The concept of a remaining carbon budget associated with global warming levels has underpinned mitigation efforts since the Paris Agreement. However, as observed temperatures near 1.5 degrees, a number of challenges have emerged for the continued use of carbon budgets to frame mitigation needs. Firstly, while the transient response to cumulative emissions describes the temperature response to constant emissions - Paris-compatible pathways require deep emissions cuts and potentially extended periods of negative emissions, the temperature outcome of which is complicated by zero emissions commitments and non-CO2 responses. Understanding of Zero emissions commitments has been thus far been primarily informed by idealised experiments which terminate emissions during an idealised concentration ramp - but these metrics are subject to unrealistic termination shocks and model-specific emissions pathways. Second, non-CO2 responses remain highly uncertain, and recent satellite observations of global radiative imbalance raise further questions on the adequacy of current modeling platforms to describe the warming which should be expected due to aerosol phaseout. Here, we consider how two novel developments impact carbon budgets beyond estimates presented in the IPCC 6th Assessment. Firstly, we present an ESM ensemble of climate reversibility experiments which provides a more realistic proxy for non-TCRE carbon dynamics during a net zero transition for use in carbon budgets. Secondly, we consider how the inclusion of recent global mean temperature measurements and CERES top of atmosphere radiative flux measurements would impacts the calibration of simple climate models - with subsequent impacts on both estimates of both TCRE and expected warming due to non-CO2 effects. Synthesising this information, we provide an updated estimate of carbon budgets and timing with respect to the 1.5 and 2 degree thresholds.

Climate policies evolve quickly, and new scenarios designed around these policies are used to illustrate how they impact global mean temperatures using simple climate models (or climate emulators). Simple climate models are extremely efficient, although some can only provide global estimates of climate metrics such as mean surface temperature, CO2 concentration and effective radiative forcing. Within the Intergovernmental Panel on Climate Change (IPCC) framework, understanding of the regional impacts of scenarios that include the most recent science is needed to allow targeted policy decisions to be made quickly. To address this, we present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), a new flexible probabilistic framework which aims to provide an efficient mechanism to run new scenarios without the significant overheads of larger, more complex Earth system models (ESMs). PRIME provides the capability to include features of the most recent ESM projections, science and scenarios to run ensemble simulations on multi-centennial timescales and include analyses of many key variables that are relevant and important for impact assessments. We use a simple climate model to provide the global temperature response to emissions scenarios. These estimated temperatures are used to scale monthly mean patterns from a large number of CMIP6 ESMs. These patterns provide the inputs to a “weather generator” algorithm and a land surface model. The PRIME system thus generates an end-to-end estimate of the land surface impacts from the emissions scenarios. We test PRIME using known scenarios in the form of the shared socioeconomic pathways (SSPs), to demonstrate that our model reproduces the ESM climate responses to these scenarios. We show results for a range of scenarios: the SSP5–8.5 high-emissions scenario was used to define the patterns, and SSP1–2.6, a mitigation scenario with low emissions, and SSP5–3.4-OS, an overshoot scenario, were used as verification data. PRIME correctly represents the climate response (and spread) for these known scenarios, which gives us confidence our simulation framework will be useful for rapidly providing probabilistic spatially resolved information for novel climate scenarios, thereby substantially reducing the time between new scenarios being released and the availability of regional impact information.

Given the pivotal role of probabilistic approaches with two-layer energy balance models in the latest climate assessment, this study aims to gain deeper insight into their advancement by comparing different approaches for generating constrained posterior ensembles. Several methodological improvements are possible both in the calibration of model parameters to the behavior of comprehensive Earth system models and in constraining the calibrated parameter ensemble with other lines of evidence. The results imply that a conventional single parameter representing evolving climate feedback characteristics is not a requirement for reliable climate projections; rather, there are potential improvements on the forcing side regarding the separation of forcing and feedbacks. Constraining the ensemble based on observational and expert-assessed climate metrics, which critically affects probabilistic climate assessment, needs to appropriately deal with different constraints on a multivariate space in a standardized and flexible way. The method introduced here is an option that fulfills the need.

The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, "esm-flat10", has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 - the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as "fast track" simulations.

