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The Amazon rainforest plays a crucial role in global carbon storage, but a minor destabilization of these forests could result in considerable carbon loss. Among the external factors affecting vegetation, elevated CO 2 (eCO 2) levels have long been anticipated to have positive impacts on vegetation, including the direct enhancement of both photosynthesis and productivity and increasing water use efficiency. However, the overall impact of eCO 2 on the net carbon balance, especially concerning tree-mortality-induced carbon loss and recovery following extreme drought events, has remained elusive. Here, we use a process-based model that couples physiological CO 2 effects with demography and both drought mortality and resistance processes. The model was previously calibrated to reproduce observed drought responses of Amazon forest sites. The model results, based on factorial simulations with and without eCO 2 , reveal that eCO 2 enhances forest growth and promotes competition between trees, leading to more natural self-thinning of forest stands. This occurs following a growth–mortality trade-off response, although the growth outweighs the tree loss. Additionally, eCO 2 provides water-saving benefits, reducing the risk of tree mortality during drought episodes. However, extra carbon losses could still occur due to an eCO 2 -induced increase in background biomass density, leading to "more carbon available to lose" when severe droughts happen. Furthermore, we found that eCO 2 accelerates drought recovery and enhances drought resistance and resilience. By delving into the less-explored aspect of tree mortality response to eCO 2 , the model improvements advance our understanding of how carbon balance responds to eCO 2 , particularly regarding mechanisms of continuous competition-induced carbon loss vs. pulses of drought-induced carbon loss. These findings provide valuable insights into the intricate ways in which rising CO 2 influences forest carbon dynamics and vulnerability, offering a critical understanding of the Amazon rainforest's evolution amidst more frequent and intense extreme climate events. [ABSTRACT FROM AUTHOR]

The role of the land carbon cycle in climate change remains highly uncertain. A key source of the projection spread is related to the assumed response of photosynthesis to warming, especially in the tropics. The optimum temperature for photosynthesis determines whether warming positively or negatively impacts photosynthesis, thereby amplifying or suppressing CO 2 fertilisation of photosynthesis under CO 2 -induced global warming. Land carbon cycle models have been extensively calibrated against local eddy flux measurements, but this has not previously been clearly translated into a reduced uncertainty in terms of how the tropical land carbon sink will respond to warming. Using a previous parameter perturbation ensemble carried out with version 3 of the Hadley Centre coupled climate–carbon cycle model (HadCM3C), we identify an emergent relationship between the optimal temperature for photosynthesis, which is especially relevant in tropical forests, and the projected amount of atmospheric CO 2 at the end of the century. We combine this with a constraint on the optimum temperature for photosynthesis, derived from eddy covariance measurements using the adjoint of the Joint UK Land Environment Simulator (JULES) land surface model. Taken together, the emergent relationship from the coupled model and the constraint on the optimum temperature for photosynthesis define an emergent constraint on future atmospheric CO 2 in the HadCM3C coupled climate–carbon cycle under a common emissions scenario (A1B). The emergent constraint sharpens the probability density of simulated CO 2 change (2100–1900) and moves its peak to a lower value of 497 ± 91 compared to 607 ± 128 ppmv (parts per million by volume) when using the equal-weight prior. Although this result is likely to be model and scenario dependent, it demonstrates the potential of combining the large-scale emergent constraint approach with a parameter estimation using detailed local measurements. [ABSTRACT FROM AUTHOR]

The instability with respect to global glaciation is a fundamental property of the climate system caused by the positive ice-albedo feedback. The atmospheric concentration of carbon dioxide (CO 2) at which this Snowball bifurcation occurs changes through Earth's history, most notably because of the slowly increasing solar luminosity. Quantifying this critical CO 2 concentration is not only interesting from a climate dynamics perspective but also constitutes an important prerequisite for understanding past Snowball Earth episodes, as well as the conditions for habitability on Earth and other planets. Earlier studies are limited to investigations with very simple climate models for Earth's entire history or studies of individual time slices carried out with a variety of more complex models and for different boundary conditions, making comparisons and the identification of secular changes difficult. Here, we use a coupled climate model of intermediate complexity to trace the Snowball bifurcation of an aquaplanet through Earth's history in one consistent model framework. We find that the critical CO 2 concentration decreased more or less logarithmically with increasing solar luminosity until about 1 billion years ago but dropped faster in more recent times. Furthermore, there was a fundamental shift in the dynamics of the critical state about 1.2 billion years ago (unrelated to the downturn in critical CO 2 values), driven by the interplay of wind-driven sea-ice dynamics and the surface energy balance: for critical states at low solar luminosities, the ice line lies in the Ferrel cell, stabilised by the poleward winds despite moderate meridional temperature gradients under strong greenhouse warming. For critical states at high solar luminosities, on the other hand, the ice line rests at the Hadley cell boundary, stabilised against the equatorward winds by steep meridional temperature gradients resulting from the increased solar energy input at lower latitudes and stronger Ekman transport in the ocean. [ABSTRACT FROM AUTHOR]

