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The role of nature restoration in mitigating the impacts of climate change is receiving increasing attention, yet the mitigation potential is often assessed in terms of carbon removal rather than the ability to meet temperature goals, such as those outlined in the Paris Agreement. Here, we estimate the global removal potential from nature restoration constrained by a “responsible development” framework and the contribution this would make to a 1.5°C temperature limit. Our constrained restoration options result in a median of 103 GtC (5%–95% range of −91 to 196 GtC) in cumulative removals between 2020 and 2100. When combined with deep-decarbonization scenarios, our restoration scenario briefly exceeds 1.5°C before declining to between 1.25°C and 1.5°C by 2100 (median, 50% probability). We conclude that additional carbon sequestration via nature restoration is unlikely to be done quickly enough to notably reduce the global peak temperatures expected in the next few decades. Land restoration is an important option for tackling climate change but cannot compensate for delays in reducing fossil fuel emissions.

Repository reproducing plots and processing used in Dooley et al., 2022 (One Earth, https://doi.org/10.1016/j.oneear.2022.06.002). For questions and comments about the paper, please contact Kate Dooley (kate.dooley@unimelb.edu.au). For questions and comments about the code, please contact Zebedee Nicholls (zebedee.nicholls@climate-energy-college.org). For full details, please see https://gitlab.com/znicholls/one-earth-2022., {"references":["Dooley et al. 2022 (One Earth, https://doi.org/10.1016/j.oneear.2022.06.002)"]}

Scientifically rigorous guidance to policy makers on mitigation options for meeting the Paris Agreement long-term temperature goal requires an evaluation of long-term global-warming implications of greenhouse gas emissions pathways. Here, we present a uniform and transparent methodology to evaluate the climate outcome, and hence the Paris Agreement consistency of influential institutional emission scenarios from the grey literature, including those from the International Energy Agency1,2, BP3, and Shell4. We first identify challenges to performing such an assessment and then proceed to outline a sequence of steps to address these challenges by harmonizing5 all emissions to a consistent base-year (2010), extending all pathways to 2100, and filling in missing emission species6. We employ two simple climate models, MAGICC7 and FaIR8,9 to assess peak and end-of-century temperatures, and find that few published scenarios that claim to be compatible with the Paris Agreement are so. References 1. International Energy Agency. World Energy Outlook 2020. (2020).2. International Energy Agency. Net Zero by 2050 - A Roadmap for the Global Energy Sector. (2021).3. BP. Global Energy Outlook 2020. (2020).4. Shell. The Energy Transformation Scenarios. (2021) 5. Gidden, M. J. et al. A methodology and implementation of automated emissions harmonization for use in Integrated Assessment Models. Environ. Model. Softw. 105, 187–200 (2018)6. Lamboll, R. D., Nicholls, Z. R. J., Kikstra, J. S., Meinshausen, M. & Rogelj, J. Silicone v1.0.0 : an open-source Python package for inferring missing emissions data for climate change research. Geosci. Model Dev 13, 5259–5275 (2020)7. Meinshausen, M., Raper, S. C. B. & Wigley, T. M. L. Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration. Atmos. Chem. Phys. 11, 1417–1456 (2011).8. Smith, C. J. et al. FAIR v1.3: A simple emissions-based impulse response and carbon cycle model. Geosci. Model Dev. 11, 2273–2297 (2018)9. Millar, J. R., Nicholls, Z. R., Friedlingstein, P. & Allen, M. R. A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions. Atmos. Chem. Phys. 17, 7213–7228 (2017).

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 CO2 concentrations by means of large net negative CO2 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 CO2, 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 CO2 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.