Regional climate impacts studies are usually predicated on output from fully-coupled Earth system models, which, due to computational constraints, can only simulate a limited number of scenarios and ensemble members. Using the PRIME system, we can simulate spatially resolved impacts quickly - emulating the response of 34 CMIP6 models, and generating ensemble members that capture the IPCC assessed range of equilibrium climate sensitivity (ECS). We assess the tail risks associated with high ECS simulations on critical tropical and boreal forest ecosystems over the 21st century and beyond, using three policy-relevant strong-mitigation IPCC WG3 emissions scenarios with different relationships to 1.5°C global warming. We quantify the future resilience and risk of dieback across these ecosystems, focus on the reversibility of loss using a temperature overshoot-and-return scenario and delineate hazardous climatic space for the Amazon basin, with climate-boundaries consistent with the literature. We show that despite using emissions scenarios which achieve 1.5 and 2 degrees Paris Agreement targets, uncertainty in ECS exhibits unavoidable risk of Amazon forest health decline and dieback, further highlighting the requirement for urgent, focused, global mitigative actions.

The effective radiative forcing (ERF) is a robust predictor of future equilibrium warming. It is generally assumed that the ERF depends only on changes in atmospheric constituents and is independent of the background climate state. Building on recent work demonstrating that, in contrast, the instantaneous radiative forcing (IRF) for CO2 is strongly state-dependent, we show that the ERF for CO2 also increases in warmer climate states. We analyse a 4×CO2 atmosphere-only forcing in both control and warmer climate states in eight CMIP6-era models. Four models participated in the Cloud Feedback Model Intercomparison Project (CFMIP) which used pre-industrial SSTs in its control state and SSTs from near the end of the same model’s coupled abrupt-4×CO2 run in its warm state. In the other four models we used an AMIP climatology as the control state and a uniform increase in SSTs of 4 K above this AMIP climatology in the warm state. All eight models show an increase in 4×CO2 ERF, ranging from 0.1-0.5 W m-2, translating to a relative increase of 0.02-0.09 W m-2 K-1 or 0.2-1.1 % K-1. The increase is statistically significant in five of the eight models.Our findings have implications for derivation of simplified relationships of climate warming, for instance in the calculations of global warming metrics and in economic models, from which future climate change risks being underpredicted without a temperature adjustment.We also run aerosol forcing experiments under the +4 K climate, for which there is less agreement between models, but some show large changes in aerosol ERF under the warmer climate state, with potential implications for our ability to discern transient warming even with a more accurate understanding of present-day aerosol forcing.

It is crucial to explore multi-century sea level responses under different emissions scenarios despite underlying physical uncertainties that rapidly increase over time, because resulting coastal risks fully manifest only on these longer timescales. Here, we use a set of climate and sea level emulators to investigate sea level rise commitments out to 2300 for cumulative emission levels at the start of every remaining 21st century decade under the five illustrative SSP-RCP scenarios. Our results indicate that emissions until 2030 “lock in” around 1.0 m (66% model range: 0.8 to 1.3 m) of global mean sea level rise in 2300 relative to 1995-2014. Under an intermediate emissions scenario roughly in line with current climate policies (SSP2-4.5), median 2300 global mean sea level commitments for cumulative emissions in 2050 (1.2 m) and 2100 (1.7 m) would be around 0.1 m and 0.6 m higher than under a very low emissions scenario (SSP1-1.9). Global results are also downscaled to selected regional sites and highlight that particularly vulnerable regions like low-lying Pacific Islands will experience higher local committed sea level rise than the global average. By attributing projected sea level rise commitments in 2300 to different cumulative emission levels in the 21st century, the study aims to more clearly link mitigation efforts in the near term to longer term coastal risk and to inform minimum adaptation requirements under different climate futures.

Forestation is widely proposed for carbon dioxide (CO2) removal, but its impact on climate through changes to atmospheric composition and surface albedo remains relatively unexplored. We assessed these responses using two Earth system models by comparing a scenario with extensive global forest expansion in suitable regions to other plausible futures. We found that forestation increased aerosol scattering and the greenhouse gases methane and ozone following increased biogenic organic emissions. Additionally, forestation decreased surface albedo, which yielded a positive radiative forcing (i.e., warming). This offset up to a third of the negative forcing from the additional CO2 removal under a 4°C warming scenario. However, when forestation was pursued alongside other strategies that achieve the 2°C Paris Agreement target, the offsetting positive forcing was smaller, highlighting the urgency for simultaneous emission reductions.

