ALBERT

Description: The Southern Ocean is a major sink for anthropogenic carbon. Yet, there is no quantitative consensus about how this sink will change when surface winds increase (as they are anticipated to do). Among the tools employed to quantify carbon uptake are global coupled ocean-circulation biogeochemical models. Because of computational limitations these models still fail to resolve potentially-important spatial scales. Instead, processes on these scales are parameterized. There is concern that deficiencies in these so-called eddy-parameterizations might imprint wrong sensitivities of projected oceanic carbon uptake. Here, we compare natural carbon uptake in the Southern Ocean simulated with contemporary eddy-parameterizations. We find that very differing parameterizations yield surprisingly similar oceanic carbon in response to strengthening winds. In contrast, we find (in an additional simulation) that the carbon uptake does differ substantially when the supply of bioavailable iron is altered within its envelope of uncertainty. We conclude that a more comprehensive understanding of bioavailable iron dynamics will substantially reduce the uncertainty of model-based projections of oceanic carbon uptake.

Description: We investigate the climate mitigation potential and collateral effects of direct injections of captured CO2 into the deep ocean as a possible means to close the gap between an intermediate CO2 emissions scenario and a specific temperature target, such as the 1.5 ∘C target aimed for by the Paris Agreement. For that purpose, a suite of approaches for controlling the amount of direct CO2 injections at 3000 m water depth are implemented in an Earth system model of intermediate complexity. Following the representative concentration pathway RCP4.5, which is a medium mitigation CO2 emissions scenario, cumulative CO2 injections required to meet the 1.5 ∘C climate goal are found to be 390 Gt C by the year 2100 and 1562 Gt C at the end of simulations, by the year 3020. The latter includes a cumulative leakage of 602 Gt C that needs to be reinjected in order to sustain the targeted global mean temperature. CaCO3 sediment and weathering feedbacks reduce the required CO2 injections that comply with the 1.5 ∘C target by about 13 % in 2100 and by about 11 % at the end of the simulation. With respect to the injection-related impacts we find that average pH values in the surface ocean are increased by about 0.13 to 0.18 units, when compared to the control run. In the model, this results in significant increases in potential coral reef habitats, i.e., the volume of the global upper ocean (0 to 130 m depth) with omega aragonite 〉 3.4 and ocean temperatures between 21 and 28 ∘C, compared to the control run. The potential benefits in the upper ocean come at the expense of strongly acidified water masses at depth, with maximum pH reductions of about −2.37 units, relative to preindustrial levels, in the vicinity of the injection sites. Overall, this study demonstrates that massive amounts of CO2 would need to be injected into the deep ocean in order to reach and maintain the 1.5 ∘C climate target in a medium mitigation scenario on a millennium timescale, and that there is a trade-off between injection-related reductions in atmospheric CO2 levels accompanied by reduced upper-ocean acidification and adverse effects on deep-ocean chemistry, particularly near the injection sites.

Description: Controlled manipulation of environmental conditions within large enclosures in the ocean, so-called pelagic mesocosms, has become a standard method to explore potential responses of marine plankton communities to anthropogenic change. Among the challenges of interpreting mesocosm data is the often uncertain role of vertical mixing, which usually is not observed directly. To account for mixing nonetheless, two pragmatic assumptions are common: either that the water column is homogeneously mixed or that it is divided into two water bodies with a horizontal barrier inhibiting turbulent exchange. In this study, we present a model-based reanalysis of vertical turbulent diffusion in the mesocosm experiments PeECE III and KOSMOS 2013. Our diffusivity estimates indicate intermittent mixing events along with stagnating periods and yield simulated temperature and salinity profiles that are consistent with the observations. Here, we provide the respective diffusivities as a comprehensive data product in the Network Common Data Format (NetCDF). This data product will help to guide forthcoming model studies that aim at deepening our understanding of biogeochemical processes in the PeECE III and KOSMOS 2013 mesocosms, such as the CO2-related changes in marine carbon export. In addition, we make our model code available, providing an adjustable tool to simulate vertical mixing in any other pelagic mesocosm. The data product and the model code are available at https://doi.org/10.1594/PANGAEA.905311 (Mathesius et al., 2019).

Description: We present a new near-global coupled biogeochemical ocean-circulation model configuration. The configuration features a horizontal discretization with a grid spacing of less than 11 km in the Southern Ocean and gradually coarsens in meridional direction to more than 200 km at 64∘ N, where the model is bounded by a solid wall. The underlying code framework is the Geophysical Fluid Dynamics Laboratory (GFDL)'s Modular Ocean Model coupled to the Biogeochemistry with Light, Iron, Nutrients and Gases (BLING) ecosystem model of Galbraith et al. (2010). The configuration is unique in that it features both a relatively equilibrated oceanic carbon inventory and an eddying ocean circulation based on a realistic model geometry/bathymetry – a combination that has been precluded by prohibitive computational cost in the past. Results from a simulation with climatological forcing and a sensitivity experiment with increasing winds suggest that the configuration is sufficiently equilibrated to explore Southern Ocean carbon uptake dynamics on decadal timescales. The configuration is dubbed MOMSO, a Modular Ocean Model Southern Ocean configuration.