Over the last five years prior to the Glasgow Climate Pact

Producing targeted climate information at the local scale, including major sources of climate change projection uncertainty for diverse emissions scenarios, is essential to support climate change mitigation and adaptation efforts. Here, we present the first chain of computationally efficient Earth System Model (ESM) emulators allowing to rapidly translate greenhouse gas emission pathways into spatially resolved annual-mean temperature anomaly field time series, accounting for both forced climate response and natural variability uncertainty at the local scale. By combining the global-mean, emissions-driven emulator MAGICC with the spatially resolved emulator MESMER, ESM-specific as well as constrained probabilistic emulated ensembles can be derived. This emulation chain can hence build on and extend large multi-ESM ensembles such as the ones produced within the 6th phase of the Coupled Model Intercomparison Project (CMIP6). The main extensions are threefold. (i) A more thorough sampling of the forced climate response and the natural variability uncertainty is possible with millions of emulated realizations being readily created. (ii) The same uncertainty space can be sampled for any emission pathway, which is not the case in CMIP6, where some of the most societally relevant strong mitigation scenarios have been run by only a small number of ESMs. (iii) Other lines of evidence to constrain future projections, including observational constraints, can be introduced, which helps to refine projected future ranges beyond the multi-ESM ensemble's estimates. In addition to presenting results from the coupled MAGICC-MESMER emulator chain, we carry out an extensive validation of MESMER, which is trained on and applied to multiple emission pathways for the first time in this study. The newly developed MAGICC-MESMER coupled emulator will allow unprecedented assessments of the implications of manifold emissions pathways at regional scale.

Significance Sea-level rise poses a threat to coastal areas and will continue for centuries, even after global mean temperature has stabilized. Research assessing the implications of current international climate mitigation efforts usually focuses on 21st century climate impacts. The multicentennial sea-level rise commitment of pledged near-term emission reduction efforts under the Paris Agreement has not been quantified yet. We here estimate this sea-level rise commitment and find that pledged emissions until 2030 lock in 1-m sea-level rise in the year 2300. Our analysis highlights the defining role of present-day emissions for future sea-level rise and points to the potential of reducing the long-term sea-level-rise commitment by more ambitious national emission reduction targets., The main contributors to sea-level rise (oceans, glaciers, and ice sheets) respond to climate change on timescales ranging from decades to millennia. A focus on the 21st century thus fails to provide a complete picture of the consequences of anthropogenic greenhouse gas emissions on future sea-level rise and its long-term impacts. Here we identify the committed global mean sea-level rise until 2300 from historical emissions since 1750 and the currently pledged National Determined Contributions (NDC) under the Paris Agreement until 2030. Our results indicate that greenhouse gas emissions over this 280-y period result in about 1 m of committed global mean sea-level rise by 2300, with the NDC emissions from 2016 to 2030 corresponding to around 20 cm or 1/5 of that commitment. We also find that 26 cm (12 cm) of the projected sea-level-rise commitment in 2300 can be attributed to emissions from the top 5 emitting countries (China, United States of America, European Union, India, and Russia) over the 1991–2030 (2016–2030) period. Our findings demonstrate that global and individual country emissions over the first decades of the 21st century alone will cause substantial long-term sea-level rise.

Scientifically rigorous guidance to policy makers on mitigation options for meeting the Paris Agreement long-term temperature goal requires an evaluation of long-term global-warming implications of greenhouse gas emissions pathways. Here we employ a uniform and transparent methodology to evaluate Paris Agreement compatibility of influential “institutional” emission scenarios from the grey literature. We compare a selection of these scenarios analyzed with this methodology to the Integrated Assessment Model scenarios assessed by the Intergovernmental Panel on Climate Change. We harmonize emissions to a consistent base-year and account for all greenhouse gases and aerosol precursor emissions, ensuring a self-consistent comparison of climate variables. An evaluation of peak and end-of-century temperatures is made, with both being relevant to the Paris Agreement goal. We find that few published scenarios that claim to be compatible with the Paris Agreement are so, and investigate root causes based on the underlying energy system transformation.

