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The Southern Ocean between 30°S and 55°S is a major sink of excess heat and anthropogenic carbon, but model projections of these sinks remain highly uncertain. Reducing such uncertainties is required to effectively guide the development of climate mitigation policies for meeting the ambitious climate targets of the Paris Agreement. Here, we show that the large spread in the projections of future excess heat uptake efficiency and cumulative anthropogenic carbon uptake in this region are strongly linked to the models’ contemporary stratification. This relationship is robust across two generations of Earth system models and is used to reduce the uncertainty of future estimates of the cumulative anthropogenic carbon uptake by up to 53% and the excess heat uptake efficiency by 28%. Our results highlight that, for this region, an improved representation of stratification in Earth system models is key to constrain future carbon budgets and climate change projections.

Robust detection of anthropogenic climate change is crucial to: (i) improve our understanding of Earth system responses to external forcing, (ii) reduce uncertainty in future climate projections, and (iii) develop efficient mitigation and adaptation plans. Here, we use Earth system model projections to establish the detection timescales of anthropogenic signals in the global ocean through analyzing temperature, salinity, oxygen, and pH evolution from surface to 2000 m depths. For most variables, anthropogenic changes emerge earlier in the interior ocean than at the surface, due to the lower background variability at depth. Acidification is detectable earliest, followed by warming and oxygen changes in the subsurface tropical Atlantic. Temperature and salinity changes in the subsurface tropical and subtropical North Atlantic are shown to be early indicators for a slowdown of the Atlantic Meridional Overturning Circulation. Even under mitigated scenarios, inner ocean anthropogenic signals are projected to emerge within the next few decades. This is because they originate from existing surface changes that are now propagating into the interior. In addition to the tropical Atlantic, our study calls for establishment of long-term interior monitoring systems in the Southern Ocean and North Atlantic in order to elucidate how spatially heterogeneous anthropogenic signals propagate into the interior and impact marine ecosystems and biogeochemistry.

The magnitude and evolution of parameters that characterize feedbacks in the coupled carbon–climate system are compared across nine Earth system models (ESMs). The analysis is based on results from biogeochemically, radiatively, and fully coupled simulations in which CO₂ increases at a rate of 1% yr−1. These simulations are part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CO₂ fluxes between the atmosphere and underlying land and ocean respond to changes in atmospheric CO₂ concentration and to changes in temperature and other climate variables. The carbon–concentration and carbon–climate feedback parameters characterize the response of the CO₂ flux between the atmosphere and the underlying surface to these changes. Feedback parameters are calculated using two different approaches. The two approaches are equivalent and either may be used to calculate the contribution of the feedback terms to diagnosed cumulative emissions. The contribution of carbon–concentration feedback to diagnosed cumulative emissions that are consistent with the 1% increasing CO₂ concentration scenario is about 4.5 times larger than the carbon–climate feedback. Differences in the modeled responses of the carbon budget to changes in CO₂ and temperature are seen to be 3–4 times larger for the land components compared to the ocean components of participating models. The feedback parameters depend on the state of the system as well the forcing scenario but nevertheless provide insight into the behavior of the coupled carbon–climate system and a useful common framework for comparing models.

Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1 % yr−1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm−1) and ocean (0.79 ± 0.07 PgC ppm−1), while the carbon–climate feedback over land (−45.1 ± 50.6 PgC ∘C−1) is about 3 times larger than over ocean (−17.2 ± 5.0 PgC ∘C−1). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 ∘C EgC−1 and is similar to that found in CMIP5 models (1.63 ± 0.48 ∘C EgC−1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

The ocean ecosystem is a vital component of the global carbon cycle, storing enough carbon to keep atmospheric CO 2 considerably lower than it would otherwise be. However, this conception is based on simple models, neglecting the coupled land-ocean feedback. Using an interactive Earth system model, we show that the role ocean biology plays in controlling atmospheric CO 2 is more complex than previously thought. Atmospheric CO 2 in a new equilibrium state after the biological pump is shut down increases by more than 50% (163 ppm), lower than expected as approximately half the carbon lost from the ocean is adsorbed by the land. The abiotic ocean is less capable of taking up anthropogenic carbon due to the warmer climate, an absent biological surface pCO 2 deficit and a higher Revelle factor. Prioritizing research on and preserving marine ecosystem functioning would be crucial to mitigate climate change and the risks associated with it. A new study reveals that the ocean biological pump plays a vital role in maintaining low atmospheric CO2 levels and facilitating efficient future anthropogenic carbon sinks. Without it, climate change would occur at an amplified and accelerated rate.

