Description: Oceans play a major role on the exchange of carbon with the atmosphere and thereby on past climates with glacial/interglacial variations of the CO2 concentration. The melting of ice sheets during deglaciations lets the sea level rise which leads to the flooding of coastal land areas resulting in the transfer of terrestrial organic matter to the ocean. However, the consequences of such fluxes on the ocean biogeochemical cycle and uptake/release of CO2 are poorly constrained. Moreover, this potentially important exchange of carbon at the land-sea interface is not represented in most Earth System Models. We present here the implementation of terrestrial organic matter fluxes into the ocean at the transiently changing land-sea interface in the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) and investigate their effect on the biogeochemistry during the last deglaciation. Our results show that during the deglaciation, most of the terrestrial organic matter inputs to the ocean occurs during Meltwater Pulse 1a (between 15–14 ka) which leads to additional 21.2 GtC of terrestrial origin (mostly originating from wood and humus). Although this additional organic matter input is relatively small in comparison to the global ocean inventory (0.06 %) and thus doesn’t have an impact on the global CO2 flux, the terrestrial organic matter fluxes initiate oceanic outgassing at regional hotspots like in Indonesia for a few hundred years. Finally, sensitivity experiments highlight that terrestrial organic matter fluxes are the drivers of oceanic outgassing in flooded coastal regions during Meltwater Pulse 1a. Furthermore, the magnitude of outgassing is rather insensitive to higher carbon to nutrients ratios of the terrestrial organic matter. Our results provide a first estimate of the importance of terrestrial organic matter fluxes in a transient deglaciation simulation. Moreover, our model development is an important step towards a fully coupled carbon cycle in an Earth System Model applicable for simulations of glacial/interglacial cycles.

Description: Direct comparison between paleo oceanic δ13C records and model results facilitates assessing simulated distributions and properties of water masses in the past. To accomplish this, 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 existing oceanic carbon pools. 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 in dissolved inorganic carbon (DIC), both parameterisations yield similar performance. However, with regard to δ13C in particulate organic carbon εpPopp shows a considerably improved performance than εpLaws, because the latter results in a too strong preference for 12C. The model also well reproduces the oceanic 13C Suess effect, i.e. the intrusion of the isotopically light anthropogenic CO2 into the ocean, based on comparison to other existing 13C models and to observation-based oceanic carbon uptake estimates over the industrial period. We further apply the approach of Eide et al. (2017a), who derived the first global oceanic 13C Suess effect estimate based on observations, to our model data that has ample spatial and temporal coverage. With this we are able to analyse in detail the underestimation of 13C Suess effect by this approach as it has been noted by Eide et al. (2017a). Based on our model we find underestimations of 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 the underestimation to two assumptions in Eide et al. (2017a)'s approach: a spatially-constant preformed component of δ13CDIC in year 1940 and neglecting 13C Suess effect in CFC-12 free water.

Description: The carbon cycle component of the newly developed Earth System Model of intermediate complexity CLIMBER-X is presented. The model represents the cycling of carbon through atmosphere, vegetation, soils, seawater and marine sediments. Exchanges of carbon with geological reservoirs occur through sediment burial, rock weathering and volcanic degassing. The state-of-the-art HAMOCC6 model is employed to simulate ocean biogeochemistry and marine sediments processes. The land model PALADYN simulates the processes related to vegetation and soil carbon dynamics, including permafrost and peatlands. The dust cycle in the model allows for an interactive determination of the input of the micro-nutrient iron into the ocean. A rock weathering scheme is implemented into the model, with the weathering rate depending on lithology, runoff and soil temperature. CLIMBER-X includes a simple representation of the methane cycle, with explicitly modelled natural emissions from land and the assumption of a constant residence time of CH4 in the atmosphere. Carbon isotopes 13C and 14C are tracked through all model compartments and provide a useful diagnostic for model-data comparison. A comprehensive evaluation of the model performance for present–day and the historical period shows that CLIMBER-X is capable of realistically reproducing the historical evolution of atmospheric CO2 and CH4, but also the spatial distribution of carbon on land and the 3D structure of biogeochemical ocean tracers. The analysis of model performance is complemented by an assessment of carbon cycle feedbacks and model sensitivities compared to state-of-the-art CMIP6 models. Enabling interactive carbon cycle in CLIMBER-X results in a relatively minor slow-down of model computational performance by ~20 %, compared to a throughput of ~10,000 simulation years per day on a single node with 16 CPUs on a high performance computer in a climate–only model setup. CLIMBER-X is therefore well suited to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to 〉100,000 years.