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Nadine Goris, Jerry F. Tjiputra, Are Olsen, Jörg Schwinger, Siv K. Lauvset, and Emil Jeansson

Abstract

The North Atlantic is one of the major sinks for anthropogenic carbon in the global ocean. Improved understanding of the underlying mechanisms is vital for constraining future projections, which presently have high uncertainties. To identify some of the causes behind this uncertainty, this study investigates the North Atlantic’s anthropogenically altered carbon uptake and inventory, that is, changes in carbon uptake and inventory due to rising atmospheric CO2 and climate change (abbreviated as -uptake and -inventory). Focus is set on an ensemble of 11 Earth system models and their simulations of a future with high atmospheric CO2. Results show that the model spread in the -uptake originates in middle and high latitudes. Here, the annual cycle of oceanic pCO2 reveals inherent model mechanisms that are responsible for different model behavior: while it is SST-dominated for models with a low future -uptake, it is dominated by deep winter mixing and biological production for models with a high future -uptake. Models with a high future -uptake show an efficient carbon sequestration and hence store a large fraction of their contemporary North Atlantic -inventory below 1000-m depth, while the opposite is true for models with a low future -uptake. Constraining the model ensemble with observation-based estimates of carbon sequestration and summer oceanic pCO2 anomalies yields later flattening of the -uptake than previously estimated. This result highlights the need to depart from the concept of unconstrained model ensembles in order to reduce uncertainties associated with future projections.

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Lifen Jiang, Yaner Yan, Oleksandra Hararuk, Nathaniel Mikle, Jianyang Xia, Zheng Shi, Jerry Tjiputra, Tongwen Wu, and Yiqi Luo

Abstract

Model intercomparisons and evaluations against observations are essential for better understanding of models’ performance and for identifying the sources of uncertainty in their output. The terrestrial vegetation carbon simulated by 11 Earth system models (ESMs) involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) was evaluated in this study. The simulated vegetation carbon was compared at three distinct spatial scales (grid, biome, and global) among models and against the observations (an updated database from Olson et al.’s “Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database”). Moreover, the underlying causes of the differences in the models’ predictions were explored. Model–data fit at the grid scale was poor but greatly improved at the biome scale. Large intermodel variability was pronounced in the tropical and boreal regions, where total vegetation carbon stocks were high. While 8 out of 11 ESMs reproduced the global vegetation carbon to within 20% uncertainty of the observational estimate (560 ± 112 Pg C), the simulated global totals varied nearly threefold between the models. The goodness of fit of ESMs in simulating vegetation carbon depended strongly on the spatial scales. Sixty-three percent of the variability in contemporary global vegetation carbon stocks across ESMs could be explained by differences in vegetation carbon residence time across ESMs (P < 0.01). The analysis indicated that ESMs’ performance of vegetation carbon predictions can be substantially improved through better representation of plant longevity (i.e., carbon residence time) and its respective spatial distributions.

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Tilla Roy, Laurent Bopp, Marion Gehlen, Birgit Schneider, Patricia Cadule, Thomas L. Frölicher, Joachim Segschneider, Jerry Tjiputra, Christoph Heinze, and Fortunat Joos
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Helene Muri, Jerry Tjiputra, Odd Helge Otterå, Muralidhar Adakudlu, Siv K. Lauvset, Alf Grini, Michael Schulz, Ulrike Niemeier, and Jón Egill Kristjánsson

