Posts Tagged 'globalmodeling'

Early detection of anthropogenic climate change signals in the ocean interior

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.

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Alkalinity biases in CMIP6 Earth System Models and implications for simulated CO2 drawdown via artificial alkalinity enhancement

The partitioning of CO2 between atmosphere and ocean depends to a large degree not only on the amount of dissolved inorganic carbon (DIC) but also of alkalinity in the surface ocean. That is also why, in the context of negative emission approaches ocean alkalinity enhancement is discussed as one potential approach. Although alkalinity is thus an important variable of the marine carbonate system little knowledge exists how its representation in models compares with measurements. We evaluated the large-scale alkalinity distribution in 14 CMIP6 models against the observational data set GLODAPv2 and showed that most models as well as the multi-model-mean underestimate alkalinity at the surface and in the upper ocean, while overestimating alkalinity in the deeper ocean. The decomposition of the global mean alkalinity biases into contributions from physical processes (preformed alkalinity), remineralization, and carbonate formation and dissolution showed that the bias stemming from the physical redistribution of alkalinity is dominant. However, below the upper few hundred meters the bias from carbonate dissolution can become similarly important as physical biases, while the contribution from remineralization processes is negligible. This highlights the critical need for better understanding and quantification of processes driving calcium carbonate dissolution in microenvironments above the saturation horizons, and implementation of these processes into biogeochemical models.

For the application of the models to assess the potential of ocean alkalinity enhancement to increase ocean carbon uptake and counteract ocean acidification, a back-of-the-envelope calculation was conducted with each model’s global mean surface alkalinity and DIC as input parameters. We find that the degree of compensation of DIC and alkalinity biases at the surface is more important for the marine CO2 uptake capacity than the alkalinity biases themselves. The global mean surface alkalinity bias relative to GLODAPv2 in the different models ranges from -85 mmol kg-1 (-3.6 %) to +50 mmol kg-1 (+2.1 %) (mean: -25 mmol kg-1 or -1.1 %), while for DIC the relative bias ranges from -55 mmol kg-1 (-2.6 %) to 53 mmol kg-1 (+2.5 %) (mean: -13 mmol kg-1 or -0.6 %). Because of this partial compensation, all but two of the CMIP6 models evaluated here overestimate the Revelle factor at the surface and thus overestimate the CO2-draw-down after alkalinity addition by up to 13 % and pH increase by up to 7.2 %. This overestimate has to be taken into account when reporting on efficiencies of ocean alkalinity enhancement experiments using CMIP6 models.

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Long-term slowdown of ocean carbon uptake by alkalinity dynamics

Abstract

Oceanic absorption of atmospheric carbon dioxide (CO2) is expected to slow down under increasing anthropogenic emissions; however, the driving mechanisms and rates of change remain uncertain, limiting our ability to project long-term changes in climate. Using an Earth system simulation, we show that the uptake of anthropogenic carbon will slow in the next three centuries via reductions in surface alkalinity. Warming and associated changes in precipitation and evaporation intensify density stratification of the upper ocean, inhibiting the transport of alkaline water from the deep. The effect of these changes is amplified three-fold by reduced carbonate buffering, making alkalinity a dominant control on CO2 uptake on multi-century timescales. Our simulation reveals a previously unknown alkalinity-climate feedback loop, amplifying multi-century warming under high emission trajectories.

Key Points

  • Oceanic uptake of carbon could slow in upcoming centuries through previously unidentified alkalinity-climate feedback
  • Reduced upwelling and carbonate buffer enhance the influence of alkalinity on the increase in surface ocean carbon dioxide
  • Reductions in surface alkalinity will reduce the rate of carbon uptake on multi-century timescales
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Recent trends and variability in the oceanic storage of dissolved inorganic carbon

