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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., (© 2022. The Author(s).)

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.)

Developing future climate projections begins with choosing future emissions scenarios. While scenarios are often based on storylines, here instead we produce a probabilistic multi-million-member ensemble of radiative forcing trajectories to assess the relevance of future forcing thresholds. We coupled a probabilistic database of future greenhouse gas emission scenarios with a probabilistically calibrated reduced complexity climate model. In 2100, we project median forcings of 5.1 watt per square meters (5th to 95th percentiles of 3.3 to 7.1), with roughly 0.5% probability of exceeding 8.5 watt per square meters, and a 1% probability of being lower than 2.6 watt per square meters. Although the probability of 8.5 watt per square meters scenarios is low, our results support their continued utility for calibrating damage functions, characterizing climate in the 22nd century (the probability of exceeding 8.5 watt per square meters increases to about 7% by 2150), and assessing low-probability/high-impact futures. The probability of exceeding various climate thresholds has been calculated. While the warmest future scenario has less than a 1 percent chance of being exceeded this century, the paper discusses why such warm scenarios are still relevant. [ABSTRACT FROM AUTHOR]

The Radiative Forcing Model Intercomparison Project (RFMIP) allows estimates of effective radiative forcing (ERF) in the Coupled Model Intercomparison Project phase six (CMIP6). We analyze the RFMIP output, including the new experiments from models that use the same parameterization for anthropogenic aerosols (RFMIP‐SpAer), to characterize and better understand model differences in aerosol ERF. We find little changes in the aerosol ERF for 1970–2014 in the CMIP6 multi‐model mean, which implies greenhouse gases primarily explain the positive trend in the total anthropogenic ERF. Cloud‐mediated effects dominate the present‐day aerosol ERF in most models. The results highlight a regional increase in marine cloudiness due to aerosols, despite suppressed cloud lifetime effects in that RFMIP‐SpAer experiment. Negative cloud‐mediated effects mask positive direct effects in many models, which arise from strong anthropogenic aerosol absorption. The findings suggest opportunities to better constrain simulated ERF by revisiting the optical properties and long‐range transport of aerosols. Plain Language Summary: Aerosols are particles in the atmosphere with sizes ranging from nanometers to tens of micrometers, which are emitted by natural and anthropogenic processes or formed from gases in the atmosphere. The extent to which anthropogenic aerosols affect the radiation budget of Earth is important to better understand anthropogenic climate changes. Aerosol effects on the radiation budget are simulated by complex Earth system models that informed the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Our study addresses why such model experiments show different magnitudes for aerosol radiative effects. The results point to opportunities to further improve models with existing observations of aerosol optical properties and aerosol transport over oceans in addition to the much‐studied aerosol effects on clouds. Key Points: Coupled Model Intercomparison Project phase six (CMIP6) averaged trend in aerosol effective radiative forcing (ERF) is small for 1970–2014 and weakly positive for 2000–2014Positive direct aerosol radiative effects in CMIP6 models are associated with strong aerosol absorptionDiverse and often strong cloud‐mediated effects primarily determine the magnitude of aerosol ERF in CMIP6 [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]