It is still possible to comply with the Paris Climate Agreement to maintain a global temperature ‘well below +2.0 °C’ above pre-industrial levels. We present two global non-overshoot pathways (+2.0 °C and +1.5 °C) with regional decarbonization targets for the four primary energy sectors—power, heating, transportation, and industry—in 5-year steps to 2050. We use normative scenarios to illustrate the effects of efficiency measures and renewable energy use, describe the roles of increased electrification of the final energy demand and synthetic fuels, and quantify the resulting electricity load increases for 72 sub-regions. Non-energy scenarios include a phase-out of net emissions from agriculture, forestry, and other land uses, reductions in non-carbon greenhouse gases, and land restoration to scale up atmospheric CO2 removal, estimated at −377 Gt CO2 to 2100. An estimate of the COVID-19 effects on the global energy demand is included and a sensitivity analysis describes the impacts if implementation is delayed by 5, 7, or 10 years, which would significantly reduce the likelihood of achieving the 1.5 °C goal. The analysis applies a model network consisting of energy system, power system, transport, land-use, and climate models.

Games that show how mathematics can solve the apparently unsolvable. This book presents a series of engaging games that seem unsolvable—but can be solved when they are translated into mathematical terms. How can players find their ID cards when the cards are distributed randomly among twenty boxes? By applying the theory of permutations. How can a player guess the color of her own hat when she can only see other players' hats? Hamming codes, which are used in communication technologies. Like magic, mathematics solves the apparently unsolvable. The games allow readers, including university students or anyone with high school–level math, to experience the joy of mathematical discovery. The authors set up each game, specifying the number of players and props needed, and show readers how mathematical language reveals the problem's underlying structure. They explain the mathematical concepts with many examples, describe the history of the problem, and offer practical advice. Colorful and clever illustrations, featuring a flock of mathematically inclined ravens, help clarify things. All of the games can be presented to an audience; each one runs from sixty to ninety minutes, suitable for seminar presentations or lectures. The authors aim at maintaining mathematical precision while avoiding overly complex notation. Appendixes go into more detail, reviewing frequently used mathematical symbols, providing further information on a range of mathematical concepts, and offering chapter-specific mathematical explanations.

Global emissions scenarios play a critical role in the assessment of strategies to mitigate climate change and their related societal transformations. The current generation of scenarios, however, are criticized because they rely heavily on net negative CO2 emissions (NNCE) that result from allowing temperature limits to be temporarily exceeded. In this study we present a new set of emissions scenarios that exclude NNCE. We show that such scenarios require a more rapid near-term transformation with significant long-term gains for the economy (even without considering the benefits of avoided climate impacts). Scenarios that avoid temperature overshoot and NNCE are thus not only economically more attractive over the long term, they also involve lower climate risks. Our study further identifies possible alternative configurations of net-zero CO2 emissions systems and the distinct roles of different sectors and regions in order to balance emissions sources and sinks.

The remaining carbon budget represents the total amount of CO2 that can still be emitted in the future while limiting global warming to a given temperature target. Remaining carbon budget estimates range widely, however, and this uncertainty can be used to either trivialize the most ambitious mitigation targets by characterizing them as impossible, or to argue that there is ample time to allow for a gradual transition to a low-carbon economy. Neither of these extremes is consistent with our best understanding of the policy implications of remaining carbon budgets. Understanding the scientific and socio-economic uncertainties affecting the size of the remaining carbon budgets, as well as the methodological choices and assumptions that underlie their calculation, is essential before applying them as a policy tool. Here we provide recommendations on how to calculate remaining carbon budgets in a traceable and transparent way, and discuss their uncertainties and implications for both international and national climate policies. ISSN:1752-0908 ISSN:1752-0894

