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Anthropogenic activity is changing Earth's climate and ecosystems in ways that are potentially dangerous and disruptive to humans. Greenhouse gas concentrations in the atmosphere continue to rise, ensuring that these changes will be felt for centuries beyond 2100, the current benchmark for projection. Estimating the effects of past, current, and potential future emissions to only 2100 is therefore short-sighted. Critical problems for food production and climate-forced human migration are projected to arise well before 2100, raising questions regarding the habitability of some regions of the Earth after the turn of the century. To highlight the need for more distant horizon scanning, we model climate change to 2500 under a suite of emission scenarios and quantify associated projections of crop viability and heat stress. Together, our projections show global climate impacts increase significantly after 2100 without rapid mitigation. As a result, we argue that projections of climate and its effects on human well-being and associated governance and policy must be framed beyond 2100., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC), including the first global stocktake under the Paris Agreement that will conclude at COP28 in December 2023. Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, surface temperature changes, the Earth's energy imbalance, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open data, open science approach, is to make annually updated reliable global climate indicators available in the public domain (10.5281/zenodo.8000192, Smith et al., 2023a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that human-induced warming reached 1.14 [0.9 to 1.4] ∘ C averaged over the 2013–2022 decade and 1.26 [1.0 to 1.6] ∘ C in 2022. Over the 2013–2022 period, human-induced warming has been increasing at an unprecedented rate of over 0.2 ∘ C per decade. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 54 ± 5.3 GtCO 2 e over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that increases in greenhouse gas emissions have slowed, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for human influence on climate. [ABSTRACT FROM AUTHOR]

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC), including 60 the first global stocktake under the Paris Agreement that will conclude at COP28 in December 2023. Evidence-based decision making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5-10 years, creating potential for an information gap between report cycles. We base this update on the assessment methods used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report, updating the monitoring datasets and to produce updated estimates for key climate indicators including emissions, greenhouse gas concentrations, radiative forcing, surface temperature changes, the Earth's energy imbalance, warming attributed to human activities, the remaining carbon budget and estimates of global temperature extremes. The purpose of this effort, grounded in an open data, open science approach, is to make annually updated reliable global climate indicators 70 available in the public domain (https://doi.org/10.5281/zenodo.7883758, Smith et al., 2023). As they are traceable and consistent with IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that human induced warming reached 1.14 [0.9 to 1.4] °C over the 2013-2022 period and 1.26 [1.0 to 1.6] C in 2022. Human induced warming is increasing at an unprecedented rate of over 0.2 °C per decade. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 57 ± 5.6 GtCO2e over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there are signs that emission levels are starting to stabilise, and we can hope that a continued series of these annual updates might track a real-world change of direction for the climate over this critical decade. [ABSTRACT FROM AUTHOR]

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 diversity in climate model experiments persists as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article synthesizes current challenges and emphasizes opportunities for advancing our understanding of climate change and model diversity. The perspective of this article is based on expert views from three multi-model intercomparison projects (MIPs) - the Precipitation Driver Response MIP (PDRMIP), the Aerosol and Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specialisms 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. It specifically facilitated contributions to the research field through sharing knowledge on best practices for the design of model diagnostics and experimental strategies across MIP boundaries, e.g., for estimating effective radiative forcing. We discuss the challenges of gaining insights from highly complex models that have specific biases 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 for faster and better sub-grid scale parameterizations where they are needed. Both would improve our ability to adopt a smart experimental design with an optimal tradeoff between resolution, complexity and simulation length. Future experiments can be evaluated and improved with sophisticated methods that leverage multiple observational datasets, and thereby, help to advance the understanding of climate change and its impacts. [ABSTRACT FROM AUTHOR]