About 25% of the emitted anthropogenic CO2 is absorbed by the ocean and transported to the interior through key gateways, such as the Southern Ocean or the North Atlantic. Over the next few centuries, anthropogenic CO2 is then redistributed by ocean circulation and stored mostly in the upper layers of the subtropical gyres. Because of the combined effects of (i) weakening buffering capacity, (ii) warming-induced lower solubility, (iii) changes in wind stress and (iv) changes in ocean circulation, there is a high confidence that the ocean sink will weaken in the future. Here, we use IPCC-class Earth System Model (ESM) simulations following the SSP1-2.6 and SSP5-8.5 climate change scenarios extended to the year 2300 to reveal that anthropogenic CO2 begins to outgas in the subtropical gyres of both hemispheres during the summer months of the 21st century. In 2100, about 53% of the surface ocean experience outgassing at least one month in a year in SSP1-2.6, against 37% in SSP5-8.5. After 2100, this fraction keeps increasing, reaching 63% by 2300 in SSP5-8.5 while stabilizing at 55% in SSP1-2.6. This outgassing pattern is driven by the rapid increase in oceanic pCO2, faster than the atmospheric pCO2, due to the combined effect of both rapid warming and long-term accumulation of anthropogenic carbon in these regions. These findings call for increased observation efforts in these areas, particularly in the subtropical gyres of the Southern Hemisphere, in order to detect future release of anthropogenic carbon and accurately constrain the future carbon budget.

Anthropogenic climate change is projected to lead to ocean warming, acidification, deoxygenation, reductions in near-surface nutrients, and changes to primary production, all of which are expected to affect marine ecosystems. Here we assess projections of these drivers of environmental change over the twenty-first century from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) that were forced under the CMIP6 Shared Socioeconomic Pathways (SSPs). Projections are compared to those from the previous generation (CMIP5) forced under the Representative Concentration Pathways (RCPs). A total of 10 CMIP5 and 13 CMIP6 models are used in the two multi-model ensembles. Under the high-emission scenario SSP5-8.5, the multi-model global mean change (2080–2099 mean values relative to 1870–1899) ± the inter-model SD in sea surface temperature, surface pH, subsurface (100–600 m) oxygen concentration, euphotic (0–100 m) nitrate concentration, and depth-integrated primary production is +3.47±0.78 ∘C, -0.44±0.005, -13.27±5.28, -1.06±0.45 mmol m−3 and -2.99±9.11 %, respectively. Under the low-emission, high-mitigation scenario SSP1-2.6, the corresponding global changes are +1.42±0.32 ∘C, -0.16±0.002, -6.36±2.92, -0.52±0.23 mmol m−3, and -0.56±4.12 %. Projected exposure of the marine ecosystem to these drivers of ocean change depends largely on the extent of future emissions, consistent with previous studies. The ESMs in CMIP6 generally project greater warming, acidification, deoxygenation, and nitrate reductions but lesser primary production declines than those from CMIP5 under comparable radiative forcing. The increased projected ocean warming results from a general increase in the climate sensitivity of CMIP6 models relative to those of CMIP5. This enhanced warming increases upper-ocean stratification in CMIP6 projections, which contributes to greater reductions in upper-ocean nitrate and subsurface oxygen ventilation. The greater surface acidification in CMIP6 is primarily a consequence of the SSPs having higher associated atmospheric CO2 concentrations than their RCP analogues for the same radiative forcing. We find no consistent reduction in inter-model uncertainties, and even an increase in net primary production inter-model uncertainties in CMIP6, as compared to CMIP5.