Several methods have been developed to quantify the oceanic accumulation of anthropogenic carbon dioxide (CO2) in response to rising atmospheric CO2. Yet, we still lack a corresponding estimate of the changes in the total oceanic dissolved inorganic carbon (DIC). In addition to the increase in anthropogenic CO2, changes in DIC also include alterations of natural CO2. Once integrated globally, changes in DIC reflect the net oceanic sink for atmospheric CO2, complementary to estimates of the air-sea CO2 exchange based on surface measurements. Here, we extend the MOBO-DIC machine learning approach by Keppler et al. (2020a) to estimate global monthly fields of DIC at 1° resolution over the top 1500 m from 2004 through 2019. We find that over these 16 years and extrapolated to cover the whole global ocean down to 4000 m, the oceanic DIC pool increased close to linearly at an average rate of 3.2+/-0.7 Pg C yr^-1. This trend is statistically indistinguishable from current estimates of the oceanic uptake of anthropogenic CO2 over the same period. Thus, our study implies no detectable net loss or gain of natural CO2 by the ocean, albeit the large uncertainties could be masking it. Our reconstructions suggest substantial internal redistributions of natural oceanic CO2, with a shift from the mid-latitudes to the tropics and from the surface to below 200 m. Such redistributions correspond with the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation. The interannual variability of DIC is strongest in the tropical Western Pacific, consistent with the El Nino Southern Oscillation.

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Climate-driven changes of global marine mercury cycles in 2100

Significance

One concern caused by the changes in the ocean due to climate change is the potential increase of neurotoxic methylmercury content in seafood. This work quantifies the impact of global change factors on marine mercury cycles. The air–sea exchange is influenced by wind speed weakening and solubility drop of mercury due to seawater warming. The decreased biological pump shrinks the methylation substrate and causes weaker methylation. The advantageous light environment resulting from less attenuation by sea ice and phytoplankton increases the photodegradation potential for seawater methylmercury. Responses of seawater methylmercury can propagate to biota, which is also modulated by the changes in anthropogenic emissions and ocean ecology. Our results offer insight into interactions among different climate change stressors.

Abstract

Human exposure to monomethylmercury (CH3Hg), a potent neurotoxin, is principally through the consumption of seafood. The formation of CH3Hg and its bioaccumulation in marine food webs experience ongoing impacts of global climate warming and ocean biogeochemistry alterations. Employing a series of sensitivity experiments, here we explicitly consider the effects of climate change on marine mercury (Hg) cycling within a global ocean model in the hypothesized twenty-first century under the business-as-usual scenario. Even though the overall prediction is subjected to significant uncertainty, we identify several important climate change impact pathways. Elevated seawater temperature exacerbates elemental Hg (Hg0) evasion, while decreased surface wind speed reduces air–sea exchange rates. The reduced export of particulate organic carbon shrinks the pool of potentially bioavailable divalent Hg (HgII) that can be methylated in the subsurface ocean, where shallower remineralization depth associated with lower productivity causes impairment of methylation activity. We also simulate an increase in CH3Hg photodemethylation potential caused by increased incident shortwave radiation and less attenuation by decreased sea ice and chlorophyll. The model suggests that these impacts can also be propagated to the CH3Hg concentration in the base of the marine food web. Our results offer insight into synergisms/antagonisms in the marine Hg cycling among different climate change stressors.

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Ocean acidification in emission-driven temperature stabilization scenarios: the role of TCRE and non-CO2 greenhouse gases

Future ocean acidification mainly depends on the continuous ocean uptake of CO2 from the atmosphere. The trajectory of future atmospheric CO2 is prescribed in traditional climate projections with Earth System Models, leading to a small model spread and apparently low uncertainties for projected acidification, but a large spread in global warming. However, climate policies such as the Paris Agreement define climate targets in terms of global warming levels and as traditional simulations do not converge to a given warming level, they cannot be used to assess uncertainties in projected acidification for these warming levels. Here, we perform climate simulations that converge to given temperature levels using the Adaptive Emission Reduction Algorithm (AERA) with the Earth System Model Bern3D-LPX at different setups with different transient climate response to cumulative carbon emissions (TCRE) and choices between reductions in CO2 and non-CO2 forcing agents. With these simulations, we demonstrate that uncertainties in surface ocean acidification are an order of magnitude larger than the usually reported inter-model uncertainties from simulations with prescribed atmospheric CO2. Uncertainties in acidification at a given stabilized temperature are dominated by TCRE and the choice of emission reductions of non-CO2 greenhouse gases. High TCRE and relatively low reductions of non-CO2 greenhouse gases, for example, necessitate relatively strong reductions in CO2 emissions and lead to relatively little ocean acidification at a given temperature level. The results suggest that choices between reducing emissions of CO2 versus non-CO2 agents should consider the economic costs and ecosystem damage of ocean acidification.