The assessment of long-term greenhouse gas emissions scenarios and societal transformation pathways is a key component of the IPCC Working Group 3 (WG3) on the Mitigation of Climate Change. A large scientific community, typically using integrated assessment models and econometric frameworks, supports this assessment in understanding both near-term actions and long-term policy responses and goals related to mitigating global warming. WG3 must systematically assess hundreds of scenarios from the literature to gain an in-depth understanding of long-term emissions pathways, across all sectors, leading to various levels of global warming. Systematic assessment and understanding the climate outcomes of each emissions scenario, requires coordinated processes which have developed over consecutive IPCC assessments. Here, we give an overview of the processes involved in the systematic assessment of long-term mitigation pathways as used in recent IPCC Assessments1 and being further developed for the IPCC 6th Assessment Report (AR6). The presentation will explain how modelling teams can submit scenarios to AR6 and invite feedback to the process.Following discussions amongst IPCC Lead Authors to define the scope of scenarios desired and variables requested, a call for scenarios to support AR6 was launched in September 2019. Modelling teams have registered and submitted scenarios through Autumn 2019 using a new and secure online submission portal, from which authorised Lead Authors can interrogate the scenarios interactively.This analysis is underpinned by the open-source software pyam, a Python package specifically designed for analysis and visualisation of integrated assessment scenarios2. Submitted scenarios are automatically checked for errors and processed using a new climate assessment pipeline. The climate assessment involves infilling and harmonization3 of emissions data, then the scenarios are processed through Simple Climate Models, using the OpenSCM framework4, to give probabilistic climate implications for each scenario – atmospheric concentrations, radiative forcing and global mean temperature. The climate assessment accounts for updated climate sensitivity estimates from CMIP6 and WG1,s scenarios are categorized according to climate outcomes and distinguish between timing and levels of net-negative emissions, emissions peak and temperature overshoot. Scenarios are also categorized by other indicators, for consistent use across WG3 chapters, such as: population and GDP; Primary and Final energy use; and shares of renewables, bioenergy and fossil fuels.The automated framework also facilitates bolt-on analyses, such as estimating the population impacted by biophysical climate impacts5, and estimates of avoided damages with the social cost of carbon6.Upon publication of the WG3 AR6 report, all scenario data used in the WG3 Assessment will be publicly available on a Scenario Explorer, an online tool for interrogating and visualizing the data that supports the report. In combination, this framework brings new levels of consistency, transparency and reproducibility to the assessment of scenarios in IPCC WG3 and will be a key resource for the climate community in understanding the main drivers of different transformation pathways.Huppmman et al 2018, Nature Climate Change Gidden and Huppmann, 2019, Journal of Open Source Software Gidden et al 2018 Environ. Model. Softw Nicholls et al 2020 Byers et al 2018 Environmental Research Letters Ricke et al 2018 Nature Climate Change

Consistent and comparable climate assessments of scenarios are critical within the context of IPCC assessment reports. Given the number of scenarios assessed by WG3, the assessment “pipeline” must be almost completely automated. Here, we present the application of a new assessment pipeline which combines state-of-the-art components into a single workflow in order to derive climate outcomes for integrated assessment model (IAM) scenarios assessed by WG3 of the IPCC. A consistent analysis ensures that WG3’s conclusions about the socioeconomic transformations required to maintain a safe climate are based on the best understanding of our planetary boundaries from WG1. For example, if WG1 determines that climate sensitivity is higher than previously considered, then WG3 could incorporate this insight by e.g. considering much smaller remaining carbon budgets for any given temperature target. The scenario-climate assessment pipeline is comprised of three primary components. First, a consistent harmonization algorithm which maintains critical model characteristics between harmonized and unharmonized scenarios [1] is employed to harmonize emissions trajectories to a common and consistent historical dataset as used in CMIP6 [2]. Next, a scenario’s reported emissions trajectories are analyzed as to the completeness of its species and sectoral coverage. A consistent set of 14 emissions species are expected, aligning with published work within ScenarioMIP and CMIP6 (see ref [2], Table 2). Should any component of this full set of emissions trajectories be absent for a given scenario, an algorithm (e.g., generalised quantile walk [3]) is employed in order to “back-fill” missing species at the native model regional resolution. Finally, full emissions scenarios are analyzed by an Earth System Model emulator, e.g., MAGICC [4]. In this presentation, we explore differences in climate assessments and estimated remaining carbon budgets across various components of the pipeline for available scenarios in the literature. We consider the impact of alternative choices, especially those made in prior assessments by the IPCC (AR5, SR15), including, for example, the historical emissions database used, the effect of harmonization and back-filling, as well as the version and setup of MAGICC used. References [1] Gidden, M.J., Fujimori, S., van den Berg, M., Klein, D., Smith, S.J., van Vuuren, D.P. and Riahi, K., 2018. A methodology and implementation of automated emissions harmonization for use in Integrated Assessment Models. Environmental Modelling & Software, 105, pp.187-200. [2] Gidden, M. J., Riahi, K., Smith, S. J., Fujimori, S., Luderer, G., Kriegler, E., van Vuuren, D. P., van den Berg, M., Feng, L., Klein, D., Calvin, K., Doelman, J. C., Frank, S., Fricko, O., Harmsen, M., Hasegawa, T., Havlik, P., Hilaire, J., Hoesly, R., Horing, J., Popp, A., Stehfest, E., and Takahashi, K.: Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century, Geosci. Model Dev., 12, 1443-1475, https://doi.org/10.5194/gmd-12-1443-2019, 2019. [3] Teske, S. et al., Achieving the Paris Climate Agreement Goals. Springer, 2019. [4] Meinshausen, M., Raper, S.C. and Wigley, T.M., 2011. Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6–Part 1: Model description and calibration. Atmospheric Chemistry and Physics, 11(4), pp.1417-1456.