A growing body of literature investigates the effects of solar radiation modification (SRM) on global and regional climates. Previous studies have focused on the potentials and the side effects of SRM, with little attention being given to possible deployment timescales and the levels of carbon dioxide removal required for a phase out. Here, we investigate the deployment timescales of SRM and how they are affected by different levels of mitigation, net-negative emissions (NNEs) and climate uncertainty. We generate a large dataset of 355 emission scenarios in which SRM is deployed to keep warming levels at 1.5 ∘ C global mean temperature. Probabilistic climate projections from this ensemble result in a large range of plausible future warming and cooling rates that lead to various SRM deployment timescales. In all pathways consistent with extrapolated current ambition, SRM deployment would exceed 100 years even under the most optimistic assumptions regarding climate response. As soon as the temperature threshold is exceeded, neither mitigation nor NNEs or climate sensitivity alone can guarantee short deployment timescales. Since the evolution of mitigation under SRM, the availability of carbon removal technologies and the effects of climate reversibility will be mostly unknown at its initialisation time, it is impossible to predict how temporary SRM deployment would be. Any deployment of SRM therefore comes with the risk of multi-century legacies of deployment, implying multi-generational commitments of costs, risks and negative side effects of SRM and NNEs combined. [ABSTRACT FROM AUTHOR]

Afforestation is an important mitigation strategy for climate change due to its carbon sequestration potential. Besides this favorable biogeochemical effect on global CO 2 concentrations, afforestation also affects the regional climate by changing the biogeophysical land surface characteristics. In this study, we investigate the effects of an idealized global CO 2 reduction to pre-industrial conditions by a Europe-wide afforestation experiment on the regional longwave radiation balance, starting in the year 1986 on a continent entirely covered with grassland. Results show that the impact of biogeophysical processes on the surface temperatures is much stronger than that of biogeochemical processes. Furthermore, biogeophysically induced changes of the surface temperatures, atmospheric temperatures, and moisture concentrations are as important for the regional longwave radiation balance as the global CO 2 reduction. While the outgoing longwave radiation is increased in winter, it is reduced in summer. In terms of annual total, a Europe-wide afforestation has a regional warming effect despite reduced CO 2 concentrations. Thus, even for an idealized reduction of the global CO 2 concentrations to pre-industrial levels, the European climate response to afforestation would still be dominated by its biogeophysical effects. [ABSTRACT FROM AUTHOR]

In this study, we investigate the maximum physical and biogeochemical potential of macroalgae open-ocean mariculture and sinking (MOS) as an ocean-based carbon dioxide removal (CDR) method. Embedding a macroalgae model into an Earth system model, we simulate macroalgae mariculture in the open-ocean surface layer followed by fast sinking of the carbon-rich macroalgal biomass to the deep seafloor (depth>3000 m), which assumes no remineralization of the harvested biomass during the quick sinking. We also test the combination of MOS with artificial upwelling (AU), which fertilizes the macroalgae by pumping nutrient-rich deeper water to the surface. The simulations are done under RCP 4.5, a moderate-emissions pathway. When deployed globally between years 2020 and 2100, the carbon captured and exported by MOS is 270 PgC, which is further boosted by AU of 447 PgC. Because of feedbacks in the Earth system, the oceanic carbon inventory only increases by 171.8 PgC (283.9 PgC with AU) in the idealized simulations. More than half of this carbon remains in the ocean after cessation at year 2100 until year 3000. The major side effect of MOS on pelagic ecosystems is the reduction of phytoplankton net primary production (PNPP) due to the competition for nutrients with macroalgae and due to canopy shading. MOS shrinks the mid-layer oxygen-minimum zones (OMZs) by reducing the organic matter export to, and remineralization in, subsurface and intermediate waters, while it creates new OMZs on the seafloor by oxygen consumption from remineralization of sunken biomass. MOS also impacts the global carbon cycle by reducing the atmospheric and terrestrial carbon reservoirs when enhancing the ocean carbon reservoir. MOS also enriches dissolved inorganic carbon in the deep ocean. Effects are mostly reversible after cessation of MOS, though recovery is not complete by year 3000. In a sensitivity experiment without remineralization of sunken MOS biomass, the whole of the MOS-captured carbon is permanently stored in the ocean, but the lack of remineralized nutrients causes a long-term nutrient decline in the surface layers and thus reduces PNPP. Our results suggest that MOS has, theoretically, considerable CDR potential as an ocean-based CDR method. However, our simulations also suggest that such large-scale deployment of MOS would have substantial side effects on marine ecosystems and biogeochemistry, up to a reorganization of food webs over large parts of the ocean. [ABSTRACT FROM AUTHOR]