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Limits and CO2 equilibration of near-coast alkalinity enhancement

Ocean alkalinity enhancement (OAE) has recently gained attention as a potential method for carbon dioxide removal (CDR) at gigatonne (Gt) scale, with near-coast OAE operations being economically favorable due to proximity to mineral and energy sources. In this paper we study critical questions which determine the scale and viability of OAE. Which coastal locations are able to sustain a large flux of alkalinity at minimal pH and ΩArag (aragonite saturation) changes? What is the interference distance between adjacent OAE projects? How much CO2 is absorbed per unit of alkalinity added? How quickly does the induced CO2 deficiency equilibrate with the atmosphere? Choosing relatively conservative constraints on ΔpH or ΔOmega, we examine the limits of OAE using the ECCO LLC270 (0.3) global circulation model. We find that the sustainable OAE rate varies over 1–2 orders of magnitude between different coasts and exhibits complex patterns and non-local dependencies which vary from region to region. In general, OAE in areas of strong coastal currents enables the largest fluxes and depending on the direction of these currents, neighboring OAE sites can exhibit dependencies as far as 400 km or more. At these steady state fluxes most regional stretches of coastline are able to accommodate on the order of 10s to 100s of megatonnes of negative emissions within 300 km of the coast. We conclude that near-coastal OAE has the potential to scale globally to several Gt CO2 yr−1 of drawdown with conservative pH constraints, if the effort is spread over the majority of available coastlines. Depending on the location, we find a diverse set of equilibration kinetics, determined by the interplay of gas exchange and surface residence time. Most locations reach an uptake efficiency plateau of 0.6–0.8 mol CO2 per mol of alkalinity after 3–4 years, after which there is only slow additional CO2 uptake. Regions of significant downwelling (e.g., around Iceland) should be avoided by OAE deployments, as in such locations up to half of the CDR potential of OAE can be lost to bottom waters. The most ideal locations, reaching a molar uptake ratio of around 0.8, include North Madagascar, California, Brazil, Peru and locations close to the Southern Ocean such as Tasmania, Kerguelen and Patagonia, where the gas exchange appears to occur faster than the surface residence time. However, some locations (e.g., Hawaii) take significantly longer to equilibrate (up to 8–10 years) but can still eventually achieve high uptake ratios.

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Pathfinder v1.0.1: a Bayesian-inferred simple carbon–climate model to explore climate change scenarios

The Pathfinder model was developed to fill a perceived gap within the range of existing simple climate models. Pathfinder is a compilation of existing formulations describing the climate and carbon cycle systems, chosen for their balance between mathematical simplicity and physical accuracy. The resulting model is simple enough to be used with Bayesian inference algorithms for calibration, which enables assimilation of the latest data from complex Earth system models and the IPCC sixth assessment report, as well as a yearly update based on observations of global temperature and atmospheric CO2. The model’s simplicity also enables coupling with integrated assessment models and their optimization algorithms or running the model in a backward temperature-driven fashion. In spite of this simplicity, the model accurately reproduces behaviours and results from complex models – including several uncertainty ranges – when run following standardized diagnostic experiments. Pathfinder is an open-source model, and this is its first comprehensive description.