Although the Coupled Model Intercomparison Project 6 (CMIP6) protocol provides an experiment to estimate effective radiative forcing (ERF), it is only quantified for few models. We present new estimates of ERF for models participating in CMIP6 by applying the method developed in Fredriksen et al. (2021, https://doi.org/10.1029/2020JD034145), and validate our approach with available fixed‐SST forcing estimates. We estimate ERF for experiments with abrupt changes of CO2, 1% increase of CO2, historical forcings, and future scenarios, and demonstrate that CMIP6 ERF is lower than CMIP5 ERF at the end of the historical period, but grows faster than CMIP5 in the future scenarios, ending up at higher levels than CMIP5 at the end of the 21st century. The simulated radiative efficiency of CO2 has not changed much, suggesting that the larger future increase in CO2 concentrations in CMIP6 compared to CMIP5 is important for explaining the forcing difference. Plain Language Summary: To understand climate model responses, it is useful to separate between the drivers of climate change and their responses. We present new estimates of the drivers, called the effective radiative forcing, for the latest generation of climate models (Coupled Model Intercomparison Project 6 (CMIP6)). This estimates the energy imbalance at the top of the atmosphere and is a measure of human and natural influences on climate. Normally this requires additional climate model experiments to make these estimates, but since these have only been run for a few models, we are here aiming to make the best alternative estimates based on more widely available data, following the method in Fredriksen et al. (2021, https://doi.org/10.1029/2020JD034145). We show that our forcing estimates are growing faster during the 21st century for the new CMIP6 models than for the previous generation of models (CMIP5), and suggest this can be attributed to the higher CO2 concentrations in future scenarios for CMIP6 compared to CMIP5. Key Points: Our method to estimate effective radiative forcing based on common model diagnostics is consistent with Coupled Model Intercomparison Project 6 (CMIP6) fixed‐SST estimatesWe present coherent estimates for abrupt CO2, 1% CO2, historical, and future scenario experimentsForcing estimates for the 21st century grow faster for CMIP6 than for CMIP5 models [ABSTRACT FROM AUTHOR]

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, including those from Shell, BP, and the International Energy Agency. We compare a selection of these scenarios analysed 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. Of the scenarios assessed, we find that only the IEA Net Zero 2050 scenario is aligned with the criteria for Paris Agreement consistency employed here. We investigate root causes for misalignment with these criteria based on the underlying energy system transformation. Here the authors present a framework to assess the temperature outcomes of decarbonization scenarios from institutions such as the IEA, BP and Shell. Scenarios are evaluated for consistency with the long-term temperature goal of the Paris Agreement. [ABSTRACT FROM AUTHOR]

This study assesses the effective climate sensitivity (EffCS) and transient climate response (TCR) derived from global energy budget constraints within historical simulations of eight CMIP6 global climate models (GCMs). These calculations are enabled by use of the Radiative Forcing Model Intercomparison Project (RFMIP) simulations, which permit accurate quantification of the radiative forcing. Long‐term historical energy budget constraints generally underestimate EffCS from CO2 quadrupling and TCR from CO2 ramping, owing to changes in radiative feedbacks and changes in ocean heat uptake efficiency. Atmospheric GCMs forced by observed warming patterns produce lower values of EffCS that are more in line with those inferred from observed historical energy budget changes. The differences in the EffCS estimates from historical energy budget constraints of models and observations are traced to discrepancies between modeled and observed historical surface warming patterns. Plain Language Summary: Here we use climate models and observations to evaluate the extent to which future warming can be inferred from historical climate change. We assess the historical energy budget in 8 climate models by leveraging a recent community effort to quantify radiative forcing within their historical simulations. We find the historical energy budget tends to provide a biased‐low constraint on future warming, represented by two metrics: effective climate sensitivity and transient climate response. Moreover, observations and simulations run with observed surface warming patterns produce even lower values of climate sensitivity. This difference in climate sensitivity estimates can be traced to discrepancies between modeled and observed surface warming patterns. Key Points: Estimates from historical energy budget constraints underestimate equilibrium climate sensitivity and transient climate response in modelsAtmosphere‐only models forced by observed surface warming patterns produce lower estimates of ECS, in line with historical observationsDiscrepancies between modeled and observed historical surface warming patterns account for the differences in climate sensitivity estimates [ABSTRACT FROM AUTHOR]

The Suite of Community Radiative Transfer Codes Based on Edwards and Slingo (SOCRATES) offline radiative transfer code is used to investigate the magnitude and structure of the instantaneous radiative forcing kernels (IRFKs) for five major greenhouse gases (GHGs; CO2, CH4, N2O, CFC-11, and O3). All gases produce IRFKs that peak in the tropical upper troposphere. In addition to differences in spectroscopic intensities and the position of absorption features relative to the peak of the Planck function for Earth’s temperature, the variation in current background concentration of gases substantially affects the IRFK magnitudes. When the background concentration of CO2 is reduced from parts per million to parts per trillion levels, the peak magnitude of the IRFK increases by a factor of 642. When all gases are set to parts per trillion concentrations in the troposphere, the peak IRFK magnitudes are 1.0, 3.0, 3.1, 58, and 75Wm-2 ppmv-1 (100 hPa)-1 for CH4, CO2, N2O, O3, and CFC-11, respectively. The altitude of the IRFK maximum also differs, with the maximum for CFC-11 and water vapor occurring above 100 hPa whereas the other gases peak near 150–200 hPa. Overlap with water vapor absorption decreases the magnitude of the IRFKs for all of the GHGs, particularly in the lower-to-middle troposphere, but it does not strongly affect the peak IRFK altitude. Cloud radiative effects reduce the magnitude of the IRFK for CO2 by around 10%–20% in the upper troposphere. The use of IRFKs to estimate instantaneous radiative forcing is found to be accurate for small-amplitude perturbations but becomes inaccurate for large-amplitude changes (e.g., a doubling) for gases with a higher atmospheric optical depth. [ABSTRACT FROM AUTHOR]