Abstract

Considering the ambitious climate targets of the Paris Agreement to limit global warming to 2°C, with aspirations of even 1.5°C, questions arise on how to achieve this. Climate geoengineering has been proposed as a potential tool to minimize global harm from anthropogenic climate change. Here, an Earth system model is used to evaluate the climate response when transferring from a high CO2 forcing scenario, RCP8.5, to a middle-of-the-road forcing scenario, like RCP4.5, using aerosol geoengineering. Three different techniques are considered: stratospheric aerosol injections (SAI), marine sky brightening (MSB), and cirrus cloud thinning (CCT). The climate states appearing in the climate geoengineering cases are found to be closer to RCP4.5 than RCP8.5 and many anthropogenic global warming symptoms are alleviated. All three techniques result in comparable global mean temperature evolutions. However, there are some notable differences in other climate variables due to the nature of the forcings applied. CCT acts mainly on the longwave part of the radiation budget, as opposed to MSB and SAI acting in the shortwave. This yields a difference in the response, particularly in the hydrological cycle. The responses in sea ice, sea level, ocean heat, and circulation, as well as the carbon cycle, are furthermore compared. Sudden termination of the aerosol injection geoengineering shows that the climate very rapidly (within two decades) reverts to the path of RCP8.5, questioning the sustainable nature of such climate geoengineering, and simultaneous mitigation during any such form of climate geoengineering would be needed to limit termination risks.

Open access
Tilla Roy, Laurent Bopp, Marion Gehlen, Birgit Schneider, Patricia Cadule, Thomas L. Frölicher, Joachim Segschneider, Jerry Tjiputra, Christoph Heinze, and Fortunat Joos

Abstract

The increase in atmospheric CO2 over this century depends on the evolution of the oceanic air–sea CO2 uptake, which will be driven by the combined response to rising atmospheric CO2 itself and climate change. Here, the future oceanic CO2 uptake is simulated using an ensemble of coupled climate–carbon cycle models. The models are driven by CO2 emissions from historical data and the Special Report on Emissions Scenarios (SRES) A2 high-emission scenario. A linear feedback analysis successfully separates the regional future (2010–2100) oceanic CO2 uptake into a CO2-induced component, due to rising atmospheric CO2 concentrations, and a climate-induced component, due to global warming. The models capture the observation-based magnitude and distribution of anthropogenic CO2 uptake. The distributions of the climate-induced component are broadly consistent between the models, with reduced CO2 uptake in the subpolar Southern Ocean and the equatorial regions, owing to decreased CO2 solubility; and reduced CO2 uptake in the midlatitudes, owing to decreased CO2 solubility and increased vertical stratification. The magnitude of the climate-induced component is sensitive to local warming in the southern extratropics, to large freshwater fluxes in the extratropical North Atlantic Ocean, and to small changes in the CO2 solubility in the equatorial regions. In key anthropogenic CO2 uptake regions, the climate-induced component offsets the CO2-induced component at a constant proportion up until the end of this century. This amounts to approximately 50% in the northern extratropics and 25% in the southern extratropics and equatorial regions. Consequently, the detection of climate change impacts on anthropogenic CO2 uptake may be difficult without monitoring additional tracers, such as oxygen.

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Jörg Schwinger, Jerry F. Tjiputra, Christoph Heinze, Laurent Bopp, James R. Christian, Marion Gehlen, Tatiana Ilyina, Chris D. Jones, David Salas-Mélia, Joachim Segschneider, Roland Séférian, and Ian Totterdell

Abstract

Carbon cycle feedbacks are usually categorized into carbon–concentration and carbon–climate feedbacks, which arise owing to increasing atmospheric CO2 concentration and changing physical climate. Both feedbacks are often assumed to operate independently: that is, the total feedback can be expressed as the sum of two independent carbon fluxes that are functions of atmospheric CO2 and climate change, respectively. For phase 5 of the Coupled Model Intercomparison Project (CMIP5), radiatively and biogeochemically coupled simulations have been undertaken to better understand carbon cycle feedback processes. Results show that the sum of total ocean carbon uptake in the radiatively and biogeochemically coupled experiments is consistently larger by 19–58 petagrams of carbon (Pg C) than the uptake found in the fully coupled model runs. This nonlinearity is small compared to the total ocean carbon uptake (533–676 Pg C), but it is of the same order as the carbon–climate feedback. The weakening of ocean circulation and mixing with climate change makes the largest contribution to the nonlinear carbon cycle response since carbon transport to depth is suppressed in the fully relative to the biogeochemically coupled simulations, while the radiatively coupled experiment mainly measures the loss of near-surface carbon owing to warming of the ocean. Sea ice retreat and seawater carbon chemistry contribute less to the simulated nonlinearity. The authors’ results indicate that estimates of the ocean carbon–climate feedback derived from “warming only” (radiatively coupled) simulations may underestimate the reduction of ocean carbon uptake in a warm climate high CO2 world.