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Ocean biogeochemical modelling

Ocean biogeochemical models describe the ocean’s circulation, physical properties, biogeochemical properties and their transformations using coupled differential equations. Numerically approximating these equations enables simulation of the dynamic evolution of the ocean state in realistic global or regional spatial domains, across time spans from years to centuries. This Primer explains the process of model construction and the main characteristics, advantages and drawbacks of different model types, from the simplest nutrient–phytoplankton–zooplankton–detritus model to the complex biogeochemical models used in Earth system modelling and climate prediction. Commonly used metrics for model-data comparison are described, alongside a discussion of how models can be informed by observations via parameter optimization or state estimation, the two main methods of data assimilation. Examples illustrate how these models are used for various practical applications, ranging from carbon accounting, ocean acidification, ocean deoxygenation and fisheries to observing system design. Access points are provided, enabling readers to engage in biogeochemical modelling through practical code examples and a comprehensive list of publicly available models and observational data sets. Recommendations are given for best practices in model archiving. Lastly, current limitations and anticipated future developments and challenges of the models are discussed.

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Neural networks and the seawater CO2 system. From the global ocean to the Ría de Vigo

This doctoral dissertation is structured in six chapters and two appendices. From this point the reader is warned about the independent numbering in each chapter, both for sections and subsections as well as for figures and tables, that is, the numbering restarts at the beginning of each chapter. Chapter I is divided into two parts. On the one hand, the topic of the doctoral dissertation is introduced in a general way to put in context the different research studies that are part of it. This introduction presents the key concepts on climate change and ocean acidification necessary to approach the reading of the following chapters. On the other hand, the main and secondary objectives that are addressed in the next chapters are detailed. Chapter II develops the construction of a global and seasonal climatology of total alkalinity. The chapter details for the first time in the thesis the use of neural networks. This methodology is used throughout the manuscript, highlighting the peculiarities associated with each study in each of the chapters where it is applied. This chapter has been published in Earth System Science Data: https://doi.org/10.5194/essd-11-1109-2019 Chapter III describes the development of a total dissolved inorganic carbon climatology. In general terms, a methodology similar to that of chapter II is used, although with certain relevant nuances such as the inclusion of a new database. In this chapter, a pCO2 climatology is also generated in a secondary way to evaluate the consistency between the two climatologies previously generated in this thesis. This chapter has been published in Earth System Science Data: https://doi.org/10.5194/essd-12-1725-2020.


Chapter IV completely changes the scale of the previous two chapters and focuses on the study of sweater CO2 chemistry system on a regional scale. Specifically, neural networks are used to generate time series of total alkalinity and pH at various locations in the Ría de Vigo. From the time series, the magnitude of seasonal variability and interannual trends for these variables are analyzed. This chapter has been published in Biogeosciences Discussions: https://doi.org/10.5194/bg-2021-33, 2021 Chapter V contains an analysis of the variability of the hydrogen ion concentration and the aragonite saturation state in the Ría de Vigo. This analysis is carried out from the time series of these variables that are constructed thanks to the study developed in chapter IV. Chapters II to V are structured in the same way as a typical scientific article, thus containing an introduction, methodology, results, discussion and conclusions about each study. Finally, chapter VI summarizes the main conclusions derived from the complete work shown through this doctoral thesis. It is worth noting the inclusion of two appendices in the final part of the thesis. Appendix I details the meaning of each of the acronyms, abbreviations and symbols used throughout the manuscript. Appendix II contains a summary of the doctoral dissertation in Spanish

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SURFER v2.0: a flexible and simple model linking anthropogenic CO2 emissions and solar radiation modification to ocean acidification and sea level rise

We present SURFER, a novel reduced model for estimating the impact of CO2 emissions and solar radiation modification options on sea level rise and ocean acidification over timescales of several thousands of years. SURFER has been designed for the analysis of CO2 emission and solar radiation modification policies, for supporting the computation of optimal (CO2 emission and solar radiation modification) policies and for the study of commitment and responsibility under uncertainty. The model is based on a combination of conservation laws for the masses of atmospheric and oceanic carbon and for the oceanic temperature anomalies, and of ad-hoc parameterisations for the different sea level rise contributors: ice sheets, glaciers and ocean thermal expansion. It consists of 9 loosely coupled ordinary differential equations, is understandable, fast and easy to modify and calibrate. It reproduces the results of more sophisticated, high-dimensional earth system models on timescales up to millennia.