For the 1960–2000 period, the latest generation of climate models (Coupled Model Intercomparison Project Phase 6 [CMIP6]) shows less global mean surface temperature change relative to pre‐industrial than that seen in observations. In contrast, the previous generation of models (CMIP5) performed well over this period. It has been hypothesized that this suppressed late‐20th Century warming seen in CMIP6 is caused by a stronger aerosol forcing. However, we find this to be only part of the story. Not only is the aerosol forcing marginally more negative in CMIP6 compared to CMIP5, the greenhouse gas forcing in CMIP6 is also weaker than in CMIP5. These forcing differences are amplified by differences in climate sensitivity between the CMIP5 and CMIP6 ensemble, which leads to both a stronger aerosol cooling over 1960–1990 and a stronger greenhouse gas induced warming from 1990, returning the warming post‐2000 toward the observed level. Plain Language Summary: Climate models are our best tools for predicting how the climate will change in the future. Confidence in future projections relies on the ability to accurately simulate the past. Many of the latest climate models show less warming than observations around the 1960–2000 period, so understanding why is key to making more confident projections. Models respond to human and natural forcings such as greenhouse gases, air pollutants (aerosols), volcanic eruptions, and solar activity. We show that the latest models simulate a lower forcing from greenhouse gases and aerosols than older models, which is part of the reason why the climate does not warm in line with observations in the late 20th Century. The other part of the reason for the lower warming is that the newer models are more sensitive: they project a greater temperature change for a given amount of forcing. The higher sensitivity is found to result in more cooling from aerosols in the new models, but it opposes the lower forcing from greenhouse gases. The aerosol effects win out, causing suppressed warming in the late 20th Century. Key Points: Coupled Model Intercomparison Project Phase 6 (CMIP6) models warm less in the multimodel mean than CMIP5 models in the 1960–2000 periodImplied forcing from greenhouse gases and aerosols is lower (more negative) in CMIP6 than in CMIP5Stronger climate feedbacks in CMIP6 amplifies the cooling from aerosols [ABSTRACT FROM AUTHOR]

Here we present an update to the FaIR model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis, and education. In this update we have focussed on identifying a minimum level of structural complexity in the model. The result is a set of six equations, five of which correspond to the standard impulse response model used for greenhouse gas (GHG) metric calculations in the IPCC's Fifth Assessment Report, plus one additional physically motivated equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. This additional equation is necessary to reproduce non-linearities in the carbon cycle apparent in both Earth system models and observations. These six equations are transparent and sufficiently simple that the model is able to be ported into standard tabular data analysis packages, such as Excel, increasing the potential user base considerably. However, we demonstrate that the equations are flexible enough to be tuned to emulate the behaviour of several key processes within more complex models from CMIP6. The model is exceptionally quick to run, making it ideal for integrating large probabilistic ensembles. We apply a constraint based on the current estimates of the global warming trend to a million-member ensemble, using the constrained ensemble to make scenario-dependent projections and infer ranges for properties of the climate system. Through these analyses, we reaffirm that simple climate models (unlike more complex models) are not themselves intrinsically biased "hot" or "cold": it is the choice of parameters and how those are selected that determines the model response, something that appears to have been misunderstood in the past. This updated FaIR model is able to reproduce the global climate system response to GHG and aerosol emissions with sufficient accuracy to be useful in a wide range of applications and therefore could be used as a lowest-common-denominator model to provide consistency in different contexts. The fact that FaIR can be written down in just six equations greatly aids transparency in such contexts. [ABSTRACT FROM AUTHOR]

Changes in atmospheric composition, such as increasing greenhouse gases, cause an initial radiative imbalance to the climate system, quantified as the instantaneous radiative forcing. This fundamental metric has not been directly observed globally and previous estimates have come from models. In part, this is because current space‐based instruments cannot distinguish the instantaneous radiative forcing from the climate's radiative response. We apply radiative kernels to satellite observations to disentangle these components and find all‐sky instantaneous radiative forcing has increased 0.53 ± 0.11 W/m2 from 2003 to 2018, accounting for positive trends in the total planetary radiative imbalance. This increase has been due to a combination of rising concentrations of well‐mixed greenhouse gases and recent reductions in aerosol emissions. These results highlight distinct fingerprints of anthropogenic activity in Earth's changing energy budget, which we find observations can detect within 4 years. Plain Language Summary: Climate change is a response to energy imbalances in the climate system. For example, rising greenhouse gases directly cause an initial imbalance, the radiative forcing, in the planetary radiation budget, and surface temperatures increase in response as the climate attempts to restore balance. The radiative forcing and subsequent radiative feedbacks dictate the amount of warming. While there are well‐established observational records of greenhouse gas concentrations and surface temperatures, there is not yet a global measure of the radiative forcing, in part because current satellite observations of Earth's radiation only measure the sum total of radiation changes that occur. We use the radiative kernel technique to isolate radiative forcing from total radiative changes and find it has increased from 2003 to 2018, accounting for nearly all of the long‐term growth in the total top‐of‐atmosphere radiation imbalance during this period. We confirm that rising greenhouse gas concentrations account for most of the increases in the radiative forcing, along with reductions in reflective aerosols. This serves as direct evidence that anthropogenic activity has affected Earth's energy budget in the recent past. Key Points: Observed instantaneous radiative forcing has increased, strengthening the top‐of‐atmosphere radiative imbalanceDue to cancellations in longwave and shortwave radiation, the sum of rapid adjustments and radiative feedbacks exhibit an insignificant trendObserved increases in instantaneous radiative forcing are direct evidence of the anthropogenic effects on the Earth's radiative energy budget [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]