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Chris Jones, Eddy Robertson, Vivek Arora, Pierre Friedlingstein, Elena Shevliakova, Laurent Bopp, Victor Brovkin, Tomohiro Hajima, Etsushi Kato, Michio Kawamiya, Spencer Liddicoat, Keith Lindsay, Christian H. Reick, Caroline Roelandt, Joachim Segschneider, and Jerry Tjiputra

Abstract

The carbon cycle is a crucial Earth system component affecting climate and atmospheric composition. The response of natural carbon uptake to CO2 and climate change will determine anthropogenic emissions compatible with a target CO2 pathway. For phase 5 of the Coupled Model Intercomparison Project (CMIP5), four future representative concentration pathways (RCPs) have been generated by integrated assessment models (IAMs) and used as scenarios by state-of-the-art climate models, enabling quantification of compatible carbon emissions for the four scenarios by complex, process-based models. Here, the authors present results from 15 such Earth system GCMs for future changes in land and ocean carbon storage and the implications for anthropogenic emissions. The results are consistent with the underlying scenarios but show substantial model spread. Uncertainty in land carbon uptake due to differences among models is comparable with the spread across scenarios. Model estimates of historical fossil-fuel emissions agree well with reconstructions, and future projections for representative concentration pathway 2.6 (RCP2.6) and RCP4.5 are consistent with the IAMs. For high-end scenarios (RCP6.0 and RCP8.5), GCMs simulate smaller compatible emissions than the IAMs, indicating a larger climate–carbon cycle feedback in the GCMs in these scenarios. For the RCP2.6 mitigation scenario, an average reduction of 50% in emissions by 2050 from 1990 levels is required but with very large model spread (14%–96%). The models also disagree on both the requirement for sustained negative emissions to achieve the RCP2.6 CO2 concentration and the success of this scenario to restrict global warming below 2°C. All models agree that the future airborne fraction depends strongly on the emissions profile with higher airborne fraction for higher emissions scenarios.

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Vivek K. Arora, George J. Boer, Pierre Friedlingstein, Michael Eby, Chris D. Jones, James R. Christian, Gordon Bonan, Laurent Bopp, Victor Brovkin, Patricia Cadule, Tomohiro Hajima, Tatiana Ilyina, Keith Lindsay, Jerry F. Tjiputra, and Tongwen Wu

Abstract

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.

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Spencer K. Liddicoat, Andy J. Wiltshire, Chris D. Jones, Vivek K. Arora, Victor Brovkin, Patricia Cadule, Tomohiro Hajima, David M. Lawrence, Julia Pongratz, Jörg Schwinger, Roland Séférian, Jerry F. Tjiputra, and Tilo Ziehn

Abstract

We present the compatible CO2 emissions from fossil fuel (FF) burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth system models (ESMs) participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (394 ± 59 GtC vs 400 ± 20 GtC, respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs’ diagnosed FF emission rates are consistent with those generated by the integrated assessment models (IAMs) from which the SSPs’ CO2 concentration pathways were constructed; the simpler IAMs’ emissions lie within the ESMs’ spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs’ FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4, and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models’ ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land-use and land-cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two.

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Sha Zhou, Junyi Liang, Xingjie Lu, Qianyu Li, Lifen Jiang, Yao Zhang, Christopher R. Schwalm, Joshua B. Fisher, Jerry Tjiputra, Stephen Sitch, Anders Ahlström, Deborah N. Huntzinger, Yuefei Huang, Guangqian Wang, and Yiqi Luo

Abstract

Terrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land–Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.

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