The global carbon budget (GCB) – including fluxes of CO 2 between the atmosphere, land, and ocean and its atmospheric growth rate – show large interannual to decadal variations. Reconstructing and predicting the variable GCB is essential for tracing the fate of carbon and understanding the global carbon cycle in a changing climate. We use a novel approach to reconstruct and predict the variations in GCB in the next few years based on our decadal prediction system enhanced with an interactive carbon cycle. By assimilating physical atmospheric and oceanic data products into the Max Planck Institute Earth System Model (MPI-ESM), we are able to reproduce the annual mean historical GCB variations from 1970–2018, with high correlations of 0.75, 0.75, and 0.97 for atmospheric CO 2 growth, air–land CO 2 fluxes, and air–sea CO 2 fluxes, respectively, relative to the assessments from the Global Carbon Project (GCP). Such a fully coupled decadal prediction system, with an interactive carbon cycle, enables the representation of the GCB within a closed Earth system and therefore provides an additional line of evidence for the ongoing assessments of the anthropogenic GCB. Retrospective predictions initialized from the simulation in which physical atmospheric and oceanic data products are assimilated show high confidence in predicting the following year's GCB. The predictive skill is up to 5 years for the air–sea CO 2 fluxes, and 2 years for the air–land CO 2 fluxes and atmospheric carbon growth rate. This is the first study investigating the GCB variations and predictions with an emission-driven prediction system. Such a system also enables the reconstruction of the past and prediction of the evolution of near-future atmospheric CO 2 concentration changes. The Earth system predictions in this study provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy. [ABSTRACT FROM AUTHOR]

To estimate equilibrium climate sensitivity from a simulation where a step change in carbon dioxide concentrations is imposed, a common approach is to linearly extrapolate temperatures as a function of top-of-atmosphere energetic imbalance to estimate the equilibrium state ("effective climate sensitivity"). In this study, we find that this estimate may be biased in some models due to state-dependent energetic leaks. Using an ensemble of multi-millennial simulations of climate model response to a constant forcing, we estimate equilibrium climate sensitivity through Bayesian calibration of simple climate models which allow for responses from subdecadal to multi-millennial timescales. Results suggest potential biases in effective climate sensitivity in the case of particular models where radiative tendencies imply energetic imbalances which differ between pre-industrial and quadrupled CO 2 states, whereas for other models even multi-thousand-year experiments are insufficient to predict the equilibrium state. These biases draw into question the utility of effective climate sensitivity as a metric of warming response to greenhouse gases and underline the requirement for operational climate sensitivity experiments on millennial timescales to better understand committed warming following a stabilization of greenhouse gases. [ABSTRACT FROM AUTHOR]

