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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). 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, the Earth's energy imbalance, surface temperature changes, 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 (https://doi.org/10.5281/zenodo.11388387, Smith et al., 2024a). 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, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO2e yr−1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.

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 over 6 months, the 2014–2015 effusive eruption at Holuhraun, Iceland, injected considerable amounts of sulfur dioxide (SO2) into the lower troposphere with a daily rate of up to one-third of the global emission rate, causing extensive air pollution across Europe. The large injection of SO2, which oxidises to form sulfate aerosol (SO42-), provides a natural experiment offering an ideal opportunity to scrutinise state-of-the-art general circulation models' (GCMs) representation of aerosol–cloud interactions (ACIs). Here we present Part 1 of a two-part model inter-comparison using the Holuhraun eruption as a framework to analyse ACIs. We use SO2 retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) instrument and ground-based measurements of SO2 and SO42- mass concentrations across Europe, in conjunction with a trajectory analysis using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, to assess the spatial and chemical evolution of the volcanic plume as simulated by five GCMs and a chemical transport model (CTM). IASI retrievals of plume altitude and SO2 column load reveal that the volcanic perturbation is largely contained within the lower troposphere. Compared to the satellite observations, the models capture the spatial evolution and vertical variability of the plume reasonably well, although the models often overestimate the plume altitude. HYSPLIT trajectories are used to attribute to Holuhraun emissions 111 instances of elevated sulfurous surface mass concentrations recorded at European Monitoring and Evaluation Programme (EMEP) stations during September and October 2014. Comparisons with the simulated concentrations show that the modelled ratio of SO2 to SO42- during these pollution episodes is often underestimated and overestimated for the young and mature plume, respectively. Models with finer vertical resolutions near the surface are found to better capture these elevated sulfurous ground-level concentrations. Using an exponential function to describe the decay of observed surface mass concentration ratios of SO2 to SO42- with plume age, the in-plume oxidation rate constant is estimated as 0.032 ± 0.002 h−1 (1.30 ± 0.08 d e-folding time), with a near-vent ratio of 25 ± 5 (µg m−3 of SO2 / µg m−3 of SO42-). The majority of the corresponding derived modelled oxidation rate constants are lower than the observed estimate. This suggests that the representation of the oxidation pathway/s in the simulated plumes is too slow. Overall, despite their coarse spatial resolutions, the six models show reasonable skill in capturing the spatial and chemical evolution of the Holuhraun plume. This capable representation of the underlying aerosol perturbation is essential to enable the investigation of the eruption's impact on ACIs in the second part of this study.

Anthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth–atmosphere system, alter the formation of clouds and precipitation, and have a substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO2 injection, seasonality of SO2 and black carbon (BC) particulate emissions, and the assumed fraction of SO2 emissions that is injected into the atmosphere as particulate phase sulfate (SO4) in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find large variation in atmospheric lifetime across models for SO2, SO4, and BC, with a particularly large relative variation for SO2, which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of −0.35 W m−2), SO2 lifetime over Northern Hemisphere land (maximum difference of 0.8 d), surface SO2 concentration (up to 59 % decrease), and surface sulfate concentration (up to 23 % increase). Emitting SO2 at height consistently increased SO2 and SO4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to ensure that anthropogenic emission injection height and SO4 emission fraction are accurately and consistently represented in global models.

This study focuses on implications of differences between recent global emissions inventories for simulated trends in anthropogenic aerosol abundances and radiative forcing (RF) over the 1990–2019 period. We use the ECLIPSE version 6 (ECLv6) and CEDS year 2021 release (CEDS21) as input to the chemical transport model OsloCTM3 and compare the resulting aerosol evolution to corresponding results derived with the first CEDS release, as well as to observed trends in regional and global aerosol optical depth (AOD). Using CEDS21 and ECLv6 results in a 3 % and 6 % lower global mean AOD compared to CEDS in 2014, primarily driven by differences over China and India, where the area average AOD is up to 30 % lower. These differences are considerably larger than the satellite-derived interannual variability in AOD. A negative linear trend over 2005–2017 in global AOD following changes in anthropogenic emissions is found with all three inventories but is markedly stronger with CEDS21 and ECLv6. Furthermore, we confirm that the model better captures the sign and strength of the observed AOD trend over China with CEDS21 and ECLv6 compared to using CEDS, while the opposite is the case for South Asia. We estimate a net global mean aerosol-induced RF in 2014 relative to 1990 of 0.08 W m−2 for CEDS21 and 0.12 W m−2 for ECLv6, compared to 0.03 W m−2 with CEDS. Using CEDS21, we also estimate the RF in 2019 relative to 1990 to be 0.10 W m−2, reflecting the continuing decreasing trend in aerosol loads post-2014. Our results facilitate more rigorous comparison between existing and upcoming studies of climate and health effects of aerosols using different emission inventories.