Here we present an update to the FaIR model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis and education. In this update we have focussed on identifying a minimum level of structural complexity in the model. The result is a set of six equations, five of which correspond to the standard Impulse Response model used for greenhouse gas (GHG) metric calculations in the IPCC's fifth assessment report, plus one additional physically-motivated additional equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. This additional equation is necessary to reproduce non-linearities in the carbon cycle apparent in both Earth System Models and observations. These six equations are transparent and sufficiently simple that the model is able to be written in standard tabular data analysis packages, such as Excel; increasing the potential user base considerably. However, we demonstrate that the equations are flexible enough to be tuned to emulate the behaviour of several key processes within more complex models from CMIP6. The model is exceptionally quick to run, making it ideal for integrating large probabilistic ensembles. We apply a constraint based on the current estimates of the global warming trend to a one million member ensemble, using the constrained ensemble to make scenario dependent projections and infer ranges for properties of the climate system. Through these analyses, we reaffirm that simple climate models (unlike more complex models) are not themselves intrinsically biased hot or cold: it is the choice of parameters and how those are selected that determines the model response, something that appears to have been misunderstood in the past. This updated FaIR model is able to reproduce the global climate system response to GHG and aerosol emissions with sufficient accuracy to be useful in a wide range of applications; and therefore could be used as a lowest common denominator model to provide consistency in different contexts. The fact that FaIR can be written down in just six equations greatly aids transparency in such contexts. [ABSTRACT FROM AUTHOR]

The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m -2 , comprised of 1.81 (±0.09) W m -2 from CO2 , 1.08 (± 0.21) W m -2 from other well-mixed greenhouse gases, -1.01 (± 0.23) W m -2 from aerosols and -0.09 (±0.13) W m -2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m -2. The majority of the remaining 0.21 W m -2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from -0.63 to -1.37 W m -2 , exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming. [ABSTRACT FROM AUTHOR]

