The ocean has absorbed about 25% of the carbon emitted by humans to date. To better predict how much climate will change, it is critical to understand how this ocean carbon sink will respond to future emissions. Here, we examine the ocean carbon sink response to low emission (SSP1-1.9, SSP1-2.6), intermediate emission (SSP2-4.5, SSP5-3.4-OS), and high emission (SSP5-8.5) scenarios in CMIP6 Earth System Models and in MAGICC7, a reduced-complexity climate carbon system model. From 2020-2100, the trajectory of the global-mean sink approximately parallels the trajectory of anthropogenic emissions. Until emission growth becomes negative, the cumulative ocean carbon sink absorbs 20-30% of cumulative emissions since 2015. In scenarios where emissions decline and become negative, the ocean remains a sink and absorbs more carbon than emitted (up to 120% of cumulative emissions since 2015). Despite similar responses in all models, there remains substantial quantitative spread in estimates of the cumulative sink through 2100 within each scenario, up to 50 PgC in CMIP6 and 120 PgC in the MAGICC7 ensemble. We demonstrate that for all but SSP1-2.6, approximately half of this future spread can be eliminated if models are brought into agreement with modern best-estimates. Considering the spatial distribution of air-sea CO 2 fluxes in CMIP6, we find significant zonal-mean divergence from newly-available observation-based constraints. We conclude that a significant portion of future ocean carbon sink uncertainty is attributable to modern-day errors in the mean state of air-sea CO 2 fluxes, which in turn are associated with model representations of ocean physics and biogeochemistry. Bringing models into agreement with modern observation-based estimates at regional to global scales can substantially reduce uncertainty in future role of the ocean in absorbing anthropogenic CO 2 from the atmosphere and mitigating climate change.

Pinatubo erupted during the first decadal survey of ocean biogeochemistry, embedding its climate fingerprint into foundational ocean biogeochemical observations and complicating the interpretation of long-term biogeochemical change. Here, we quantify the influence of the Pinatubo climate perturbation on externally forced decadal and multi-decadal changes in key ocean biogeochemical quantities using a large ensemble simulation of the Community Earth System Model designed to isolate the effects of Pinatubo, which cleanly captures the ocean biogeochemical response to the eruption. We find increased uptake of apparent oxygen utilization and preindustrial carbon over 1993-2003. Nearly 100\% of the forced response in these quantities are attributable to Pinatubo. The eruption caused enhanced ventilation of the North Atlantic, as evidenced by deep ocean chlorofluorocarbon changes that appear 10-15 years after the eruption. Our results help contextualize observed change and contribute to improved constraints on uncertainty in the global carbon budget and ocean deoxygenation.

The El Niño-Southern Oscillation (ENSO) in the equatorial Pacific is the dominant mode of global air-sea CO2 flux interannual variability (IAV). Air-sea CO2 fluxes are driven by the difference between atmospheric and surface ocean pCO2, with variability of the latter driving flux variability. Previous studies found that models in Coupled Model Intercomparison Project Phase 5 (CMIP5) failed to reproduce the observed ENSO-related pattern of CO2 fluxes and had weak pCO2 IAV, which were explained by both weak upwelling IAV and weak mean vertical DIC gradients. We assess whether the latest generation of CMIP6 models can reproduce equatorial Pacific pCO2 IAV by validating models against observations-based data products. We decompose pCO2 IAV into thermally and non-thermally driven anomalies to examine the balance between these competing anomalies, which explain the total pCO2 IAV. The majority of CMIP6 models underestimate pCO2 IAV, while they overestimate SST IAV. Thermal and non-thermal pCO2 anomalies are not appropriately balanced in models, such that the resulting pCO2 IAV is too weak. We compare the relative strengths of the vertical transport of temperature and DIC and evaluate their contributions to thermal and non-thermal pCO2 anomalies. Model-to-observations-based product comparisons reveal that modeled mean vertical DIC gradients are biased weak relative to their mean vertical temperature gradients, but upwelling acting on these gradients is insufficient to explain the relative magnitudes of thermal and non-thermal pCO2 anomalies.