Description: Global biogeochemical ocean models help to investigate the present and potential future state of the ocean, its productivity and cascading effects on higher trophic levels such as fish. They are often subjectively tuned against data sets of inorganic tracers and surface chlorophyll and only very rarely against organic components such as particulate organic carbon or zooplankton. The resulting uncertainty in biogeochemical model parameters (and parameterisations) associated with these components can explain some of the large spread of global model solutions with regard to the cycling of organic matter and its impacts on biogeochemical tracer distributions, such as oxygen minimum zones (OMZs). A second source of uncertainty arises from differences in the model spin-up length as, so far, there seems to be no agreement on the required simulation time that should elapse before a global model is assessed against observations. We investigated these two sources of uncertainty by optimising a global biogeochemical ocean model against the root-mean-squared error (RMSE) of six different combinations of data sets and different spin-up times. Besides nutrients and oxygen, the observational data sets also included phyto- and zooplankton, as well as dissolved and particulate organic phosphorus (DOP and POP, respectively). We further analysed the optimised model performance with regard to global biogeochemical fluxes, oxygen inventory and OMZ volume. Following the optimisation procedure, we evaluated the RMSE for all tracers located in the upper 100 m (except for POP, for which we considered the entire vertical domain), regardless of their consideration during optimisation. For the different optimal model solutions, we find a narrow range of the RMSE, between 14 % of the average RMSE after 10 years and 24 % after 3000 years of simulation. Global biogeochemical fluxes, global oxygen bias and OMZ volume showed a much stronger divergence among the models and over time than RMSE, indicating that even models that are similar with regard to local surface tracer concentrations can perform very differently when assessed against the global diagnostics for oxygen. Considering organic tracers in the optimisation had a strong impact on the particle flux exponent (Martin b) and may reduce much of the uncertainty in this parameter and the resulting deep particle flux. Independent of the optimisation setup, the OMZ volume showed a particularly sensitive response with strong trends over time, even after 3000 years of simulation time (despite the constant physical forcing); a high sensitivity to simulation time; and the highest sensitivity to model parameters arising from the tuning strategy setup (variation of almost 80 % of the ensemble mean). In conclusion, calibration against observations of organic tracers can help to improve global biogeochemical models even after short spin-up times; here especially, observations of deep particle flux could provide a powerful constraint. However, a large uncertainty remains with regard to global OMZ volume and its evolution over time, which can show very dynamic behaviour during the model spin-up, which renders temporal extrapolation to a final equilibrium state difficult if not impossible. Given that the real ocean shows variations on many timescales, the assumption of observations representing a steady-state ocean may require some reconsideration.

Description: Open-ocean oxygen minimum zones (OMZs) occur in regions with high biological productivity and weak ventilation. They restrict marine habitats and alter biogeochemical cycles. Global models generally show a large model–data misfit with regard to oxygen. Reliable statements about the future development of OMZs and the quantification of their interaction with climate change are currently not possible. One of the most intense OMZs worldwide is located in the Arabian Sea (AS). We give an overview of the main model deficiencies with a detailed comparison of the historical state of 10 climate models from the 5th Coupled Model Intercomparison Project (CMIP5) that present our present-day understanding of physical and biogeochemical processes. Most of the models show a general underestimation of the OMZ volume in the AS compared to observations that is caused by an overly shallow layer of oxygen-poor water in the models. The deviation of oxygen values in the deep AS is the result of oxygen levels that are too high simulated in the Southern Ocean formation regions of Indian Ocean Deep Water in the models compared to observations and uncertainties in the deepwater mass transport from the Southern Ocean northward into the AS. Differences in simulated water mass properties and ventilation rates of Red Sea Water and Persian Gulf Water cause different mixing in the AS and thus influence the intensity of the OMZ. These differences in ventilation rates also point towards variations in the parameterizations of the overflow from the marginal seas among the models. The results of this study are intended to foster future model improvements regarding the OMZ in the AS.

Description: Observed oxygen minimum zones (OMZs) in the tropical Pacific Ocean are located above intermediate-depth waters (IDWs), defined here as the 500–1500 m water layer. Typical climate models do not represent IDW properties well and are characterized by OMZs that are too deep-reaching. We analyze the role of the IDW in the misrepresentation of oxygen levels in a heterogeneous subset of ocean models characterized by a horizontal resolution ranging from 0.1 to 2.8∘. First, we show that forcing the extratropical boundaries (30∘ S and N) to observed oxygen values results in a significant increase in oxygen levels in the intermediate eastern tropical region. Second, we highlight the fact that the Equatorial Intermediate Current System (EICS) is a key feature connecting the western and eastern part of the basin. Typical climate models lack in representing crucial aspects of this supply at intermediate depth, as the EICS is basically absent in models characterized by a resolution lower than 0.25∘. These two aspects add up to a “cascade of biases” that hampers the correct representation of oxygen levels at intermediate depth in the eastern tropical Pacific Ocean and potentially future OMZ projections.