The relative importance of anthropogenic aerosol in decadal variations of historical climate is uncertain, largely due to uncertainty in aerosol radiative forcing. We analyze a novel large ensemble of simulations with HadGEM3‐GC3.1 for 1850–2014, where anthropogenic aerosol and precursor emissions are scaled to sample a wide range of historical aerosol radiative forcing with present‐day values ranging from –0.38 to –1.50 Wm–2. Five ensemble members are run for each of five aerosol scaling factors. Decadal variations in surface temperatures are strongly sensitive to aerosol forcing, particularly between 1950 and 1980. Post‐1980, trends are dominated by greenhouse gas forcing, with much lower sensitivity to aerosol emission differences. Most realizations with aerosol forcing more negative than about –1 Wm–2 simulate stronger cooling trends in the mid‐20th century compared with observations, while the simulated warming post‐1980 always exceeds observed warming, likelydue to a warm bias in the transient climate response in HadGEM3‐GC3.1. Plain Language Summary: Anthropogenic aerosols have an overall cooling effect on climate due to their interaction with incoming solar radiation and influence on cloud properties. Their emissions have offset some of the historical warming induced by increasing greenhouse gases. However, the magnitude of the cooling induced by anthropogenic aerosol remains poorly constrained. In this study, we use a state‐of‐the‐art climate model, HadGEM3‐GC3.1, driven by different levels of aerosol emissions. This experimental setup tests the sensitivity of simulated historical temperatures to the strength of aerosol forcing in a climate model, all other factors remaining equal. Our results show that the period from 1951 to 1980 is particularly sensitive to aerosol forcing, coinciding with a period of rapid increases in global aerosol emissions and observed cooling over many regions, while temperature trends from 1980 onwards are primarily driven by increases in greenhouse gas concentrations. The observed temperatures over 1951–1980 are best reproduced by simulations with lower aerosol emissions than the standard configuration, implying that this model responds too strongly to aerosol forcing. Concurrently, the simulated temperatures warm faster than observed temperatures from 1980 onwards, suggesting that this climate model also responds more strongly to greenhouse gas forcing than observations suggest. Key Points: Simulations sampling aerosol forcing uncertainty suggest that aerosol forcing in the HadGEM3‐GC3.1 CMIP6 historical simulations is too largeComparing two key periods (1950–1980 and 1981–2010) with observations suggests a positive bias in the transient climate response in HadGEM3Most realizations with aerosol forcing more negative than about –1 Wm–2 cool too much in the mid‐20th century [ABSTRACT FROM AUTHOR]

We present top-of-atmosphere and surface radiative kernels based on the atmospheric component (GA7.1) of the HadGEM3 general circulation model developed by the UK Met Office. We show that the utility of radiative kernels for forcing adjustments in idealised CO2 perturbation experiments is most appropriate where there is sufficiently high resolution in the stratosphere in both the target climate model and the radiative kernel. This is because stratospheric cooling to a CO2 perturbation continues to increase with height, and low-resolution or low-top kernels or climate model output are unable to fully resolve the full stratospheric temperature adjustment. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), standard atmospheric model data is available up to 1hPa on 19 pressure levels, which is a substantial advantage compared to CMIP5. We show in the IPSL-CM6A-LR model where a full set of climate diagnostics are available that the HadGEM3-GA7.1 kernel exhibits linear behaviour and the residual error term is small. From kernels available in the literature we recommend three kernels for adjustment calculations to CO2 and well-mixed greenhouse gas perturbations based on their stratospheric resolution: HadGEM3-GA7.1, ECMWF-Oslo, and ECHAM6. The HadGEM3-GA7.1 radiative kernels are available at https://doi.org/10.5281/zenodo.3594673 (Smith, 2019). [ABSTRACT FROM AUTHOR]

Here we present a Generalised Impulse Response (GIR) model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis and teaching. This model is based on a set of only six equations, which correspond to the standard Impulse Response model used for greenhouse gas metric calculations by the IPCC, plus one physically-motivated additional equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. These six equations are simple and transparent enough to be easily understood and implemented in other models without reliance on the original source code, but flexible enough to reproduce observed well-mixed greenhouse gas (GHG) concentrations and atmospheric lifetimes, best-estimate effective radiative forcing, and temperature response. We describe the assumptions and methods used in selecting the default parameters, but emphasize that other methods would be equally valid: our focus here is on identifying a minimum level of structural complexity. The tunable nature of the model lends it to use as a fully transparent emulator of complex Earth System Models, such as those participating in CMIP6, while also reproducing the behaviour of other simple climate models. We argue that this GIR model is adequate to reproduce the global temperature response to global emissions and effective radiative forcing, and that it should be used as a lowest-common denominator to provide consistency and continuity between different climate assessments. The model design is such that it can be written in tabular data analysis software, such as Excel, increasing the potential user base considerably. [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]