Ongoing greenhouse gas emissions can modify climate processes and induce shifts in ocean temperature, pH, oxygen concentration, and productivity, which in turn could alter biological and social systems. Here, we provide a synoptic globalassessment of the simultaneous changes in future ocean biogeochemical variables over marine biota and their broader implications for people. We analyzed modern Earth System Models forced by greenhouse gas concentration pathways until 2100 and showed that the entire world’s ocean surface will be simultaneously impacted by varying intensities of ocean warming, acidification, oxygen depletion, or shortfalls in productivity. In contrast, only a small fraction of the world’s ocean surface, mostly in polar regions, will experience increased oxygenation and productivity, while almost nowhere will there be ocean cooling or pH elevation. We compiled the global distribution of 32 marine habitats and biodiversity hotspots and found that they would all experience simultaneous exposure to changes in multiple biogeochemical variables. This superposition highlights the high risk for synergistic ecosystem responses, the suite of physiological adaptations needed to cope with future climate change, and the potential for reorganization of global biodiversity patterns. If co-occurring biogeochemical changes influence the delivery of ocean goods and services, then they could also have a considerable effect on human welfare. Approximately 470 to 870 million of the poorest people in the world rely heavily on the ocean for food, jobs, and revenues and live in countries that will be most affected by multaneous changes in ocean biogeochemistry. These results highlight the high risk of degradation of marine ecosystems and associated human hardship expected in a future following current trends in anthropogenic greenhouse gas emissions.

The ocean carbon cycle is a key player in the climate system through its role in regulating the atmospheric carbon dioxide concentration and other processes that alter the Earth's radiative balance. In the second version of the Norwegian Earth System Model (NorESM2), the oceanic carbon cycle component has gone through numerous updates that include, amongst others, improved process representations, increased interactions with the atmosphere, and additional new tracers. Oceanic dimethyl sulfide (DMS) is now prognostically simulated and its fluxes are directly coupled with the atmospheric component, leading to a direct feedback to the climate. Atmospheric nitrogen deposition and additional riverine inputs of other biogeochemical tracers have recently been included in the model. The implementation of new tracers such as “preformed” and “natural” tracers enables a separation of physical from biogeochemical drivers as well as of internal from external forcings and hence a better diagnostic of the simulated biogeochemical variability. Carbon isotope tracers have been implemented and will be relevant for studying long-term past climate changes. Here, we describe these new model implementations and present an evaluation of the model's performance in simulating the observed climatological states of water-column biogeochemistry and in simulating transient evolution over the historical period. Compared to its predecessor NorESM1, the new model's performance has improved considerably in many aspects. In the interior, the observed spatial patterns of nutrients, oxygen, and carbon chemistry are better reproduced, reducing the overall model biases. A new set of ecosystem parameters and improved mixed layer dynamics improve the representation of upper-ocean processes (biological production and air–sea CO2 fluxes) at seasonal timescale. Transient warming and air–sea CO2 fluxes over the historical period are also in good agreement with observation-based estimates. NorESM2 participates in the Coupled Model Intercomparison Project phase 6 (CMIP6) through DECK (Diagnostic, Evaluation and Characterization of Klima) and several endorsed MIP simulations.

The contributions of species to ecosystem functions or services depend not only on their presence but also on their local abundance. Progress in predictive spatial modelling has largely focused on species occurrence rather than abundance. As such, limited guidance exists on the most reliable methods to explain and predict spatial variation in abundance. We analysed the performance of 68 abundance‐based species distribution models fitted to 800 000 standardised abundance records for more than 800 terrestrial bird and reef fish species. We found a large amount of variation in the performance of abundance‐based models. While many models performed poorly, a subset of models consistently reconstructed range‐wide abundance patterns. The best predictions were obtained using random forests for frequently encountered and abundant species and for predictions within the same environmental domain as model calibration. Extending predictions of species abundance outside of the environmental conditions used in model training generated poor predictions. Thus, interpolation of abundances between observations can help improve understanding of spatial abundance patterns, but our results indicate extrapolated predictions of abundance under changing climate have a much greater uncertainty. Our synthesis provides a road map for modelling abundance patterns, a key property of species distributions that underpins theoretical and applied questions in ecology and conservation.