Here we present results from the first phase of the Reduced Complexity Model Intercomparison Project (RCMIP). RCMIP is a systematic examination of reduced complexity climate models (RCMs), which are used to complement and extend the insights from more complex Earth System Models (ESMs), in particular those participating in the Sixth Coupled Model Intercomparison Project (CMIP6). In Phase 1 of RCMIP, with 14 participating models namely ACC2, AR5IR (2 and 3 box versions), CICERO-SCM, ESCIMO, FaIR, GIR, GREB, Hector, Held et al. two layer model, MAGICC, MCE, OSCAR and WASP, we highlight the structural differences across various RCMs and show that RCMs are capable of reproducing global-mean surface air temperature (GSAT) changes of ESMs and historical observations. We find that some RCMs are capable of emulating the GSAT response of CMIP6 models to within a root-mean square error of 0.2 °C (of the same order of magnitude as ESM internal variability) over a range of scenarios. Running the same model configurations for both RCP and SSP scenarios, we see that the SSPs exhibit higher effective radiative forcing throughout the second half of the 21st Century. Comparing our results to the difference between CMIP5 and CMIP6 output, we find that the change in scenario explains approximately 46 % of the increase in higher end projected warming between CMIP5 and CMIP6. This suggests that changes in ESMs from CMIP5 to CMIP6 explain the rest of the increase, hence the higher climate sensitivities of available CMIP6 models may not be having as large an impact on GSAT projections as first anticipated. A second phase of RCMIP will complement RCMIP Phase 1 by exploring probabilistic results and emulation in more depth to provide results available for the IPCC's Sixth Assessment Report author teams.

Under the bottom-up architecture of the Paris Agreement, countries pledge Nationally Determined Contributions (NDCs). Current NDCs individually align, at best, with divergent concepts of equity and are collectively inconsistent with the Paris Agreement. We show that the global 2030-emissions of NDCs match the sum of each country adopting the least-stringent of five effort-sharing allocations of a well-below 2 °C-scenario. Extending such a self-interested bottom-up aggregation of equity might lead to a median 2100-warming of 2.3 °C. Tightening the warming goal of each country’s effort-sharing approach to aspirational levels of 1.1 °C and 1.3 °C could achieve the 1.5 °C and well-below 2 °C-thresholds, respectively. This new hybrid allocation reconciles the bottom-up nature of the Paris Agreement with its top-down warming thresholds and provides a temperature metric to assess NDCs. When taken as benchmark by other countries, the NDCs of India, the EU, the USA and China lead to 2.6 °C, 3.2 °C, 4 °C and over 5.1 °C warmings, respectively., The Paris Agreement includes bottom-up pledges and top-down warming threshold. Under this setting where countries effectively choose their own fairness principle, this article assesses the global warming implied by each Nationally Determined Contribution to inform the future ratcheting-up process.