Anthropogenic aerosols exert a cooling influence that offsets part of the greenhouse gas warming. Due to their short tropospheric lifetime of only several days, the aerosol forcing responds quickly to emissions. Here, we present and discuss the evolution of the aerosol forcing since 2000. There are multiple lines of evidence that allow us to robustly conclude that the anthropogenic aerosol effective radiative forcing (ERF) – both aerosol–radiation interactions (ERFari) and aerosol–cloud interactions (ERFaci) – has become less negative globally, i.e. the trend in aerosol effective radiative forcing changed sign from negative to positive. Bottom-up inventories show that anthropogenic primary aerosol and aerosol precursor emissions declined in most regions of the world; observations related to aerosol burden show declining trends, in particular of the fine-mode particles that make up most of the anthropogenic aerosols; satellite retrievals of cloud droplet numbers show trends in regions with aerosol declines that are consistent with these in sign, as do observations of top-of-atmosphere radiation. Climate model results, including a revised set that is constrained by observations of the ocean heat content evolution show a consistent sign and magnitude for a positive forcing relative to the year 2000 due to reduced aerosol effects. This reduction leads to an acceleration of the forcing of climate change, i.e. an increase in forcing by 0.1 to 0.3 W m−2, up to 12 % of the total climate forcing in 2019 compared to 1750 according to the Intergovernmental Panel on Climate Change (IPCC).

Global models are widely used to simulate biomass burning aerosol (BBA). Exhaustive evaluations on model representation of aerosol distributions and properties are fundamental to assess health and climate impacts of BBA. Here we conducted a comprehensive comparison of Aerosol Comparisons between Observations and Models (AeroCom) project model simulations with satellite observations. A total of 59 runs by 18 models from three AeroCom Phase-III experiments (i.e., biomass burning emissions, CTRL16, and CTRL19) and 14 satellite products of aerosols were used in the study. Aerosol optical depth (AOD) at 550 nm was investigated during the fire season over three key fire regions reflecting different fire dynamics (i.e., deforestation-dominated Amazon, Southern Hemisphere Africa where savannas are the key source of emissions, and boreal forest burning in boreal North America). The 14 satellite products were first evaluated against AErosol RObotic NETwork (AERONET) observations, with large uncertainties found. But these uncertainties had small impacts on the model evaluation that was dominated by modeling bias. Through a comparison with Polarization and Directionality of the Earth’s Reflectances measurements with the Generalized Retrieval of Aerosol and Surface Properties algorithm (POLDER-GRASP), we found that the modeled AOD values were biased by −93 % to 152 %, with most models showing significant underestimations even for the state-of-the-art aerosol modeling techniques (i.e., CTRL19). By scaling up BBA emissions, the negative biases in modeled AOD were significantly mitigated, although it yielded only negligible improvements in the correlation between models and observations, and the spatial and temporal variations in AOD biases did not change much. For models in CTRL16 and CTRL19, the large diversity in modeled AOD was in almost equal measures caused by diversity in emissions, lifetime, and the mass extinction coefficient (MEC). We found that in the AeroCom ensemble, BBA lifetime correlated significantly with particle deposition (as expected) and in turn correlated strongly with precipitation. Additional analysis based on Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) aerosol profiles suggested that the altitude of the aerosol layer in the current models was generally too low, which also contributed to the bias in modeled lifetime. Modeled MECs exhibited significant correlations with the Ångström exponent (AE, an indicator of particle size). Comparisons with the POLDER-GRASP-observed AE suggested that the models tended to overestimate the AE (underestimated particle size), indicating a possible underestimation of MECs in models. The hygroscopic growth in most models generally agreed with observations and might not explain the overall underestimation of modeled AOD. Our results imply that current global models contain biases in important aerosol processes for BBA (e.g., emissions, removal, and optical properties) that remain to be addressed in future research.