The El Niño–Southern Oscillation (ENSO) widely modulates the global carbon cycle. More specifically, it alters the net uptake of carbon in the tropical ocean. Indeed, over the tropical Pacific less carbon is released by oceans during El Niño, while the opposite is the case for La Niña. Here, the skill of Earth system models (ESMs) from the latest Coupled Model Intercomparison Project (CMIP6) to simulate the observed tropical Pacific CO 2 flux variability in response to ENSO is assessed. The temporal amplitude and spatial extent of CO 2 flux anomalies vary considerably among models, while the surface temperature signals of El Niño and La Niña phases are generally well represented. Under historical conditions followed by the high-warming Shared Socio-economic Pathway (SSP5-8.5) scenarios, about half the ESMs simulate a reversal in ENSO–CO 2 flux relationship. This gradual shift, which occurs as early as the first half of the 21st century, is associated with a high CO 2 -induced increase in the Revelle factor that leads to stronger sensitivity of partial pressure of CO 2 (p CO 2) to changes in surface temperature between ENSO phases. At the same time, uptake of anthropogenic CO 2 substantially increases upper-ocean dissolved inorganic carbon (DIC) concentrations (reducing its vertical gradient in the thermocline) and weakens the ENSO-modulated surface DIC variability. The response of the ENSO–CO 2 flux relationship to future climate change is sensitive to the contemporary mean state of the carbonate ion concentration in the tropics. We present an emergent constraint between the simulated contemporary carbonate concentration with the projected cumulated CO 2 fluxes. Models that simulate shifts in the ENSO–CO 2 flux relationship simulate positive bias in surface carbonate concentrations. [ABSTRACT FROM AUTHOR]

Cold and snowy spells are compound extreme events with the potential to cause high socioeconomic impacts. Gaining insight into their dynamics in climate change scenarios could help anticipating the need for adaptation efforts. We focus on winter cold and snowy spells over Italy, reconstructing 32 major events in the past 60 years from documentary sources. Despite warmer winter temperatures, very recent cold spells have been associated with abundant and sometimes exceptional snowfall. Our goal is to analyse the dynamical weather patterns associated with these events and understand whether those patterns would be more or less recurrent in different emission scenarios using an intermediate-complexity model (the Planet Simulator, PlaSim). Our results, obtained by considering RCP2.6, RCP4.5 and RCP8.5 end-of-century equivalent CO2 concentrations, suggest that the likelihood of synoptic configurations analogous to those leading to extreme cold spells would grow substantially under increased emissions. [ABSTRACT FROM AUTHOR]

Future climate projections from Earth system models (ESMs) typically focus on the timescale of this century. We use a set of five ESMs and one Earth system model of intermediate complexity (EMIC) to explore the dynamics of the Earth's climate and carbon cycles under contrasting emissions trajectories beyond this century to the year 2300. The trajectories include a very-high-emissions, unmitigated fossil-fuel-driven scenario, as well as a mitigation scenario that diverges from the first scenario after 2040 and features an "overshoot", followed by a decrease in atmospheric CO 2 concentrations by means of large net negative CO 2 emissions. In both scenarios and for all models considered here, the terrestrial system switches from being a net sink to either a neutral state or a net source of carbon, though for different reasons and centered in different geographic regions, depending on both the model and the scenario. The ocean carbon system remains a sink, albeit weakened by carbon cycle feedbacks, in all models under the high-emissions scenario and switches from sink to source in the overshoot scenario. The global mean temperature anomaly is generally proportional to cumulative carbon emissions, with a deviation from proportionality in the overshoot scenario that is governed by the zero emissions commitment. Additionally, 23rd century warming continues after the cessation of carbon emissions in several models in the high-emissions scenario and in one model in the overshoot scenario. While ocean carbon cycle responses qualitatively agree in both globally integrated and zonal mean dynamics in both scenarios, the land models qualitatively disagree in zonal mean dynamics, in the relative roles of vegetation and soil in driving C fluxes, in the response of the sink to CO 2 , and in the timing of the sink–source transition, particularly in the high-emissions scenario. The lack of agreement among land models on the mechanisms and geographic patterns of carbon cycle feedbacks, alongside the potential for lagged physical climate dynamics to cause warming long after CO 2 concentrations have stabilized, points to the possibility of surprises in the climate system beyond the 21st century time horizon, even under relatively mitigated global warming scenarios, which should be taken into consideration when setting global climate policy. [ABSTRACT FROM AUTHOR]

