalinity and DIC as input parameters. We find that the degree of compensation of DIC and alkalinity biases at the surface is more important for the marine CO2 uptake capacity than the alkalinity biases themselves. The global mean surface alkalinity bias relative to GLODAPv2 in the different models ranges from -85 mmol kg-1 (-3.6 %) to +50 mmol kg-1 (+2.1 %) (mean: -25 mmol kg-1 or -1.1 %), while for DIC the relative bias ranges from -55 mmol kg-1 (-2.6 %) to 53 mmol kg-1 (+2.5 %) (mean: -13 mmol kg-1 or -0.6 %). Because of this partial compensation, all but two of the CMIP6 models evaluated here overestimate the Revelle factor at the surface and thus overestimate the CO2-draw-down after alkalinity addition by up to 13 % and pH increase by up to 7.2 %. This overestimate has to be taken into account when reporting on efficiencies of ocean alkalinity enhancement experiments using CMIP6 models.
Hinrichs C., Köhler P., Völker C. & Hauck J., 2023. Alkalinity biases in CMIP6 Earth System Models and implications for simulated CO2 drawdown via artificial alkalinity enhancement. Biogeosciences Discussions. Article.