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m2 g−1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

For the radiative impact of individual climate forcings, most previous studies focused on the global mean values at the top of the atmosphere (TOA), and less attention has been paid to surface processes, especially for black carbon (BC) aerosols. In this study, the surface radiative responses to five different forcing agents were analyzed by using idealized model simulations. Our analyses reveal that for greenhouse gases, solar irradiance, and scattering aerosols, the surface temperature changes are mainly dictated by the changes of surface radiative heating, but for BC, surface energy redistribution between different components plays a more crucial role. Globally, when a unit BC forcing is imposed at TOA, the net shortwave radiation at the surface decreases by -5.87±0.67 W m−2 (W m−2)−1 (averaged over global land without Antarctica), which is partially offset by increased downward longwave radiation (2.32±0.38 W m−2 (W m−2)−1 from the warmer atmosphere, causing a net decrease in the incoming downward surface radiation of -3.56±0.60 W m−2 (W m−2)−1. Despite a reduction in the downward radiation energy, the surface air temperature still increases by 0.25±0.08 K because of less efficient energy dissipation, manifested by reduced surface sensible (-2.88±0.43 W m−2 (W m−2)−1) and latent heat flux (-1.54±0.27 W m−2 (W m−2)−1), as well as a decrease in Bowen ratio (-0.20±0.07 (W m−2)−1). Such reductions of turbulent fluxes can be largely explained by enhanced air stability (0.07±0.02 K (W m−2)−1), measured as the difference of the potential temperature between 925 hPa and surface, and reduced surface wind speed (-0.05±0.01 m s−1 (W m−2)−1). The enhanced stability is due to the faster atmospheric warming relative to the surface, whereas the reduced wind speed can be partially explained by enhanced stability and reduced Equator-to-pole atmospheric temperature gradient. These rapid adjustments under BC forcing occur in the lower atmosphere and propagate downward to influence the surface energy redistribution and thus surface temperature response, which is not observed under greenhouse gases or scattering aerosols. Our study provides new insights into the impact of absorbing aerosols on surface energy balance and surface temperature response.

Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes. Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1. Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc. Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment. Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models. Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions. Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %.

This paper quantifies the pre-industrial (1850) to present-day (2014) effective radiative forcing (ERF) of anthropogenic emissions of NOX, volatile organic compounds (VOCs; including CO), SO2, NH3, black carbon, organic carbon, and concentrations of methane, N2O and ozone-depleting halocarbons, using CMIP6 models. Concentration and emission changes of reactive species can cause multiple changes in the composition of radiatively active species: tropospheric ozone, stratospheric ozone, stratospheric water vapour, secondary inorganic and organic aerosol, and methane. Where possible we break down the ERFs from each emitted species into the contributions from the composition changes. The ERFs are calculated for each of the models that participated in the AerChemMIP experiments as part of the CMIP6 project, where the relevant model output was available. The 1850 to 2014 multi-model mean ERFs (± standard deviations) are −1.03 ± 0.37 W m−2 for SO2 emissions, −0.25 ± 0.09 W m−2 for organic carbon (OC), 0.15 ± 0.17 W m−2 for black carbon (BC) and −0.07 ± 0.01 W m−2 for NH3. For the combined aerosols (in the piClim-aer experiment) it is −1.01 ± 0.25 W m−2. The multi-model means for the reactive well-mixed greenhouse gases (including any effects on ozone and aerosol chemistry) are 0.67 ± 0.17 W m−2 for methane (CH4), 0.26 ± 0.07 W m−2 for nitrous oxide (N2O) and 0.12 ± 0.2 W m−2 for ozone-depleting halocarbons (HC). Emissions of the ozone precursors nitrogen oxides (NOx), volatile organic compounds and both together (O3) lead to ERFs of 0.14 ± 0.13, 0.09 ± 0.14 and 0.20 ± 0.07 W m−2 respectively. The differences in ERFs calculated for the different models reflect differences in the complexity of their aerosol and chemistry schemes, especially in the case of methane where tropospheric chemistry captures increased forcing from ozone production.

This study presents a multiparameter analysis of aerosol trends over the last 2 decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical-composition and mass aerosol properties by using the observations from several ground-based networks. From these regional time series the aerosol trends have been derived for the different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases in aerosol optical depth (AOD) are found in Europe, North America, South America, North Africa and Asia, ranging from −1.2 % yr−1 to −3.1 % yr−1. An error and representativity analysis of the spatially and temporally limited observational data has been performed using model data subsets in order to investigate how much the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of 10 models (6 AeroCom phase III models and 4 CMIP6 models) and the CAMS reanalysis dataset and of their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, the column Ångström exponent, sulfate and particulate matter well (except in North Africa), but they show larger discrepancies for coarse-mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from that depicted by solely relying on ground-based observations. Using a model with complete diagnostics (NorESM2), we find a global increase in AOD of about 0.2 % yr−1 between 2000 and 2014, primarily caused by an increase in the loads of organic aerosols, sulfate and black carbon.