The ocean has absorbed the equivalent of 39% of industrial-age fossil carbon emissions, significantly modulating the growth rate of atmospheric CO2 and its associated impacts on climate. Despite the importance of the ocean carbon sink to climate, our understanding of the causes of its interannual-to-decadal variability remains limited. This hinders our ability to attribute its past behavior and project its future. A key period of interest is the 1990s, when the ocean carbon sink did not grow as expected. Previous explanations of this behavior have focused on variability internal to the ocean or associated with coupled atmosphere/ocean modes. Here, we use an idealized upper ocean box model to illustrate that two external forcings are sufficient to explain the pattern and magnitude of sink variability since the mid-1980s. First, the global-scale reduction in the decadal-average ocean carbon sink in the 1990s is attributable to the slowed growth rate of atmospheric pCO2. The acceleration of atmospheric pCO2 growth after 2001 drove recovery of the sink. Second, the global sea surface temperature response to the 1991 eruption of Mt Pinatubo explains the timing of the global sink within the 1990s. These results are consistent with previous experiments using ocean hindcast models with and without forcing from variable atmospheric pCO2 and climate variability. The fact that variability in the growth rate of atmospheric pCO2 directly imprints on the ocean sink implies that there will be an immediate reduction in ocean carbon uptake as atmospheric pCO2 responds to cuts in anthropogenic emissions.

The ocean plays a critical role in reducing human impact on the global climate by absorbing and sequestering CO2 from the atmosphere. To quantify the ocean’s role in the global carbon budget, we need surface ocean pCO2 across space and time, but only sparse observations exist. The typical approach to reconstructing pCO2 is to train a machine learning approach on a subset of the pCO2 data and available physical and biogeochemical observations. Though the variables are all related to the pCO2, these approaches are often perceived as black boxes, as it is unclear how inputs are physically linked to pCO2 outputs. Here, we add physics by incorporating our knowledge of the direct effect of temperature on surface ocean pCO2. We use the machine learning algorithm XGBoost to develop a function between satellite and in-situ observations and the difference between observed pCO2 and the pCO2 that would exist if temperature variations were the only driver of variability. We show the resulting model is physically consistent, and performs at least as well as other data approaches. Uncertainty in the reconstructed pCO2 and its impact on the estimated CO2 fluxes are quantified. Uncertainty in piston velocity drives flux uncertainties. The historical reconstructed CO2 fluxes show larger interannual variability than the smoother neural network approaches, but a lesser trend since 2005. We estimate an air-sea flux of -2.3 +/- 0.5 PgC/yr for 1990-2018, agreeing with other data products and the Global Ocean Carbon Budget models of 2021 estimate of -2.3 +/- 0.4 PgC/yr.

The decline in global emissions of carbon dioxide due to the COVID-19 pandemic provides a unique opportunity to investigate the sensitivity of the global carbon cycle and climate system to emissions reductions. Recent efforts to study the response to these emissions declines has not addressed their impact on the ocean, yet ocean carbon absorption is particularly susceptible to changing atmospheric carbon concentrations. Here, we use ensembles of simulations conducted with an Earth system model to explore the potential detection of COVID-related emissions reductions in the partial pressure difference in carbon dioxide between the surface ocean and overlying atmosphere (ΔpCO2), a quantity that is regularly measured. We find a unique fingerprint in global-scale ΔpCO2 that is attributable to COVID and potentially detectable in observations, but only with much larger emissions reductions than those that have been observed to date.

We compare air-sea CO2 exchange in an ensemble of global ocean hindcast models to a suite of observation-based products for 1990-2018. Individual products agree closely for regional fluxes, but individual models vary widely in their regional estimates. Despite their regional divergence, individual models estimate similar global mean fluxes, indicating that significant regional compensation occurs to balance in the global integral. Models diverge most strongly from the observed mean flux in the northern and southern subtropics, despite strong agreement in seasonality. In the Southern Ocean, models estimate a wide range of both mean and seasonality. The ensemble of observation-based products can be used to select the models that best represent the regionally-resolved mean state of air-sea CO2 exchange. Three models are within 3σ of the observed estimates in all regions. With this selected model ensemble, the global mean flux is slightly reduced and its uncertainty is reduced by 35%.