Understanding historical changes in gross primary productivity (GPP) is essential for better predicting the future global carbon cycle. However, the historical trends of terrestrial GPP, due to the CO 2 fertilization effect, climate, and land-use change, remain largely uncertain. Using long-term satellite-based near-infrared radiance of vegetation (NIRv), a proxy for GPP, and multiple GPP datasets derived from satellite-based products, dynamic global vegetation model (DGVM) simulations, and an upscaled product from eddy covariance (EC) measurements, here we comprehensively investigated their trends and analyzed the causes for any discrepancies during 1982–2015. Although spatial patterns of climatological annual GPP from all products and NIRv are highly correlated (r>0.84), the spatial correlation coefficients of trends between DGVM GPP and NIRv significantly decreased (with the ensemble mean of r=0.49) and even the spatial correlation coefficients of trends between other GPP products and NIRv became negative. By separating the global land into the tropics plus extratropical Southern Hemisphere (Trop + SH) and extratropical Northern Hemisphere (NH), we found that, during 1982–2015, simulated GPP from most of the models showed a stronger increasing trend over Trop + SH than NH. In contrast, the satellite-based GPP products indicated a substantial increase over NH. Mechanistically, model sensitivity experiments indicated that the increase of annual global total GPP was dominated by the CO 2 fertilization effect (83.9 % contribution), however, with the largest uncertainty in magnitude in individual simulations among the three drivers of CO 2 fertilization, climate, and land-use change. Interestingly, the spatial distribution of inter-model spreads of GPP trends resulted mainly from climate and land-use change rather than CO 2 fertilization effect. After 2000, trends from satellite-based GPP products were different from the full time series, suggesting weakened rising trends over NH and even significantly decreasing trends over Trop + SH, while the trends from DGVMs and NIRv kept increasing. The inconsistencies of GPP trends are very likely caused by the contrasting performance between satellite-derived and DGVM simulated vegetation structure parameter (leaf area index, LAI). Therefore, the uncertainty in satellite-based GPP products induced by highly uncertain LAI data in the tropics undermines their roles in assessing the performance of DGVM simulations and understanding the changes of global carbon sinks. The higher consistency between DGVM GPP and NIRv suggests that the trends from a DGVM ensemble might even have better performance than satellite-based GPP products. [ABSTRACT FROM AUTHOR]

Fluctuations in atmospheric CO2 can be measured with great precision and are used to identify human-driven sources as well as natural cycles of ocean and land carbon. One source of variability is the stratosphere, where the influx of aged CO2 -depleted air can produce fluctuations at the surface. This process has been speculated to be a potential source of interannual variability (IAV) in CO2 that might obscure the quantification of other sources of IAV. Given the recent success in demonstrating that the stratospheric influx of N2O - and chlorofluorocarbon-depleted air is a dominant source of their surface IAV in the Southern Hemisphere, I apply the same model and measurement analysis here to CO2. Using chemistry-transport modeling or scaling of the observed N2O variability, I find that the stratosphere-driven surface variability in CO2 is at most 10 % of the observed IAV and is not an important source. Diagnosing the amplitude of the CO2 annual cycle and its increase from 1985 to 2021 through the annual variance gives rates similar to traditional methods in the Northern Hemisphere (BRW, MLO) but can identify the emergence of small trends (0.08 ppm per decade) in the Southern Hemisphere (SMO, CGO). [ABSTRACT FROM AUTHOR]

In the context of climate change, emissions of different species (e.g., carbon dioxide and methane) are not directly comparable since they have different radiative efficiencies and lifetimes. Since comparisons via detailed climate models are computationally expensive and complex, emission metrics were developed to allow a simple and straightforward comparison of the estimated climate impacts of emissions of different species. Emission metrics are not unique and variety of different emission metrics has been proposed, with key choices being the climate impacts and time horizon to use for comparisons. In this paper, we present analytical expressions and describe how to calculate common emission metrics for different species. We include the climate metrics radiative forcing, integrated radiative forcing, temperature change and integrated temperature change in both absolute form and normalised to a reference gas. We consider pulse emissions, sustained emissions and emission scenarios. The species are separated into three types: CO2 which has a complex decay over time, species with a simple exponential decay, and ozone precursors (NOx, CO, VOC) which indirectly effect climate via various chemical interactions. We also discuss deriving Impulse Response Functions, radiative efficiency, regional dependencies, consistency within and between metrics and uncertainties. We perform various applications to highlight key applications of emission metrics, which show that emissions of CO2 are important regardless of what metric and time horizon is used, but that the importance of short lived climate forcers varies greatly depending on the metric choices made. Further, the ranking of countries by emissions changes very little with different metrics despite large differences in metric values, except for the shortest time horizons (GWP20). [ABSTRACT FROM AUTHOR]