Limiting global warming to a 1.5°C temperature rise requires drastic emissions reductions and removal of carbon-dioxide from the atmosphere. Most modelled pathways for 1.5°C assume substantial removals in the form of biomass energy with carbon capture and storage, which brings with it increasing risks to biodiversity and food security via extensive land-use change. Recently, multiple efforts to describe and quantify potential removals via ecosystem-based approaches have gained traction in the climate policy discourse. However, these options have yet to be evaluated in a systematic and scientifically robust way. We provide spatially explicit estimates of ecosystem restoration potential quantified with a Dynamic Global Vegetation Model. Simulations covering forest restoration, reforestation, reduced harvest, agroforestry and silvopasture were combined and found to sequester an additional 93 Gt C by 2100, reducing mean global temperature increase by ∼0.12°C (5%–95% range 0.06°C–0.21°C) relative to a baseline mitigation pathway. Ultimately, pathways to achieving the 1.5°C goal garner broader public support when they include land management options that can bring about multiple benefits, including ecosystem restoration, biodiversity protection, and resilient agricultural practices.

The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercomparison Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000 transient simulations serve to investigate the response to (mainly) natural forcing under background conditions not too different from today, and to discriminate between forced and internally generated variability on interannual to centennial timescales. This paper describes the motivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents orbital, solar, volcanic, and land use/land cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849 CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 experiments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simulations have been divided into three tiers. A default forcing data set has been defined for the Tier 1 (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated Tier 2 simulations. Additional experiments (Tier 3) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simulations. This paper outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instrumental data).

Data related to ourpublication about remaining carbon budget assessment frameworks.

Anthropogenic increases of atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The Integrated Assessment community quantified anthropogenic emissions for the Shared Socioeconomic Pathways (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentration for these SSP scenarios – using the reduced complexity climate-carbon cycle model MAGICC7.0. We extend historical, observationally-based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios respectively. We also provide the concentration extensions beyond 2100 based on assumptions in the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from today 66 % to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterisations that reflect the Oslo Line by Line model results. In comparison to the RCPs, the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) are more evenly spaced in terms of their expected global-mean temperatures, extend to lower 2100 temperatures and sea level rise than the RCP set. Performing 2 pairs of 6-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the MAM season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼ 5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies’ projections over the next 100 to 500 years unequivocally depict a ‘hockey-stick’ upwards shape – it is a collective choice whether the hothouse pathway is pursued or whether we manage climate damages to the SSP1-1.9 equivalent of around 1.5 °C warming.

The amount of additional future temperature change following a complete cessation of CO2 emissions is a measure of the unrealized warming to which we are committed due to CO2 already emitted to the atmosphere. This "Zero Emissions Commitment" (ZEC) is also an important quantity when estimating the remaining carbon budget – a limit on the total amount of CO2 emissions consistent with limiting global mean temperature at a particular level. In the recent IPCC Special Report on Global Warming of 1.5 °C, the carbon budget framework used to calculate the remaining carbon budget for 1.5 °C included the assumption that the ZEC due to CO2 emissions is negligible and close to zero. Previous research has shown significant uncertainty even in the sign of the ZEC. To close this knowledge gap, we propose the Zero Emissions Commitment Model Intercomparison Project (ZECMIP), which will quantify the amount of unrealized temperature change that occurs after CO2 emissions cease and investigate the geophysical drivers behind this climate response. Quantitative information on ZEC is a key gap in our knowledge, and one that will not be addressed by currently planned CMIP6 simulations, yet it is crucial for verifying whether carbon budgets need to be adjusted to account for any unrealized temperature change resulting from past CO2 emissions. We request only one top priority simulation from comprehensive general circulation Earth System Models (ESMs) and Earth System Models of Intermediate Complexity (EMICs) – a branch from the 1 % CO2 run with CO2 emissions set to zero at the point of 1000 PgC of total CO2 emissions in the simulation – with the possibility for additional simulations, if resources allow. ZECMIP is part of CMIP6, under joint sponsorship by C4MIP and CDRMIP, with associated experiment names to enable data submissions to Earth System Grid Federation. All data will be published and made freely available.