Despite the importance of the Southern Ocean carbon sink, its response to future atmospheric CO2 perturbations and warming remains highly uncertain. In this study, we use six state-of-the-art Earth system models to assess the response of Southern Ocean air-sea CO2 fluxes (FCO2) to a rapid atmospheric forcing increase and subsequent negative emissions in an idealized carbon dioxide removal reversibility experiment. We find that during positive emissions, the region north of the Polar Front only takes up atmospheric CO2 for 30-50 years before reaching equilibrium; surface stratification and reduction of CO2 solubility with warming diminishes ocean CO2 uptake in this region. In contrast, south of the Polar Front, the upper ocean continues to take up CO2 until the end of positive emissions at 140 years. Sea-ice loss and the accumulation of anthropogenic dissolved inorganic carbon in the upper ocean reduce the upwelling-driven seasonal CO2 outgassing, leading to a stronger Antarctic CO2 sink. CO2 removal triggers a CO2 uptake reduction that slowly converts the Southern Ocean into a CO2 source which persists for at least 50 years post-mitigation. Furthermore, we find that model sensitivity to atmospheric perturbation is closely linked to seasonal FCO2 dynamics. Specifically, models with a thermally dominated pCO2 seasonal cycle exhibit nearly twice the sensitivity to atmospheric perturbations compared to non-thermal models. Our findings further emphasize the necessity of accurate model representation of the seasonal CO2 dynamics for appropriately simulating the future Southern Ocean carbon sink.

The air-sea transfer of carbon dioxide can be viewed as a dynamical system through which atmospheric and oceanic processes push surface waters away from thermodynamic equilibrium, while diffusive gas transfer pulls them back towards local equilibrium. These push/pull processes drive significant sub-seasonal, seasonal, and interannual variability in air-sea carbon fluxes, the quantification of which is critical both for diagnosing the ocean response to fossil fuel emissions and for attempts to mitigate anthropogenic climate disruption through intentional modification of surface ocean biogeochemistry. In this study, we present a new approach for attributing air-sea carbon fluxes to specific mechanisms. The new framework is first applied to the two-box ocean nutrient and carbon cycle model as an illustrative example. Next, the outputs from a regional eddy-resolving model of the Southern Ocean are analyzed. The roles of multiple physical and biogeochemical processes are identified. Decomposition of the seasonal air-sea carbon flux shows the dominant role of biological carbon pumps that are partially compensated by the transport convergence. Finally, the framework is used to diagnose the response to mesoscale iron and alkalinity release, explicitly quantifying transport feedbacks and eventual impacts on net air-sea carbon flux. Ocean carbon transport have divergent influences between iron and alkalinity release, due to opposing near-surface gradients of dissolved inorganic carbon. More broadly, we suggest that our attribution framework may be a useful analytical technique for monitoring natural ocean carbon fluxes and quantifying the impacts of human intervention on the ocean carbon cycle.

The ocean oxygen (O2) inventory has declined in recent decades but the estimates of O2 trend are uncertain due to its sparse and irregular sampling. A refined estimate of deoxygenation rate is developed using machine learning techniques and biogeochemical Argo array. The source data includes historical shipboard (bottle and CTD-O2) profiles from 1965 to 2020 and biogeochemical Argo profiles after 2005. Neural network and random forest algorithms were trained using approximately 80 % of this data and the remaining 20% for validation. The training data is further divided into 5-fold decadal groups to perform cross validation and hyperparameter tuning. Through different combinations of algorithm types and predictor variable sets, an ensemble of gridded monthly O2 datasets was generated with similar skills (root-mean-square error ~ 13-18 micro-mol/kg and R2 ~ 0.9). The largest errors are found in the oxycline and frontal regions with strong lateral and vertical gradients. The mapping was repeated with shipboard data only and with both shipboard and Argo data. The effect of including Argo data on the estimated global deoxygenation trends has a major impact with an 56% increase while reducing the uncertainty by 40% as measured by the ensemble spread. This study demonstrates the importance of new biogeochemical Argo arrays in relatively data-poor regions such as the Southern Ocean.