So far, scientific analyses have mainly focused on the pros and cons of solar geoengineering or solar radiation management (SRM) as a climate policy option in mere isolation. Here, we put SRM into the context of mitigation by a strictly temperature-target-based approach. As the main innovation, we present a scheme that extends the applicability regime of temperature targets from mitigation-only to SRM-mitigation analyses. We explicitly account for one major category of side effects of SRM while minimizing economic costs for complying with the 2 ∘C temperature target. To do so, we suggest regional precipitation guardrails that are compatible with the 2 ∘C target. Our analysis shows that the value system enshrined in the 2 ∘C target leads to an elimination of most of the SRM from the policy scenario if a transgression of environmental targets is confined to 1/10 of the standard deviation of natural variability. Correspondingly, about half to nearly two-thirds of mitigation costs could be saved, depending on the relaxation of the precipitation criterion. In addition, assuming a climate sensitivity of 3 ∘C or more, in case of a delayed enough policy, a modest admixture of SRM to the policy portfolio might provide debatable trade-offs compared to a mitigation-only future. Also, in our analysis which abstains from a utilization of negative emissions technologies, for climate sensitivities higher than 4 ∘C , SRM will be an unavoidable policy tool to comply with the temperature targets. The economic numbers we present must be interpreted as upper bounds in the sense that cost-lowering effects by including negative emissions technologies are absent. However, with an additional climate policy option such as carbon dioxide removal present, the role of SRM would be even more limited. Hence, our results, pointing to a limited role of SRM in a situation of immediate implementation of a climate policy, are robust in that regard. This limitation would be enhanced if further side effects of SRM are taken into account in a target-based integrated assessment of SRM. [ABSTRACT FROM AUTHOR]

Mitigation of non-CO 2 emissions plays a key role in meeting the Paris Agreement ambitions and sustainable development goals. Implementation of respective policies addressing these targets mainly occur at sectoral and regional levels, and designing efficient mitigation strategies therefore relies on detailed knowledge about the mix of emissions from individual sources and their subsequent climate impact. Here we present a comprehensive dataset of near- and long-term global temperature responses to emissions of CO 2 and individual short-lived climate forcers (SLCFs) from 7 sectors and 13 regions – for both present-day emissions and their continued evolution as projected under the Shared Socioeconomic Pathways (SSPs). We demonstrate the key role of CO 2 in driving both near- and long-term warming and highlight the importance of mitigating methane emissions from agriculture, waste management, and energy production as the primary strategy to further limit near-term warming. Due to high current emissions of cooling SLCFs, policies targeting end-of-pipe energy sector emissions may result in net added warming unless accompanied by simultaneous methane and/or CO 2 reductions. We find that SLCFs are projected to play a continued role in many regions, particularly those including low- to medium-income countries, under most of the SSPs considered here. East Asia, North America, and Europe will remain the largest contributors to total net warming until 2100, regardless of scenario, while South Asia and Africa south of the Sahara overtake Europe by the end of the century in SSP3-7.0 and SSP5-8.5. Our dataset is made available in an accessible format, aimed also at decision makers, to support further assessment of the implications of policy implementation at the sectoral and regional scales. [ABSTRACT FROM AUTHOR]

Can we summarize uncertainties in global response to greenhouse gas forcing with a single number? Here, we assess the degree to which traditional metrics are related to future warming indices using an ensemble of simple climate models together with results from the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). We consider effective climate sensitivity (EffCS), transient climate response (TCR) at CO2 quadrupling (T140) and a proposed simple metric of temperature change 140 years after a quadrupling of carbon dioxide (A140). In a perfectly equilibrated model, future temperatures under RCP8.5 (Representative Concentration Pathway 8.5) are almost perfectly described by T140, whereas in a mitigation scenario such as RCP2.6, both EffCS and T140 are found to be poor predictors of 21st century warming, and future temperatures are better correlated with A140. We show further that T140 and EffCS calculated in full CMIP simulations are subject to errors arising from control model drift and internal variability, with greater relative errors in estimation for T140. As such, if starting from a non-equilibrated state, measured values of effective climate sensitivity can be better correlated with true TCR than measured values of TCR itself. We propose that this could be an explanatory factor in the previously noted surprising result that EffCS is a better predictor than TCR of future transient warming under RCP8.5. [ABSTRACT FROM AUTHOR]