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Assessing the future carbon budget through the lens of policy-driven acidification and temperature targets

Basing a future carbon budget on warming targets is subject to uncertainty due to uncertainty in the relationship between carbon emissions and warming, and may not prevent dangerous change throughout the entire climate system. Here, we use a climate emulator to constrain a future carbon budget that is more representative by using a combination of both warming and ocean acidification targets. The warming targets considered are the Paris Agreement targets of 1.5 and 2°C; the acidification targets are -0.17 and -0.21 pH units informed by aragonite saturation states. Considering acidification targets in conjunction with warming targets is found to narrow the uncertainty in the future carbon budget, especially in situations where the acidification target is more stringent than, or of similar stringency to, the warming target. Considering a strict combination of the two more stringent targets (both targets of 1.5°C warming and -0.17 acidification must be met), the carbon budget ranges from -74.0 to 129.8PgC. This reduces uncertainty in the carbon budget from 286.2PgC to 203.8PgC (29%). Assuming an emissions rate held constant since 2021 (which is a conservative assumption), the budget towards both targets was either spent by 2019, or will be spent by 2026.

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The representation of alkalinity and the carbonate pump from CMIP5 to CMIP6 ESMs and implications for the ocean carbon cycle

Ocean alkalinity is critical to the uptake of atmospheric carbon in surface waters and provides buffering capacity towards associated acidification. However, unlike dissolved inorganic carbon (DIC), alkalinity is not directly impacted by anthropogenic carbon emissions. Within the context of projections of future ocean carbon uptake and potential ecosystem impacts, especially through Coupled Model Intercomparison Projects (CMIPs), the representation of alkalinity and the main driver of its distribution in the ocean interior, the calcium carbonate cycle, have often been overlooked. Here we track the changes from CMIP5 to CMIP6 with respect to the Earth system model (ESM) representation of alkalinity and the carbonate pump which depletes the surface ocean in alkalinity through biological production of calcium carbonate, and releases it at depth through export and dissolution. We report a significant improvement in the representation of alkalinity in CMIP6 ESMs relative to those in CMIP5. This improvement can be explained in part by an increase in calcium carbonate (CaCO3) production for some ESMs, which redistributes alkalinity at the surface and strengthens its vertical gradient in the water column. We were able to constrain a PIC export estimate of 51–70 Tmol yr-1 at 100 m for the ESMs to match the observed vertical gradient of alkalinity. Biases in the vertical profile of DIC have also significantly decreased, especially with the enhancement of the carbonate pump, but the representation of the saturation horizons has slightly worsened in contrast. Reviewing the representation of the CaCO3 cycle across CMIP5/6, we find a substantial range of parameterizations. While all biogeochemical models currently represent pelagic calcification, they do so implicitly, and they do not represent benthic calcification. In addition, most models simulate marine calcite but not aragonite. In CMIP6 certain model groups have increased the complexity of simulated CaCO3 production, sinking, dissolution and sedimentation. However, this is insufficient to explain the overall improvement in the alkalinity representation, which is therefore likely a result of improved marine biogeochemistry model tuning or ad hoc parameterizations. We find differences in the way ocean alkalinity is initialized that lead to offsets of up to 1 % in the global alkalinity inventory of certain models. These initialization biases should be addressed in future CMIPs by adopting accurate unit conversions. Although modelers aim to balance the global alkalinity budget in ESMs in order to limit drift in ocean carbon uptake under preindustrial conditions, varying assumptions in the closure of the budget have the potential to influence projections of future carbon uptake. For instance, in many models, carbonate production, dissolution and burial are independent of the seawater saturation state, and when considered, the range of sensitivities is substantial. As such, the future impact of ocean acidification on the carbonate pump, and in turn ocean carbon uptake, is potentially underestimated in current ESMs and insufficiently constrained.