Anaplastic lymphoma kinase (ALK)-fusion sarcomas are rare part of the emerging theoretically targetable tyrosine kinase RAS::MAPK pathway fusion myopericytic-ovoid sarcomas. We report our clinicopathologic and treatment experience with an ALK fusion sarcoma. A novel ELKS/RAB6-interacting/CAST family member 1-unaligned ALK fusion infiltrative nonmetastatic low-grade sarcoma of the right hand of a 15-month-old male was treated with crizotinib, an ALK tyrosine kinase inhibitor as oral monotherapy, inducing complete radiographic and clinical resolution by 10 months and sustained response now over 12 months after elective discontinuation. Crizotinib can successfully be used to treat unresectable novel ALK fusion sarcomas.

The remaining carbon budget (RCB), the net amount of CO 2 humans can still emit without exceeding a chosen global warming limit, is often used to evaluate political action against the goals of the Paris Agreement. RCB estimates for 1.5 °C are small, and minor changes in their calculation can therefore result in large relative adjustments. Here we evaluate recent RCB assessments by the IPCC and present more recent data, calculation refinements and robustness checks that increase confidence in them. We conclude that the RCB for a 50% chance of keeping warming to 1.5 °C is around 250 GtCO 2 as of January 2023, equal to around six years of current CO 2 emissions. For a 50% chance of 2 °C the RCB is around 1,200 GtCO 2 . Key uncertainties affecting RCB estimates are the contribution of non-CO 2 emissions, which depends on socioeconomic projections as much as on geophysical uncertainty, and potential warming after net zero CO 2 .

Forestation is widely proposed for carbon dioxide (CO 2 ) removal, but its impact on climate through changes to atmospheric composition and surface albedo remains relatively unexplored. We assessed these responses using two Earth system models by comparing a scenario with extensive global forest expansion in suitable regions to other plausible futures. We found that forestation increased aerosol scattering and the greenhouse gases methane and ozone following increased biogenic organic emissions. Additionally, forestation decreased surface albedo, which yielded a positive radiative forcing (i.e., warming). This offset up to a third of the negative forcing from the additional CO 2 removal under a 4°C warming scenario. However, when forestation was pursued alongside other strategies that achieve the 2°C Paris Agreement target, the offsetting positive forcing was smaller, highlighting the urgency for simultaneous emission reductions.

The reformulation of the Met Office's dynamical core for weather and climate prediction previously described by the authors is extended to spherical domains using a cubed-sphere mesh. This paper updates the semi-implicit mixed finite-element formulation to be suitable for spherical domains. In particular the finite-volume transport scheme is extended to take account of non-uniform, non-orthogonal meshes and uses an advective-then-flux formulation so that increment from the transport scheme is linear in the divergence. The resulting model is then applied to a standard set of dry dynamical core tests and compared to the existing semi-implicit semi-Lagrangian dynamical core currently used in the Met Office's operational model.

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide. With an atmospheric lifetime of around a decade, methane mitigation starting immediately has the potential to avoid substantial levels of additional warming by mid-century. In addition to the methane emissions reductions that are necessary to limit warming, we address the question of whether technological methane removal can provide additional benefits by avoiding global mean surface temperatures exceeding 1.5 ^∘ C above pre-industrial—the high-ambition Paris Agreement climate goal. Using an adaptive emissions methane removal routine in a simple climate model, we successfully limit peak warming to 1.5 ^∘ C for overshoots of up to around 0.3 ^∘ C. For substantially higher overshoots, methane removal alone is unable to limit warming to 1.5 ^∘ C, but in an extreme scenario could limit peak warming by an ensemble median 0.7 ^∘ C if all atmospheric methane was removed, requiring huge levels of net removal on the order of tens of petagrams cumulatively. The efficacy of methane removal depends on many emergent properties of the climate system, including climate sensitivity, aerosol forcing, and the committed warming after net zero CO _2 (zero emissions commitment). To avoid overshooting 1.5 ^∘ C in the low-overshoot, strong-mitigation SSP1-1.9 scenario, a median cumulative methane removal of 1.2 PgCH _4 is required, though this may be much higher if climate sensitivity is high or the zero emissions commitment is positive, and in these cases may require ongoing methane removal long after peak warming in order to stabilise warming below 1.5 ^∘ C.

