The representation of alkalinity and the carbonate pump from CMIP5 to CMIP6 ESMs and implications for the ocean carbon cycle
Abstract. Ocean alkalinity is critical to the uptake of atmospheric carbon in surface waters and provides buffering capacity towards associated acidification. However, unlike dissolved inorganic carbon (DIC), alkalinity is not directly impacted by anthropogenic carbon emissions. Within the context of projections of future ocean carbon uptake and potential ecosystem impacts, especially through Coupled Model Intercomparison Projects (CMIPs), the representation of alkalinity and the main driver of its distribution in the ocean interior, the calcium carbonate cycle, have often been overlooked. Here we track the changes from CMIP5 to CMIP6 with respect to the Earth system model (ESM) representation of alkalinity and the carbonate pump which depletes the surface ocean in alkalinity through biological production of calcium carbonate, and releases it at depth through export and dissolution. We report a significant improvement in the representation of alkalinity in CMIP6 ESMs relative to those in CMIP5. This improvement can be explained in part by an increase in calcium carbonate (CaCO3) production for some ESMs, which redistributes alkalinity at the surface and strengthens its vertical gradient in the water column. We were able to constrain a PIC export estimate of 51–70 Tmol yr-1 at 100 m for the ESMs to match the observed vertical gradient of alkalinity. Biases in the vertical profile of DIC have also significantly decreased, especially with the enhancement of the carbonate pump, but the representation of the saturation horizons has slightly worsened in contrast. Reviewing the representation of the CaCO3 cycle across CMIP5/6, we find a substantial range of parameterizations. While all biogeochemical models currently represent pelagic calcification, they do so implicitly, and they do not represent benthic calcification. In addition, most models simulate marine calcite but not aragonite. In CMIP6 certain model groups have increased the complexity of simulated CaCO3 production, sinking, dissolution and sedimentation. However, this is insufficient to explain the overall improvement in the alkalinity representation, which is therefore likely a result of improved marine biogeochemistry model tuning or ad hoc parameterizations. We find differences in the way ocean alkalinity is initialized that lead to offsets of up to 1 % in the global alkalinity inventory of certain models. These initialization biases should be addressed in future CMIPs by adopting accurate unit conversions. Although modelers aim to balance the global alkalinity budget in ESMs in order to limit drift in ocean carbon uptake under preindustrial conditions, varying assumptions in the closure of the budget have the potential to influence projections of future carbon uptake. For instance, in many models, carbonate production, dissolution and burial are independent of the seawater saturation state, and when considered, the range of sensitivities is substantial. As such, the future impact of ocean acidification on the carbonate pump, and in turn ocean carbon uptake, is potentially underestimated in current ESMs and insufficiently constrained.
Alban Planchat et al.
Alban Planchat et al.
Alban Planchat et al.
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Review ofThe representation of alkalinity and the carbonate pump from CMIP5 to CMIP6 EMSs and implications for the ocean carbon cycle by Planchat et al.
In this manuscript, Planchat et al. compare the representation of ocean alkalinity within a set of 15 marine biogeochemical models, across two generations, from CMIP5 to CMIP6. Besides alkalinity they also compare seawater dissolved inorganic carbon (DIC), as well as sinking fluxes of CaCO3 and particulate organic carbon. They note an increased global export of CaCO3, closer to observations, and a strengthened vertical alkalinity gradient.
This is a long and dense manuscript, but remarkably clearly written and structured given the number of results presented. Overall, this is likely going to be a key paper that will be useful to anyone using or interpreting results from CMIP5/6 models, and will pave the way to the next generation of ocean biogeochemical models. I enjoyed reading and reviewing it and praise the authors for putting such an important piece of work together.
One main comment I have after reading this piece is that what has changed within models between both generations is clearly presented in the main text, and as a result, we are left wondering what exactly needs to be done for models to better reproduce observed alkalinity patterns. I reckon that there are many models included in this analysis and that all had unique improvements that were not necessarily well described in the original publications/technical notes, so it is very challenging to attribute the improvement to any process. Section 3.1 does a great job synthesizing the different ways to represent various processes across different model groups; it would be useful to do the same synthesis effort but focusing on changes between CMIP5 and CMIP6. Section 4.1 touches this issue, but is very short, and seems to be summarized by the fact that no major trend emerges with regards to the modelling schemes. Could the authors develop this section further? What could be the main processes behind the improved, stronger alkalinity gradient? Inclusion of aragonite or of better diagenesis modules? Could the authors express their opinions on which processes need to be implemented n priority in the next generation of models?
L31: avoid use of significant for non-statistical meaning
L87: remove extra “Fig. 1”
L170: define “piControl” and “Historical” experiments
L180-181: just to make sure I understand: export at 100m from the 3D fields is in theory the exact same thing than export at 100m from the 2D fields?
L182-183: why using MIROC models then? Can you precise whether there is no export in those models, or those quantities exist but were not saved and/or made available to you?
L194: what are those constants?
L196-197: are those two models the only ones that include exchanges at the seafloor? Discarding the lower layer would appear justified if the goal was to compare water-column processes amongst models and if only the lower layer was affected by non-water-column (i.e. seafloor). However, seafloor processes, e.g., dissolution or respiration, should also affect water-column chemistry far away from the seafloor. I would like further discussion regarding the role of seafloor processes in the current model intercomparison (see main comment).
L203: define SSP and explain the difference with RCP
L230-231: I believe that the Sulpis and Battaglia references are mixed up in this sentence
L257: what is tau^5m? the concentration of a given tracer tau at 5 m-depth?
Section 3.1.1.: An explicit integration of calcification in models would look like a series of equations used to compute calcification for individual groups, as a function of variables such as light, saturation state, etc. If I understand correctly the implicit integration used by all models skip the production step and computes the PIC export directly, as a function of the same variables (light, saturation, etc.). Because this implicit calcification scheme misses “gut dissolution”, as explained in this section, models using it should all miss the shallow (in the couple hundred meters below the euphotic layer) but strong alkalinity production observed in the ocean, see Feely et al. (2004, DOI: 10.1126/science.1097329), Subhas et al. (2022, https://doi.org/10.1029/2022GB007388), Sulpis et al. (2021, https://doi.org/10.1038/s41561-021-00743-y).Could you show and/or discuss that somewhere?
Section 3.1.4.: the term “sedimentation” sounds simply like physical accumulation or burial, whereas in this context it should include other sediment transport processes and chemical reactions. Perhaps replace with “diagenesis”?
L445: please add a reference for an observational estimate of the rain ratio
Table 1 define “MBG”
Fig. 1 the arrow associated with (3) dissolution should be colored in green because, as for the arrow associated with sediment mobilization, it represents a flux impacting seawater alkalinity
Figure 2 why are the 6th and 8th rows for the MPI models not colored instead of being colored in grey (N/A)?
Figures 2 and 6: all CaCO3 in ACCESS-ESM1-5 is aragonite? Can you please elaborate on that?