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Modified future diurnal variability of the global surface ocean CO2 system

Our understanding of how increasing atmospheric CO2 and climate change influences the marine CO2 system and in turn ecosystems, has increasingly focussed on perturbations to carbonate chemistry variability. This variability can affect ocean-climate feedbacks and has been shown to influence marine ecosystems. The seasonal variability of the ocean CO2 system has already changed, with enhanced seasonal variations in the surface ocean pCO2 over recent decades and further amplification projected by models over the 21st century. Mesocosm studies and CO2 vent sites indicate that diurnal variability of the CO2 system, the amplitude of which in extreme events can exceed that of mean seasonal variability, is also likely to be altered by climate change. Here we modified a global ocean biogeochemical model to resolve physically and biologically driven diurnal variability of the ocean CO2 system. Forcing the model with 3-hourly atmospheric outputs derived from an Earth system model, we explore how surface ocean diurnal variability responds to historical changes and project how it changes under two contrasting 21st century emissions scenarios. Compared to preindustrial values, the global mean diurnal amplitude of pCO2 increases by 4.8 μatm (+226 %) in the high-emissions scenario but only 1.2 μatm (+55 %) in the high-mitigation scenario. The probability of extreme diurnal amplitudes of pCO2 and [H+] is also affected, with 30- to 60-fold increases relative to the preindustrial under high twenty-first century emissions. The main driver of heightened pCO2 diurnal variability is the enhanced sensitivity of pCO2 to changes in temperature as the ocean absorbs atmospheric CO2. Our projections suggest that organisms in the future ocean will be exposed to enhanced diurnal variability in pCO2 and [H+], with likely increases in the associated metabolic cost that such variability imposes.

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Cascading effects augment the direct impact of CO2 on phytoplankton growth in a biogeochemical model

Atmospheric and oceanic CO2 concentrations are rising at an unprecedented rate. Laboratory studies indicate a positive effect of rising CO2 on phytoplankton growth until an optimum is reached, after which the negative impact of accompanying acidification dominates. Here, we implemented carbonate system sensitivities of phytoplankton growth into our global biogeochemical model FESOM-REcoM and accounted explicitly for coccolithophores as the group most sensitive to CO2. In idealized simulations in which solely the atmospheric CO2 mixing ratio was modified, changes in competitive fitness and biomass are not only caused by the direct effects of CO2, but also by indirect effects via nutrient and light limitation as well as grazing. These cascading effects can both amplify or dampen phytoplankton responses to changing ocean pCO2 levels. For example, coccolithophore growth is negatively affected both directly by future pCO2 and indirectly by changes in light limitation, but these effects are compensated by a weakened nutrient limitation resulting from the decrease in small-phytoplankton biomass. In the Southern Ocean, future pCO2 decreases small-phytoplankton biomass and hereby the preferred prey of zooplankton, which reduces the grazing pressure on diatoms and allows them to proliferate more strongly. In simulations that encompass CO2-driven warming and acidification, our model reveals that recent observed changes in North Atlantic coccolithophore biomass are driven primarily by warming and not by CO2. Our results highlight that CO2 can change the effects of other environmental drivers on phytoplankton growth, and that cascading effects may play an important role in projections of future net primary production.

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Enhance seasonal amplitude of atmospheric CO2 by the changing Southern Ocean carbon sink

The enhanced seasonal amplitude of atmospheric CO2 has been viewed so far primarily as a Northern Hemisphere phenomenon. Yet, analyses of atmospheric CO2 records from 49 stations between 1980 and 2018 reveal substantial trends and variations in this amplitude globally. While no significant trends can be discerned before 2000 in most places, strong positive trends emerge after 2000 in the southern high latitudes. Using factorial simulations with an atmospheric transport model and analyses of surface ocean Pco2 observations, we show that the increase is best explained by the onset of increasing seasonality of air-sea CO2 exchange over the Southern Ocean around 2000. Underlying these changes is the long-term ocean acidification trend that tends to enhance the seasonality of the air-sea fluxes, but this trend is modified by the decadal variability of the Southern Ocean carbon sink. The seasonal variations of atmospheric CO2 thus emerge as a sensitive recorder of the variations of the Southern Ocean carbon sink.