Solar radiation management (SRM) and carbon dioxide removal (CDR) are geoengineering methods that have been proposed to mitigate global warming in the event of insufficient greenhouse gas emission reductions. Here, we have studied temperature and precipitation responses to CDR and SRM with the Representative Concentration Pathway 4.5 (RCP4.5) scenario using the MPI-ESM and CESM Earth system models (ESMs). The SRM scenarios were designed to meet one of the two different long-term climate targets: to keep either global mean (1) surface temperature or (2) precipitation at the 2010–2020 level via stratospheric sulfur injections. Stratospheric sulfur fields were simulated beforehand with an aerosol–climate model, with the same aerosol radiative properties used in both ESMs. In the CDR scenario, atmospheric CO2 concentrations were reduced to keep the global mean temperature at approximately the 2010–2020 level. Results show that applying SRM to offset 21st century climate warming in the RCP4.5 scenario leads to a 1.42 % (MPI-ESM) or 0.73 % (CESM) reduction in global mean precipitation, whereas CDR increases global precipitation by 0.5 % in both ESMs for 2080–2100 relative to 2010–2020. In all cases, the simulated global mean precipitation change can be represented as the sum of a slow temperature-dependent component and a fast temperature-independent component, which are quantified by a regression method. Based on this component analysis, the fast temperature-independent component of the changed atmospheric CO2 concentration explains the global mean precipitation change in both SRM and CDR scenarios. Based on the SRM simulations, a total of 163–199 Tg S (CESM) or 292–318 Tg S (MPI-ESM) of injected sulfur from 2020 to 2100 was required to offset global mean warming based on the RCP4.5 scenario. To prevent a global mean precipitation increase, only 95–114 Tg S was needed, and this was also enough to prevent global mean climate warming from exceeding 2 ∘ above preindustrial temperatures. The distinct effects of SRM in the two ESM simulations mainly reflected differing shortwave absorption responses to water vapour. Results also showed relatively large differences in the individual (fast versus slow) precipitation components between ESMs. [ABSTRACT FROM AUTHOR]

We investigate the climate mitigation potential and collateral effects of direct injections of captured CO2 into the deep ocean as a possible means to close the gap between an intermediate CO2 emissions scenario and a specific temperature target, such as the 1.5 ∘ C target aimed for by the Paris Agreement. For that purpose, a suite of approaches for controlling the amount of direct CO2 injections at 3000 m water depth are implemented in an Earth system model of intermediate complexity. Following the representative concentration pathway RCP4.5, which is a medium mitigation CO2 emissions scenario, cumulative CO2 injections required to meet the 1.5 ∘ C climate goal are found to be 390 Gt C by the year 2100 and 1562 Gt C at the end of simulations, by the year 3020. The latter includes a cumulative leakage of 602 Gt C that needs to be reinjected in order to sustain the targeted global mean temperature. CaCO3 sediment and weathering feedbacks reduce the required CO2 injections that comply with the 1.5 ∘ C target by about 13 % in 2100 and by about 11 % at the end of the simulation. With respect to the injection-related impacts we find that average pH values in the surface ocean are increased by about 0.13 to 0.18 units, when compared to the control run. In the model, this results in significant increases in potential coral reef habitats, i.e., the volume of the global upper ocean (0 to 130 m depth) with omega aragonite > 3.4 and ocean temperatures between 21 and 28 ∘ C, compared to the control run. The potential benefits in the upper ocean come at the expense of strongly acidified water masses at depth, with maximum pH reductions of about -2.37 units, relative to preindustrial levels, in the vicinity of the injection sites. Overall, this study demonstrates that massive amounts of CO2 would need to be injected into the deep ocean in order to reach and maintain the 1.5 ∘ C climate target in a medium mitigation scenario on a millennium timescale, and that there is a trade-off between injection-related reductions in atmospheric CO2 levels accompanied by reduced upper-ocean acidification and adverse effects on deep-ocean chemistry, particularly near the injection sites. [ABSTRACT FROM AUTHOR]