Simple climate models can be valuable if they are able to replicate aspects of complex fully coupled earth system models. Larger ensembles can be produced, enabling a probabilistic view of future climate change. A simple emissions-based climate model, FAIR, is presented which calculates atmospheric concentrations of greenhouse gases and effective radiative forcing (ERF) from greenhouse gases, aerosols, ozone precursors and other agents. The ERFs are integrated into global mean surface temperature change. Model runs are constrained to observed temperature change from 1880 to 2016 and produce a range of future projections under the Representative Concentration Pathway (RCP) scenarios. For the historical period the ERF time series in FAIR emulates the results in the IPCC Fifth Assessment Report (AR5), whereas for RCP historical and future scenarios, the greenhouse gas concentrations in FAIR closely track the observations and projections in the RCPs. The constrained estimates of equilibrium climate sensitivity (ECS) of 2.79 (1.97 to 4.08) K, transient climate response (TCR) of 1.47 (1.03 to 2.23) K and transient climate response to cumulative CO2 emissions (TCRE) of 1.43 (1.01 to 2.16) K (1000 GtC)-1 (median and 5-95 % credible intervals) are in good agreement, with tighter uncertainty bounds, than AR5 (1.5 to 4.5 K, 1.0 to 2.5 K, and 0.8 to 2.5 K respectively). The ranges of future projections of temperature and ranges of estimates of ECS, TCR and TCRE are moderately sensitive to the historical temperature dataset used to constrain, prior distributions of ECS/TCR parameters, aerosol radiative forcing relationship and ERF from a doubling of CO2. Taking these sensitivities into account, there is no evidence to suggest that the median and credible range of observationally constrained TCR or ECS differ from climate model-derived estimates. However, the range of temperature projections under the RCP scenarios for 2081-2100 in the constrained FAIR model ensemble are lower than the emissions-based estimates reported in AR5. [ABSTRACT FROM AUTHOR]

• Analysis of final energy demand in the IPCC's 1.5 and 2 °C mitigation pathways. • Final energy demand reduces by 2100 in less than 5% of scenarios considered. • Lower energy pathways broadly reduce the share of renewables and energy investment. • Lower energy pathways do not necessarily reduce reliance on carbon dioxide removal. • There is more scope to use energy demand reductions to reduce technology reliance. Today's climate policies will shape the future trajectory of emissions. Consumption is the main driver behind recent increases in global greenhouse gas emissions, outpacing savings through improved technologies, and therefore its representation in the evidence base will impact on the success of policy interventions. The IPCC's Special Report on Global Warming of 1.5 °C (SR1.5) summarises global evidence on pathways for meeting below-2 °C targets, underpinned by a suite of scenarios from integrated assessment models (IAMs). We explore how final energy demand is framed within these, with the aim to making demand-related assumptions more transparent, and evaluating their significance, feasibility, and use or underutilisation as a mitigation lever. We investigate how the integrated assessment models compensate for higher and lower levels of final energy demand across scenarios, and how this varies when mitigating for 2 °C and 1.5 °C temperature targets through an analysis of (1) final energy demand projections, (2) energy-economy relationships and (3) differences between energy system decarbonisation and carbon dioxide removal in the highest and lowest energy demand pathways. We look across the full suite of mitigation pathways and assess the consequences of achieving different global carbon budgets. We find that energy demand in 2100 in the highest energy demand scenarios is approximately three to four times higher than the lowest demand pathways, but we do not find strong evidence that 1.5 °C-consistent pathways cluster on the lower end of demand levels, particularly when they allow for overshoot. The majority of demand reductions happen pre-2040, which assumes absolute decoupling from economic growth in the near-term; thereafter final energy demand levels generally grow to 2100. Lower energy demand pathways moderately result in lower renewable energy supply and lower energy system investment, but do not necessarily reduce reliance on carbon dioxide removal. In this sense, there is more scope for IAMs to implement energy demand reduction as a longer-term mitigation lever and to reduce reliance on negative emissions technologies. We demonstrate the need for integrated assessments to play closer attention to how final energy demand interacts with, relates to, and can potentially offset supply-side characteristics, alongside a more diverse evidence base. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]