Oceanic CO2 outgassing and biological production hotspots induced by pre-industrial river loads of nutrients and carbon in a global modeling approach

Rivers are a major source of nutrients, carbon and alkalinity to the global ocean. In this study, we firstly estimate pre-industrial riverine loads of nutrients, carbon and alkalinity based on a hierarchy of weathering and terrestrial organic matter export models, while identifying regional hotspots of the riverine exports. Secondly, we implement the riverine loads into a global ocean biogeochemical model to describe their implications for oceanic nutrient concentrations, net primary production (NPP) and air–sea CO2 fluxes globally, as well as in an analysis of coastal regions. Thirdly, we quantitatively assess the terrestrial origins and the long-term fate of riverine carbon in the ocean. We quantify annual bioavailable pre-industrial riverine loads of 3.7 Tg P, 27 Tg N, 158 Tg Si and 603 Tg C delivered to the ocean globally. We thereby identify the tropical Atlantic catchments (20 % of global C), Arctic rivers (9 % of global C) and Southeast Asian rivers (15 % of global C) as dominant suppliers of carbon for the ocean. The riverine exports lead to a simulated net global oceanic CO2 source of 231 Tg C yr−1 to the atmosphere, which is mainly caused by inorganic carbon (source of 183 Tg C yr−1) and by organic carbon (source of 128 Tg C yr−1) riverine loads. Additionally, a sink of 80 Tg C yr−1 is caused by the enhancement of the biological carbon uptake from dissolved inorganic nutrient inputs from rivers and the resulting alkalinity production. While large outgassing fluxes are simulated mostly in proximity to major river mouths, substantial outgassing fluxes can be found further offshore, most prominently in the tropical Atlantic. Furthermore, we find evidence for the interhemispheric transfer of carbon in the model; we detect a larger relative outgassing flux (49 % of global riverine-induced outgassing) in the Southern Hemisphere in comparison to the hemisphere's relative riverine inputs (33 % of global C inputs), as well as an outgassing flux of 17 Tg C yr−1 in the Southern Ocean. The addition of riverine loads in the model leads to a strong NPP increase in the tropical west Atlantic, Bay of Bengal and the East China Sea (+166 %, +377 % and +71 %, respectively). On the light-limited Arctic shelves, the NPP is not strongly sensitive to riverine loads, but the CO2 flux is strongly altered regionally due to substantial dissolved inorganic and organic carbon supplies to the region. While our study confirms that the ocean circulation remains the main driver for biogeochemical distributions in the open ocean, it reveals the necessity to consider riverine inputs for the representation of heterogeneous features in the coastal ocean and to represent riverine-induced pre-industrial carbon outgassing in the ocean. It also underlines the need to consider long-term CO2 sources from volcanic and shale oxidation fluxes in order to close the framework's atmospheric carbon budget

Incorporating the stable carbon isotope 13C in the ocean biogeochemical component of the Max Planck Institute Earth System Model

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

Current and Future Decadal Trends in the Oceanic Carbon Uptake Are Dominated by Internal Variability

We investigate the internal decadal variability of the ocean carbon uptake using 100 ensemble simulations based on the Max Planck Institute Earth system model (MPI‐ESM). We find that on decadal time scales, internal variability (ensemble spread) is as large as the forced temporal variability (ensemble mean), and the largest internal variability is found in major carbon sink regions, that is, the 50–65°S band of the Southern Ocean, the North Pacific, and the North Atlantic. The MPI‐ESM ensemble produces both positive and negative 10 year trends in the ocean carbon uptake in agreement with observational estimates. Negative decadal trends are projected to occur in the future under RCP4.5 scenario. Due to the large internal variability, the Southern Ocean and the North Pacific require the most ensemble members (more than 53 and 46, respectively) to reproduce the forced decadal trends. This number increases up to 79 in future decades as CO2 emission trajectory changes

Detectability of Artificial Ocean Alkalinization and Stratospheric Aerosol Injection in MPI‐ESM