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Source-labeled anthropogenic carbon reveals a large shift of preindustrial carbon from the ocean to the atmosphere

Abstract

Two centuries of anthropogenic CO2 emissions have increased the CO2 concentration of the atmosphere and the dissolved inorganic carbon (DIC) concentration of the ocean compared to preindustrial times. These anthropogenic carbon perturbations are often equated to the amount of anthropogenically emitted carbon in the atmosphere or ocean, which ignores the possibility of a shift of natural carbon between the oceanic and atmospheric carbon reservoirs. Here we use a data-assimilated ocean circulation model and numerical tracers akin to ideal isotopes to label carbon when it is emitted by anthropogenic sources. We find that emitted carbon accounts for only about 45% of the atmospheric CO2 increase since preindustrial times, the remaining 55% being natural CO2 that outgassed from the ocean in response to anthropogenically emitted carbon invading the ocean. This outgassing is driven by the order-10 seawater carbonate buffer factor which causes increased leakage of natural CO2 as DIC concentrations increase. By 2020, the ocean had outgassed ∼159 Pg of natural carbon, which is counteracted by the ocean absorbing ∼347 Pg of emitted carbon, about 1.8 times more than the net increase in oceanic carbon storage of ∼188 PgC. These results do not challenge existing estimates of anthropogenically driven changes in atmospheric or oceanic carbon inventories, but they shed new light on the composition of these changes and the fate of anthropogenically emitted carbon in the Earth system.

Key Points

  • Anthropogenically emitted carbon accounts for about half of the atmospheric CO2 increase since preindustrial times
  • The remaining half of the atmospheric CO2 increase is due to outgassing of preindustrial carbon from the ocean
  • By 2020, the ocean had lost 1 preindustrial CO2 molecule for every 2.2 anthropogenically emitted CO2 molecules gained
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Co-occurring anthropogenic stressors reduce the timeframe of environmental viability for the world’s coral reefs

Anthropogenic disturbances are posing unprecedented challenges to the persistence of ecosystems worldwide. The speed at which these disturbances reach an ecosystem’s tolerance thresholds will determine the time available for adaptation and conservation. Here, we aim to calculate the year after which a given environmental stressor permanently exceeds the bounds of an ecosystem’s tolerance. Ecosystem thresholds are here defined as limits in a given stressor beyond which ecosystems have showed considerable changes in community assembly and functioning, becoming remnants of what they once were, but not necessarily leading to species extirpation or extinction. Using the world’s coral reefs as a case example, we show that the projected effects of marine heatwaves, ocean acidification, storms, land-based pollution, and local human stressors are being underestimated considerably by looking at disturbances independently. Given the spatial complementarity in which numerous disturbances impact the world’s coral reefs, we show that the timelines of environmental suitability are halved when all disturbances are analyzed simultaneously, as opposed to independently. Under business-as-usual scenarios, the median year after which environmental conditions become unsuitable for the world’s remaining coral reefs was, at worse, 2050 for any one disturbance alone (28 years left); but when analyzed concurrently, this date was shortened to 2035 (13 years left). When analyzed together, disturbances reduced the date of environmental suitability because areas that may remain suitable under one disturbance could become unsuitable by any of several other variables. The significance of co-occurring disturbances at reducing timeframes of environmental suitability was evident even under optimistic scenarios. The best-case scenario, characterized by strong mitigation of greenhouse gas emissions and optimistic human development, resulted in 41% of global coral reefs with unsuitable conditions by 2100 under any one disturbance independently; yet when analyzed in combination up to 64% of the world’s coral reefs could face unsuitable environmental conditions by one disturbance or another. Under the worst-case scenario, nearly all coral reef ecosystems worldwide (approximately 99%) will permanently face unsuitable conditions by 2055 in at least one of the disturbances analyzed. Prior studies have indicated the projected dire effects of climate change on coral reefs by mid-century; by analyzing a multitude of projected disturbances, our study reveals a much more severe prognosis for the world’s coral reefs as they have significantly less time to adapt while highlighting the urgent need to tackle available solutions to human disturbances.