The ocean plays a critical role in reducing the human impact on the climate by absorbing and sequestering CO2. To quantify the ocean carbon sink, surface ocean pCO2; must be estimated across space and time. Sparse in situ pCO2; observations began in the 1980s, thus only global ocean biogeochemical models (GOBMs) have been the basis for quantification of the ocean carbon sink prior to the 1980s. The LDEO-Hybrid Physics Data product (LDEO-HPD) incorporates the physical knowledge within the GOBMs and corrects these estimates to observations. Here, we extend the LDEO-HPD product back to 1959 using a climatology of model-observation misfits. LDEO-HPD is closer to independent observations than unadjusted GOBMs. Most of the improvement from the GOBM prior in LDEO-HPD is attributable to the climatological adjustment, which supports the use of a climatological adjustment prior to 1982. Air-sea CO2; fluxes for 1959-2020 demonstrate response to atmospheric pCO2 growth and volcanic eruptions.

Large volcanic eruptions drive significant climate perturbations through major anomalies in radiative fluxes and the resulting widespread cooling of the surface and upper ocean. Recent studies suggest that these eruptions also drive important variability in air-sea carbon and oxygen fluxes. By simulating the Earth system using two initial-condition large ensembles, with and without the aerosol forcing associated with the Mt. Pinatubo eruption in June 1991, we isolate the impact of this event on ocean physical and biogeochemical properties. The Mt. Pinatubo eruption generated significant anomalies in surface fluxes and the ocean interior inventories of heat, oxygen, and carbon. Pinatubo-driven changes persist for multiple years in the upper ocean and permanently modify the ocean’s heat, oxygen, and carbon inventories. Positive anomalies in oxygen concentrations emerge immediately post-eruption and penetrate into the deep ocean. In contrast, carbon anomalies intensify in the upper ocean over several years post-eruption, and are largely confined to the upper 150 m. In the tropics and northern high latitudes, the change in oxygen is dominated by surface cooling and subsequent ventilation to mid-depths, while the carbon anomaly is associated with solubility changes and eruption-generated ENSO variability. Our results indicate that Pinatubo does not substantially impact oxygen or carbon in the Southern Ocean; forced signals do not emerge from the large internal variability in this region.

The ocean plays a critical role in modulating climate change by sequestering CO2 from the atmosphere. Quantifying the CO2 flux across the air-sea interface requires time-dependent maps of surface ocean partial pressure of CO2 (pCO2), which can be estimated using global ocean biogeochemical models (GOBMs) and observational-based data products. GOBMs are internally consistent, mechanistic representations of the ocean circulation and carbon cycle, and have long been the standard for making spatio-temporally resolved estimates of air-sea CO2 fluxes. However, there are concerns about the fidelity of GOBM flux estimates. Observation-based products have the strength of being data-based, but the underlying data are sparse and require significant extrapolation to create global full-coverage flux estimates. The Lamont Doherty Earth Observatory-Hybrid Physics Data (LDEO-HPD) pCO2 product is a new approach to estimating the temporal evolution of surface ocean pCO2 and air-sea CO2 exchange. LDEO-HPD uses machine learning to merge high-quality observations with state-of-the-art GOBMs. We train an eXtreme Gradient Boosting (XGB) algorithm to learn a non-linear relationship between model-data mismatch and observed predictors. GOBM fields are then corrected with the predicted model-data misfit to estimate real-world pCO2 for 1982-2018. A benefit of this approach is that model-data misfit has reduced temporal skewness compared to the observed pCO2 that is the target variable for other machine-learning based reconstructions. This supports a robust reconstruction by LDEO-HPD that is in better agreement with independent observations than other estimates. LDEO-HPD global ocean uptake of CO2 is in agreement with other products and the Global Carbon Budget 2020.