Abstract

Abstract. The stable carbon isotopic composition (δ13C) is an important variable to study the ocean carbon cycle across different timescales. We include a new representation of the stable carbon isotope 13C into the HAMburg Ocean Carbon Cycle model (HAMOCC), the ocean biogeochemical component of the Max Planck Institute Earth System Model (MPI-ESM). 13C is explicitly resolved for all oceanic carbon pools considered. We account for fractionation during air–sea gas exchange and for biological fractionation ϵp associated with photosynthetic carbon fixation during phytoplankton growth. We examine two ϵp parameterisations of different complexity: ϵpPopp varies with surface dissolved CO2 concentration (Popp et al., 1989), while ϵpLaws additionally depends on local phytoplankton growth rates (Laws et al., 1995). When compared to observations of δ13C of dissolved inorganic carbon (DIC), both parameterisations yield similar performance. However, with regard to δ13C in particulate organic carbon (POC) ϵpPopp shows a considerably improved performance compared to ϵpLaws. This is because ϵpLaws produces too strong a preference for 12C, resulting in δ13CPOC that is too low in our model. The model also well reproduces the global oceanic anthropogenic CO2 sink and the oceanic 13C Suess effect, i.e. the intrusion and distribution of the isotopically light anthropogenic CO2 in the ocean. The satisfactory model performance of the present-day oceanic δ13C distribution using ϵpPopp and of the anthropogenic CO2 uptake allows us to further investigate the potential sources of uncertainty of the Eide et al. (2017a) approach for estimating the oceanic 13C Suess effect. Eide et al. (2017a) derived the first global oceanic 13C Suess effect estimate based on observations. They have noted a potential underestimation, but their approach does not provide any insight about the cause. By applying the Eide et al. (2017a) approach to the model data we are able to investigate in detail potential sources of underestimation of the 13C Suess effect. Based on our model we find underestimations of the 13C Suess effect at 200 m by 0.24 ‰ in the Indian Ocean, 0.21 ‰ in the North Pacific, 0.26 ‰ in the South Pacific, 0.1 ‰ in the North Atlantic and 0.14 ‰ in the South Atlantic. We attribute the major sources of underestimation to two assumptions in the Eide et al. (2017a) approach: the spatially uniform preformed component of δ13CDIC in year 1940 and the neglect of processes that are not directly linked to the oceanic uptake and transport of chlorofluorocarbon-12 (CFC-12) such as the decrease in δ13CPOC over the industrial period. The new 13C module in the ocean biogeochemical component of MPI-ESM shows satisfying performance. It is a useful tool to study the ocean carbon sink under the anthropogenic influences, and it will be applied to investigating variations of ocean carbon cycle in the past.

Highlights

  • The stable carbon isotopic composition (δ13C) measured in carbonate shells of fossil foraminifera is one of the most widely used properties in paleoceanographic research (Schmittner et al, 2017)

  • We present a new implementation of 13C in the HAMburg Ocean Carbon Cycle model (HAMOCC6), the ocean biogeochemical component of the Max Planck Institute Earth System Model (MPI-Earth system models (ESMs))

  • The model is able to reproduce the size of the global oceanic anthropogenic CO2 sink, though some local biases in the net air–sea CO2 flux exist (Fig. 9d)

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Summary

Introduction

The stable carbon isotopic composition (δ13C) measured in carbonate shells of fossil foraminifera is one of the most widely used properties in paleoceanographic research (Schmittner et al, 2017). Due to the simplified representation of marine biological production in HAMOCC3, biological fractionation was based on fixation of inorganic carbon into non-living particulate organic matter and was parameterised by a spatially and temporally uniform factor. Such an observation-based estimate is valuable as it is the basis of an almost independent estimate of the global ocean anthropogenic carbon uptake It could be used for evaluating models at pre-industrial states (Buchanan et al, 2019; Tjiputra et al, 2020) and for setting up paleo-simulations (O’Neill et al, 2019). Our consistent model framework, with the complete spatiotemporal information of the hydrological and biogeochemical variables, enables us to investigate the spatial distribution of the above-mentioned potential underestimation of the oceanic 13C Suess effect.

Model description
The stable carbon isotope 13C in HAMOCC6
Fractionation during air–sea gas exchange
Fractionation during phytoplankton growth
Model setup and experimental design
Experimental design
Model results and observations in the late 20th century
Isotopic signature of particular organic carbon in the surface ocean
Isotopic signature of dissolved inorganic carbon δ13CDIC
Evaluation of the simulated oceanic 13C Suess effect
Source of underestimation attributed to data coverage
Source of underestimation attributed to assumptions of E17’s approach
Summary and conclusions
Additional model–observation comparison for oceanic biogeochemical variables
Linear regression for subregions in the Indian Ocean
Calculation of SEtotal
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