The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.

For effective radiative forcing (ERF) to be an ideal metric for comparing the strength of different climate drivers (such as CO2 and aerosols), the ratio of radiative forcing to global-mean temperature change must be the same for each driver. Typically, this ratio is divided by the same ratio for CO2 and termed efficacy. Previously it has been shown that efficacy is close to unity in abrupt perturbation experiments for a range of climate drivers, but efficacy with respect to CO2 has not been investigated in transient realistic simulations. Here, we analyse transient simulations from CMIP6 experiments and show comparable results between transient and abrupt perturbation experiments. We demonstrate that aerosol efficacy is not significantly different from unity, however inter-model differences in aerosol experiments are notably large.

Simple climate models (also known as emulators) have re-emerged as critical tools for the analysis of climate policy. Emulators are efficient and highly parameterised, where the parameters are tunable to produce a diversity of global mean surface temperature (GMST) response pathways to a given emission scenario. Only a small fraction of possible parameter combinations will produce historically consistent climate hindcasts, a necessary condition for trust in future projections. Alongside historical GMST, additional observed (e.g. ocean heat content) and emergent climate metrics (such as the equilibrium climate sensitivity) can be used as constraints upon the parameter sets used for climate projections. This paper describes a multi-variable constraining package for the Finite-amplitude Impulse Response (FaIR) simple climate model (FaIR versions 2.1.0 onwards) using a Bayesian framework. The steps are, first, to generate prior distributions of parameters for FaIR based on the Coupled Model Intercomparison Project (CMIP6) Earth system models or Intergovernmental Panel on Climate Change (IPCC)-assessed ranges; second, to generate a large Monte Carlo prior ensemble of parameters to run FaIR with; and, third, to produce a posterior set of parameters constrained on several observable and assessed climate metrics. Different calibrations can be produced for different emission datasets or observed climate constraints, allowing version-controlled and continually updated calibrations to be produced. We show that two very different future projections to a given emission scenario can be obtained using emissions from the IPCC Sixth Assessment Report (AR6) (fair-calibrate v1.4.0) and from updated emission datasets through 2022 (fair-calibrate v1.4.1) for similar climate constraints in both cases. fair-calibrate can be reconfigured for different source emission datasets or target climate distributions, and new versions will be produced upon availability of new climate system data.

Recent analyses show the importance of methane shortwave absorption, which many climate models lack. In particular, Allen et al. (2023) used idealized climate model simulations to show that methane shortwave absorption mutes up to 30 % of the surface warming and 60 % of the precipitation increase associated with its longwave radiative effects. Here, we explicitly quantify the radiative and climate impacts due to shortwave absorption of the present-day methane perturbation. Our results corroborate the hypothesis that present-day methane shortwave absorption mutes the warming effects of longwave absorption. For example, the global mean cooling in response to the present-day methane shortwave absorption is -0.10 +/- 0.07 K, which offsets 28 % (7 %-55 %) of the surface warming associated with present-day methane longwave radiative effects. The precipitation increase associated with the longwave radiative effects of the present-day methane perturbation (0.012 +/- 0.006 mm d-1) is also muted by shortwave absorption but not significantly so (-0.008 +/- 0.009 mm d-1). The unique responses to methane shortwave absorption are related to its negative top-of-the-atmosphere effective radiative forcing but positive atmospheric heating and in part to methane's distinctive vertical atmospheric solar heating profile. We also find that the present-day methane shortwave radiative effects, relative to its longwave radiative effects, are about 5 times larger than those under idealized carbon dioxide perturbations. Additional analyses show consistent but non-significant differences between the longwave versus shortwave radiative effects for both methane and carbon dioxide, including a stronger (negative) climate feedback when shortwave radiative effects are included (particularly for methane). We conclude by reiterating that methane remains a potent greenhouse gas.