Rapid adjustments occur after initial perturbation of an external climate driver (e.g., CO2) and involve changes in, e.g. atmospheric temperature, water vapour and clouds, independent of sea surface temperature changes. Knowledge of such adjustments is necessary to estimate effective radiative forcing (ERF), a useful indicator of surface temperature change, and to understand global precipitation changes due to different drivers. Yet, rapid adjustments have not previously been analysed in any detail for certain compounds, including halocarbons and N2O. Here we use several global climate models combined with radiative kernel calculations to show that individual rapid adjustment terms due to CFC-11, CFC-12 and N2O are substantial, but that the resulting flux changes approximately cancel at the top-of-atmosphere due to compensating effects. Our results further indicate that radiative forcing (which includes stratospheric temperature adjustment) is a reasonable approximation for ERF. These CFCs lead to a larger increase in precipitation per kelvin surface temperature change (2.2 ± 0.3% K−1) compared to other well-mixed greenhouse gases (1.4 ± 0.3% K−1 for CO2). This is largely due to rapid upper tropospheric warming and cloud adjustments, which lead to enhanced atmospheric radiative cooling (and hence a precipitation increase) and partly compensate increased atmospheric radiative heating (i.e. which is associated with a precipitation decrease) from the instantaneous perturbation. [ABSTRACT FROM AUTHOR]

The Arctic is experiencing rapid climate change in response to changes in greenhouse gases, aerosols, and other climate drivers. Emission changes in general, as well as geographical shifts in emissions and transport pathways of short‐lived climate forcers, make it necessary to understand the influence of each climate driver on the Arctic. In the Precipitation Driver Response Model Intercomparison Project, 10 global climate models perturbed five different climate drivers separately (CO2, CH4, the solar constant, black carbon, and SO4). We show that the annual mean Arctic amplification (defined as the ratio between Arctic and the global mean temperature change) at the surface is similar between climate drivers, ranging from 1.9 (± an intermodel standard deviation of 0.4) for the solar to 2.3 (±0.6) for the SO4 perturbations, with minimum amplification in the summer for all drivers. The vertical and seasonal temperature response patterns indicate that the Arctic is warmed through similar mechanisms for all climate drivers except black carbon. For all drivers, the precipitation change per degree global temperature change is positive in the Arctic, with a seasonality following that of the Arctic amplification. We find indications that SO4 perturbations produce a slightly stronger precipitation response than the other drivers, particularly compared to CO2. Key Points: Arctic amplification of surface warming is similar between global drivers of climate changeBlack carbon induces differing vertical and seasonal amplification patternsSulfate affects Arctic precipitation responses more strongly than other drivers, particularly in the summer season [ABSTRACT FROM AUTHOR]

In recent years, the idea of geoengineering, artificially modifying the climate to reduce global temperatures, has received increasing attention because of the lack of progress in reducing global greenhouse gas emissions. Stratospheric sulfate injection (SSI) is a geoengineering method proposed to reduce planetary warming by reflecting a proportion of solar radiation back into space that would otherwise warm the surface and lower atmosphere. The authors analyze results from the Met Office Hadley Centre Global Environment Model, version 2, Carbon Cycle Stratosphere (HadGEM2-CCS) climate model with stratospheric emissions of 10 Tg yr−1 of SO2, designed to offset global temperature rise by around 1°C. A reduction in concentrating solar power output of 5.9% on average over land is shown under SSI relative to a baseline future climate change scenario (RCP4.5) caused by a decrease in direct radiation. Solar photovoltaic energy is generally less affected as it can use diffuse radiation, which increases under SSI, at the expense of direct radiation. The results from HadGEM2-CCS are compared with the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) from the Geoengineering Model Intercomparison Project (GeoMIP), with 5 Tg yr−1 emission of SO2. In many regions, the differences predicted in solar energy output between the SSI and RCP4.5 simulations are robust, as the sign of the changes for both HadGEM2-CCS and GEOSCCM agree. Furthermore, the sign of the total and direct annual mean radiation changes evaluated by HadGEM2-CCS agrees with the sign of the multimodel mean changes of an ensemble of GeoMIP models over the majority of the world. [ABSTRACT FROM AUTHOR]