Interannual variations in air–sea fluxes of carbon dioxide (CO2) impact the global carbon cycle and climate system, and previous studies suggest that these variations may be predictable in the near term (from a year to a decade in advance). Here, we quantify and understand the sources of near-term predictability and predictive skill in air–sea CO2 flux on global and regional scales by analyzing output from a novel set of retrospective decadal forecasts of an Earth system model. These forecasts exhibit the potential to predict year-to-year variations in the globally integrated air–sea CO2 flux several years in advance, as indicated by the high correlation of the forecasts with a model reconstruction of past CO2 flux evolution. This potential predictability exceeds that obtained solely from foreknowledge of variations in external forcing or a simple persistence forecast, with the longest-lasting forecast enhancement in the subantarctic Southern Ocean and the northern North Atlantic. Potential predictability in CO2 flux variations is largely driven by predictability in the surface ocean partial pressure of CO2 , which itself is a function of predictability in surface ocean dissolved inorganic carbon and alkalinity. The potential predictability, however, is not realized as predictive skill, as indicated by the moderate to low correlation of the forecasts with an observationally based CO2 flux product. Nevertheless, our results suggest that year-to-year variations in ocean carbon uptake have the potential to be predicted well in advance and establish a precedent for forecasting air–sea CO2 flux in the near future. [ABSTRACT FROM AUTHOR]

Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Intercomparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981-2010) to the future (2070-2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies. [ABSTRACT FROM AUTHOR]

Emission metrics are used to compare the climate effect of the emission of different species, such as carbon dioxide (CO2) and methane (CH4). The most common metrics use linear impulse response functions (IRFs) derived from a single more complex model. There is currently little understanding on how IRFs vary across models, and how the model variation propagates into the metric values. In this study, we first derive CO2 and temperature IRFs for a large number of complex models participating in different intercomparison exercises, synthesizing the results in distributions representing the variety in behaviour. The derived IRF distributions differ considerably, which is partially related to differences among the underlying models, and partially to the specificity of the scenarios used (experimental setup). In a second part of the study, we investigate how differences among the IRFs impact the estimates of global warming potential (GWP), global temperature change potential (GTP) and integrated global temperature change potential (iGTP) for time horizons between 20 and 500 yr. Within each derived CO2 IRF distribution, underlying model differences give similar spreads on the metrics in the range of -20 to +40% (5-95% spread), and these spreads are similar among the three metrics. GTP and iGTP metrics are also impacted by variation in the temperature IRF. For GTP, this impact depends strongly on the lifetime of the species and the time horizon. The GTP of black carbon shows spreads of up to -60 to +80% for time horizons to 100 yr, and even larger spreads for longer time horizons. For CH4 the impact from variation in the temperature IRF is still large, but it becomes smaller for longerlived species. The impact from variation in the temperature IRF on iGTP is small and falls within a range of ±10% for all species and time horizons considered here. We have used the available data to estimate the IRFs, but we suggest the use of tailored intercomparison projects specific for IRFs in emission metrics. Intercomparison projects are an effective means to derive an IRF and its model spread for use in metrics, but more detailed analysis is required to explore a wider range of uncertainties. Further work can reveal which parameters in each IRF lead to the largest uncertainties, and this information may be used to reduce the uncertainty in metric values. [ABSTRACT FROM AUTHOR]

The article discusses the study which examines the possible information from the changes in the strength of the Atlantic Meriodional Overturning Circulation (AMOC) in sea surface height (SSH). The study considered three forcing types such as the increase of carbon dioxide (CO2) concentration and the modification of Southern Ocean winds. Results show that a sea-level difference between the Atlantic and AMOC for freshwater and wind forcing are linear and similar.

The article presents a study which focuses on the investigation of the uncertainties in the methane carbon dioxide (CO2)-equivalence using a simplified global damage potential (GDP). The probability distribution function for the methane GDP was produced by varying input parameters within some reasonable ranges. Results show that the convex damage function is simplifying the rationale for an increase in the methane (CO2)-equivalence in the future global warming unfolds.

The article presents a study which investigates the individual contributions of the transient and stationary eddy components to the main energetic response. The study utilizes the Lorenz Energy Cycle (LEC) to evaluate changes in the global energetic activity due to carbon dioxide doubling in the coupled atmosphere-ocean. It also notes the main features of the carbon dioxide warming pattern such as tropical upper-tropospheric warming and high-latitude surface warming.