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Observation-constrained estimates of the global ocean carbon sink from Earth system models

The ocean slows global warming by currently taking up around one-quarter of all human-made CO2 emissions. However, estimates of the ocean anthropogenic carbon uptake vary across various observation-based and model-based approaches. Here, we show that the global ocean anthropogenic carbon sink simulated by Earth system models can be constrained by two physical parameters, the present-day sea surface salinity in the subtropical–polar frontal zone in the Southern Ocean and the strength of the Atlantic Meridional Overturning Circulation, and one biogeochemical parameter, the Revelle factor of the global surface ocean. The Revelle factor quantifies the chemical capacity of seawater to take up carbon for a given increase in atmospheric CO2. By exploiting this three-dimensional emergent constraint with observations, we provide a new model- and observation-based estimate of the past, present, and future global ocean anthropogenic carbon sink and show that the ocean carbon sink is 9 %–11 % larger than previously estimated. Furthermore, the constraint reduces uncertainties of the past and present global ocean anthropogenic carbon sink by 42 %–59 % and the future sink by 32 %–62 % depending on the scenario, allowing for a better understanding of the global carbon cycle and better-targeted climate and ocean policies. Our constrained results are in good agreement with the anthropogenic carbon air–sea flux estimates over the last three decades based on observations of the CO2 partial pressure at the ocean surface in the Global Carbon Budget 2021, and they suggest that existing hindcast ocean-only model simulations underestimate the global ocean anthropogenic carbon sink. The key parameters identified here for the ocean anthropogenic carbon sink should be quantified when presenting simulated ocean anthropogenic carbon uptake as in the Global Carbon Budget and be used to adjust these simulated estimates if necessary. The larger ocean carbon sink results in enhanced ocean acidification over the 21st century, which further threatens marine ecosystems by reducing the water volume that is projected to be undersaturated towards aragonite by around 3.7×106–7.4×106 km3 more than originally projected.

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Vulnerability of exploited deep-sea demersal species to ocean warming, deoxygenation, and acidification

Vulnerability of marine species to climate change (including ocean acidification, deoxygenation, and associated changes in food supply) depends on species’ ecological and biological characteristics. Most existing assessments focus on coastal species but systematic analysis of climate vulnerability for the deep sea is lacking. Here, we combine a fuzzy logic expert system with species biogeographical data to assess the risks of climate impacts to the population viability of 32 species of exploited demersal deep-sea species across the global ocean. Climatic hazards are projected to emerge from historical variabilities in all the recorded habitats of the studied species by the mid-twenty-first century. Species that are both at very high risk of climate impacts and highly vulnerable to fishing include Antarctic toothfish (Dissostichus mawsoni), rose fish (Sebastes norvegicus), roughhead grenadier (Macrourus berglax), Baird’s slickhead (Alepocephalus bairdii), cusk (Brosme brosme), and Portuguese dogfish (Centroscymnus coelepis). Most exploited deep-sea fishes are likely to be at higher risk of local, or even global, extinction than previously assessed because of their high vulnerability to both climate change and fishing. Spatially, a high concentration of deep-sea species that are climate vulnerable is predicted in the northern Atlantic Ocean and the Indo-Pacific region. Aligning carbon mitigation with improved fisheries management offers opportunities for overall risk reduction in the coming decades. Regional fisheries management organizations (RFMOs) have an obligation to incorporate climate change in their deliberations. In addition, deep-sea areas that are not currently managed by RFMOs should be included in existing or new international governance institutions or arrangements.

Continue reading ‘Vulnerability of exploited deep-sea demersal species to ocean warming, deoxygenation, and acidification’

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