The ocean oxygen (O2) inventory has declined in recent decades but the estimates of O2 trend is uncertain due to its sparse and irregular sampling. A refined estimate of deoxygenation rate is developed for the North Atlantic basin using machine learning techniques and biogeochemical Argo array. The source data includes 159 thousand historical shipboard (bottle and CTD-O2) profiles from 1965 to 2020 and 17 thousand Argo O2 profiles after 2005. Neural network and random forest algorithms were trained using 80% of this data using different hyperparameters and predictor variable sets. From a total of 240 trained algorithms, 12 high performing algorithms were selected based on their ability to accurately predict the 20% of oxygen data withheld from training. The final product includes gridded monthly O2 ensembles with similar skills (mean bias < 1mol/kg and R2 > 0.95). The reconstruction of basin-scale oxygen inventory shows a moderate increase before 1980 and steep decline after 1990 in agreement with a previous estimate using an optimal interpolation method. However, significant differences exist between reconstructions trained with only shipboard data and with both shipboard and Argo data. The gridded oxygen datasets using only shipboard measurements resulted in a wide spread of deoxygenation trends (0.8-2.7% per decade) during 1990-2010. When both shipboard and Argo were used, the resulting deoxygenation trends converged within a smaller spread (1.4-2.0% per decade). This study demonstrates the importance of new biogeochemical Argo arrays in combination with applications of machine learning techniques.

Earth System Models project a decline of dissolved oxygen in the oceans under warming climate. Observational studies suggest that the ratio of O2 inventory to ocean heat content (O2-OHC) is several fold larger than can be explained by solubility alone, but the ratio remains poorly understood. In this work, models of different complexity are used to understand the factors controlling the O2-OHC ratio during deep convection, with a focus on the Labrador Sea, a site of deep water formation in the North Atlantic Ocean. A simple one-dimensional convective adjustment model suggests two limit case scenarios. When the near-surface oxygen level is dominated by the entrainment of subsurface water, surface buoyancy forcing, air-sea gas exchange coefficient and vertical structure of sea water together affect the O2-OHC ratio. In contrast, vertical gradients of temperature and oxygen become important when the surface oxygen flux dominates. The former describes the O2-OHC ratio of individual convective event in agreement with model simulations of deep convection. The latter captures the O2-OHC ratio of interannual variability, where the pre-conditioning of interior ocean gradients dominates. The relative vertical gradients of temperature and oxygen, which in turn depend on the lateral transport and regional biological productivity, control the year-to-year variations of O2-OHC ratio. These theoretical predictions are tested against the output of a three-dimensional regional circulation and biogeochemistry model which captures the observed large-scale distribution of the O2-OHC ratio, and agrees broadly with the prediction by the simpler model.

Marine ecosystem is influenced by multiple factors under the global warming. Increasing temperature raises the matabolic demand for oxygen, however, its supply declines as the concentration of dissolved oxygen decreases. Metabolic index is defined as the oxygen supply to demand ratio for a marine organism, quantitatively combining the effects of ocean warming and deoxygenation. A subset of the earth system models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) are used to calculate the century-scale changes in the metabolic index under three different scenarios. Under the most aggressive warming scenario, metabolic index can decline over 50\% at northern extratropics including the US west coast. Overall magnitude of the change is dependent on the emission scenarios, whereas spatial patterns are model-dependent, in particular at low latitudes due to the large uncertainty in projected oxygen changes.

Phytoplankton growth in the Indian Ocean is limited by nitrogen and phosphorus in the north and by iron in the south. Increasing anthropogenic atmospheric deposition of nitrogen and dissolved iron (dFe) into the ocean can thus lead to significant responses from the Indian Ocean ecosystems. Previous modeling studies investigated the impacts of anthropogenic nutrient deposition on the ocean, but their results are uncertain due to incomplete representations of the Fe cycling. This study uses a state-of-the-art ocean ecosystem and Fe cycling model to evaluate the transient responses of ocean productivity and carbon uptake in the Indian Ocean, focusing on the centennial time scale. The model includes three major dFe sources and represents an internal Fe cycling modulated by scavenging, desorption, and complexation with multiple, spatially varying ligand classes. Sensitivity simulations show that after a century of anthropogenic deposition, increased dFe input stimulates diatom in the southern Indian Ocean poleward of 50S and the southeastern tropics. However, diatom decreases in the southern Arabian Sea due to the phosphorus limitation, and diatom is outcompeted there by coccolithophores and picoplankton, which have a lower phosphorus demand. These changes in diatom and coccolithophores productions alter the balance between the organic and carbonate pumps in the Indian Ocean, increasing the carbon uptake poleward of 50 S and the southeastern tropics while decreasing it in the Arabian Sea. Our results reveal the important role of ecosystem dynamics in controlling the sensitivity of carbon fluxes in the Indian Ocean under the impact of anthropogenic nutrient deposition.