The diurnal temperature range (DTR) (or difference between the maximum and minimum temperature within a day) is one of many climate parameters that affects health, agriculture and society. Understanding how DTR evolves under global warming is therefore crucial. Physically different drivers of climate change, such as greenhouse gases and aerosols, have distinct influences on global and regional climate. Therefore, predicting the future evolution of DTR requires knowledge of the effects of individual climate forcers, as well as of the future emissions mix, in particular in high-emission regions. Using global climate model simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), we investigate how idealized changes in the atmospheric levels of a greenhouse gas (CO2) and aerosols (black carbon and sulfate) influence DTR (globally and in selected regions). We find broad geographical patterns of annual mean change that are similar between climate drivers, pointing to a generalized response to global warming which is not defined by the individual forcing agents. Seasonal and regional differences, however, are substantial, which highlights the potential importance of local background conditions and feedbacks. While differences in DTR responses among drivers are minor in Europe and North America, there are distinctly different DTR responses to aerosols and greenhouse gas perturbations over India and China, where present aerosol emissions are particularly high. BC induces substantial reductions in DTR, which we attribute to strong modeled BC-induced cloud responses in these regions.

Black carbon (BC) aerosols emitted from natural and anthropogenic sources induce positive radiative forcing and global warming, which in turn significantly affect the Asian summer monsoon (ASM). However, many aspects of the BC effect on the ASM remain elusive and largely inconsistent among previous studies, which is strongly dependent on different low-level thermal feedbacks over the Asian continent and the surrounding ocean. This study examines the response of the ASM to BC forcing in comparison with the effect of doubled greenhouse gases (GHGs) by analyzing the Precipitation Driver Response Model Intercomparison Project (PDRMIP) simulations under an extremely high BC level (10 times modern global BC emissions or concentrations, labeled BC×10) from nine global climate models (GCMs). The results show that although BC and GHGs both enhance the ASM precipitation minus evaporation (P−E; a 13.6 % increase for BC forcing and 12.1 % for GHGs from the nine-model ensemble, respectively), there exists a much larger uncertainty in changes in ASM P−E induced by BC than by GHGs. The summer P−E is increased by 7.7 % to 15.3 % due to these two forcings over three subregions, including East Asian, South Asian and western North Pacific monsoon regions. Further analysis of moisture budget reveals distinct mechanisms controlling the increases in ASM P−E induced by BC and GHGs. The change in ASM P−E by BC is dominated by the dynamic effect due to the enhanced large-scale monsoon circulation, whereas the GHG-induced change is dominated by the thermodynamic effect through increasing atmospheric water vapor. Radiative forcing of BC significantly increases the upper-level atmospheric temperature over the Asian region to enhance the upper-level meridional land–sea thermal gradient (MLOTG), resulting in a northward shift of the upper-level subtropical westerly jet and an enhancement of the low-level monsoon circulation, whereas radiative forcing of GHGs significantly increases the tropical upper-level temperature, which reduces the upper-level MLOTG and suppresses the low-level monsoonal circulation. Hence, our results indicate a different mechanism of BC climate effects under the extremely high BC level: that BC forcing significantly enhances the upper-level atmospheric temperature over the Asian region, determining ASM changes, instead of low-level thermal feedbacks as indicated by previous studies.