In every Intergovernmental Panel on Climate Change (IPCC) Assessment cycle, a multitude of scenarios are assessed, with different scope and emphasis throughout the various Working Group reports and special reports, as well as their respective chapters. Within the reports, the ambition is to integrate knowledge on possible climate futures across the Working Groups and scientific research domains based on a small set of “framing pathways” such as the so-called representative concentration pathways (RCPs) in the Fifth IPCC Assessment Report (AR5) and the shared socioeconomic pathway (SSP) scenarios in the Sixth Assessment Report (AR6). This perspective, initiated by discussions at the IPCC Bangkok workshop in April 2023 on the “Use of Scenarios in AR6 and Subsequent Assessments”, is intended to serve as one of the community contributions to highlight the needs for the next generation of framing pathways that is being advanced under the Coupled Model Intercomparison Project (CMIP) umbrella, which will influence or even predicate the IPCC AR7 consideration of framing pathways. Here we suggest several policy research objectives that such a set of framing pathways should ideally fulfil, including mitigation needs for meeting the Paris Agreement objectives, the risks associated with carbon removal strategies, the consequences of delay in enacting that mitigation, guidance for adaptation needs, loss and damage, and for achieving mitigation in the wider context of societal development goals. Based on this context, we suggest that the next generation of climate scenarios for Earth system models should evolve towards representative emission pathways (REPs) and suggest key categories for such pathways. These framing pathways should address the most critical mitigation policy and adaptation plans that need to be implemented over the next 10 years. In our view, the most important categories are those relevant in the context of the Paris Agreement long-term goal, specifically an immediate action (low overshoot) 1.5 °C pathway and a delayed action (high overshoot) 1.5 °C pathway. Two other key categories are a pathway category approximately in line with current (as expressed by 2023) near- and long-term policy objectives, as well as a higher-emission category that is approximately in line with “current policies” (as expressed by 2023). We also argue for the scientific and policy relevance in exploring two “worlds that could have been”. One of these categories has high-emission trajectories well above what is implied by current policies and the other has very-low-emission trajectories which assume that global mitigation action in line with limiting warming to 1.5 °C without overshoot had begun in 2015. Finally, we note that the timely provision of new scientific information on pathways is critical to inform the development and implementation of climate policy. Under the Paris Agreement, for the second global stocktake, which will occur in 2028, and to inform subsequent development of nationally determined contributions (NDCs) up to 2040, scientific inputs are required by 2027. These needs should be carefully considered in the development timeline of community modelling activities, including those under CMIP7.

Global emission reduction efforts continue to be insufficient to meet the temperature goal of the Paris Agreement1. This makes the systematic exploration of so-called overshoot pathways that temporarily exceed a targeted global warming limit before drawing temperatures back down to safer levels a priority for science and policy2-5. Here we show that global and regional climate change and associated risks after an overshoot are different from a world that avoids it. We find that achieving declining global temperatures can limit long-term climate risks compared with a mere stabilization of global warming, including for sea-level rise and cryosphere changes. However, the possibility that global warming could be reversed many decades into the future might be of limited relevance for adaptation planning today. Temperature reversal could be undercut by strong Earth-system feedbacks resulting in high near-term and continuous long-term warming6,7. To hedge and protect against high-risk outcomes, we identify the geophysical need for a preventive carbon dioxide removal capacity of several hundred gigatonnes. Yet, technical, economic and sustainability considerations may limit the realization of carbon dioxide removal deployment at such scales8,9. Therefore, we cannot be confident that temperature decline after overshoot is achievable within the timescales expected today. Only rapid near-term emission reductions are effective in reducing climate risks.

AbstractSince the 5th Assessment Report of the Intergovernmental Panel on Climate Change (AR5) an extended concept of the energetic analysis of climate change including forcings, feedbacks and adjustment processes has become widely adopted. Adjustments are defined as processes that occur in response to the introduction of a climate forcing agent, but that are independent of global‐mean surface temperature changes. Most considered are the adjustments that impact the Earth energy budget and strengthen or weaken the instantaneous radiative forcing due to the forcing agent. Some adjustment mechanisms also impact other aspects of climate not related to the Earth radiation budget. Since AR5 and a following description by Sherwood et al. (2015, https://doi.org/10.1175/bams‐d‐13‐00167.1), much research on adjustments has been performed and is reviewed here. We classify the adjustment mechanisms into six main categories, and discuss methods of quantifying these adjustments in terms of their potentials, shortcomings and practicality. We furthermore describe aspects of adjustments that act beyond the energetic framework, and we propose new ideas to observe adjustments or to make use of observations to constrain their representation in models. Altogether, the problem of adjustments is now on a robust scientific footing, and better quantification and observational constraint is possible. This allows for improvements in understanding and quantifying climate change.