To monitor the success of carbon dioxide removal (CDR) or solar radiation management (SRM) that offset anthropogenic climate change, the forced response to any external forcing is required to be detectable against internal variability. Thus far, only the detectability of SRM has been examined using both a stationary and nonstationary detection and attribution method. Here, the spatiotemporal detectability of the forced response to artificial ocean alkalinization (AOA) and stratospheric aerosol injection (SAI) as exemplary methods for CDR and SRM, respectively, is compared in Max Planck Institute Earth System Model (MPI-ESM) experiments using regularized optimal fingerprinting and single-model estimates of internal variability, while working under a stationary or nonstationary null hypothesis. Although both experiments are forced by emissions according to the Representative Concentration Pathway 8.5 (RCP8.5) and target the climate of the RCP4.5 scenario using AOA or SAI, detection timescales reflect the fundamentally different forcing agents. Moreover, detectability timescales are sensitive to the choice of null hypothesis. Globally, changes in the CO2 system in seawater are detected earlier than the response in temperature to AOA but later in the case of SAI. Locally, the detection time scales depend on the physical, chemical, and radiative impacts of CDR and SRM forcing on the climate system, as well as patterns of internal variability, which is highlighted for oceanic heat and carbon storage

Microstructure and composition of marine aggregates as co-determinants for vertical particulate organic carbon transfer in the global ocean

Marine aggregates are the vector for biogenically bound carbon and nutrients from the euphotic zone to the interior of the oceans. To improve the representation of this biological carbon pump in the global biogeochemical HAMburg Ocean Carbon Cycle (HAMOCC) model, we implemented a novel Microstructure, Multiscale, Mechanistic, Marine Aggregates in the Global Ocean (M4AGO) sinking scheme. M4AGO explicitly represents the size, microstructure, heterogeneous composition, density and porosity of aggregates and ties ballasting mineral and particulate organic carbon (POC) fluxes together. Additionally, we incorporated temperature-dependent remineralization of POC. We compare M4AGO with the standard HAMOCC version, where POC fluxes follow a Martin curve approach with (i) linearly increasing sinking velocity with depth and (ii) temperature-independent remineralization. Minerals descend separately with a constant speed. In contrast to the standard HAMOCC, M4AGO reproduces the latitudinal pattern of POC transfer efficiency, as recently constrained by Weber et al. (2016). High latitudes show transfer efficiencies of ≈0.25±0.04, and the subtropical gyres show lower values of about 0.10±0.03. In addition to temperature as a driving factor for remineralization, diatom frustule size co-determines POC fluxes in silicifier-dominated ocean regions, while calcium carbonate enhances the aggregate excess density and thus sinking velocity in subtropical gyres. Prescribing rising carbon dioxide (CO2) concentrations in stand-alone runs (without climate feedback), M4AGO alters the regional ocean atmosphere CO2 fluxes compared to the standard model. M4AGO exhibits higher CO2 uptake in the Southern Ocean compared to the standard run, while in subtropical gyres, less CO2 is taken up. Overall, the global oceanic CO2 uptake remains the same. With the explicit representation of measurable aggregate properties, M4AGO can serve as a test bed for evaluating the impact of aggregate-associated processes on global biogeochemical cycles and, in particular, on the biological carbon pump

Rapid emergence of climate change in environmental drivers of marine ecosystems

Climate change is expected to modify ecological responses in the ocean, with the potential for important effects on the ecosystem services provided to humankind. Here we address the question of how rapidly multiple drivers of marine ecosystem change develop in the future ocean. By analysing an ensemble of models we find that, within the next 15 years, the climate change-driven trends in multiple ecosystem drivers emerge from the background of natural variability in 55% of the ocean and propagate rapidly to encompass 86% of the ocean by 2050 under a ‘business-as-usual’ scenario. However, we also demonstrate that the exposure of marine ecosystems to climate change-induced stress can be drastically reduced via climate mitigation measures; with mitigation, the proportion of ocean susceptible to multiple drivers within the next 15 years is reduced to 34%. Mitigation slows the pace at which multiple drivers emerge, allowing an additional 20 years for adaptation in marine ecological and socio-economic systems alike