The uptake of water by atmospheric aerosols has a pronounced effect on particle light scattering properties, which in turn are strongly dependent on the ambient relative humidity (RH). Earth system models need to account for the aerosol water uptake and its influence on light scattering in order to properly capture the overall radiative effects of aerosols. Here we present a comprehensive model–measurement evaluation of the particle light scattering enhancement factor f(RH), defined as the particle light scattering coefficient at elevated RH (here set to 85 %) divided by its dry value. The comparison uses simulations from 10 Earth system models and a global dataset of surface-based in situ measurements. In general, we find a large diversity in the magnitude of predicted f(RH) amongst the different models, which can not be explained by the site types. Based on our evaluation of sea salt scattering enhancement and simulated organic mass fraction, there is a strong indication that differences in the model parameterizations of hygroscopicity and model chemistry are driving at least some of the observed diversity in simulated f(RH). Additionally, a key point is that defining dry conditions is difficult from an observational point of view and, depending on the aerosol, may influence the measured f(RH). The definition of dry also impacts our model evaluation, because several models exhibit significant water uptake between RH = 0 % and 40 %. The multisite average ratio between model outputs and measurements is 1.64 when RH = 0 % is assumed as the model dry RH and 1.16 when RH = 40 % is the model dry RH value. The overestimation by the models is believed to originate from the hygroscopicity parameterizations at the lower RH range which may not implement all phenomena taking place (i.e., not fully dried particles and hysteresis effects). This will be particularly relevant when a location is dominated by a deliquescent aerosol such as sea salt. Our results emphasize the need to consider the measurement conditions in such comparisons and recognize that measurements referred to as dry may not be dry in model terms. Recommendations for future model–measurement evaluation and model improvements are provided.

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.

Radiative forcing provides an important basis for understanding and predicting global climate changes, but its quantification has historically been done independently for different forcing agents, has involved observations to varying degrees, and studies have not always included a detailed analysis of uncertainties. The Copernicus Atmosphere Monitoring Service reanalysis is an optimal combination of modelling and observations of atmospheric composition. It provides a unique opportunity to rely on observations to quantify the monthly and spatially resolved global distributions of radiative forcing consistently for six of the largest forcing agents: carbon dioxide, methane, tropospheric ozone, stratospheric ozone, aerosol–radiation interactions, and aerosol–cloud interactions. These radiative-forcing estimates account for adjustments in stratospheric temperatures but do not account for rapid adjustments in the troposphere. On a global average and over the period 2003–2017, stratospherically adjusted radiative forcing of carbon dioxide has averaged +1.89 W m−2 (5 %–95 % confidence interval: 1.50 to 2.29 W m−2) relative to 1750 and increased at a rate of 18 % per decade. The corresponding values for methane are +0.46 (0.36 to 0.56) W m−2 and 4 % per decade but with a clear acceleration since 2007. Ozone radiative-forcing averages +0.32 (0 to 0.64) W m−2, almost entirely contributed by tropospheric ozone since stratospheric ozone radiative forcing is only +0.003 W m−2. Aerosol radiative-forcing averages −1.25 (−1.98 to −0.52) W m−2, with aerosol–radiation interactions contributing −0.56 W m−2 and aerosol–cloud interactions contributing −0.69 W m−2 to the global average. Both have been relatively stable since 2003. Taking the six forcing agents together, there is no indication of a sustained slowdown or acceleration in the rate of increase in anthropogenic radiative forcing over the period. These ongoing radiative-forcing estimates will monitor the impact on the Earth's energy budget of the dramatic emission reductions towards net-zero that are needed to limit surface temperature warming to the Paris Agreement temperature targets. Indeed, such impacts should be clearly manifested in radiative forcing before being clear in the temperature record. In addition, this radiative-forcing dataset can provide the input distributions needed by researchers involved in monitoring of climate change, detection and attribution, interannual to decadal prediction, and integrated assessment modelling. The data generated by this work are available at https://doi.org/10.24380/ads.1hj3y896 (Bellouin et al., 2020b).

The radiative forcing of the aerosol–radiation interaction can be decomposed into clear-sky and cloudy-sky portions. Two sets of multi-model simulations within Aerosol Comparisons between Observations and Models (AeroCom), combined with observational methods, and the time evolution of aerosol emissions over the industrial era show that the contribution from cloudy-sky regions is likely weak. A mean of the simulations considered is 0.01±0.1 W m−2. Multivariate data analysis of results from AeroCom Phase II shows that many factors influence the strength of the cloudy-sky contribution to the forcing of the aerosol–radiation interaction. Overall, single-scattering albedo of anthropogenic aerosols and the interaction of aerosols with the short-wave cloud radiative effects are found to be important factors. A more dedicated focus on the contribution from the cloud-free and cloud-covered sky fraction, respectively, to the aerosol–radiation interaction will benefit the quantification of the radiative forcing and its uncertainty range.

Shortwave cloud radiative effects (SWCREs), defined as the difference of the shortwave radiative flux between all-sky and clear-sky conditions at the surface, have been reported to play an important role in influencing the Earth's energy budget and temperature extremes. In this study, we employed a set of global climate models to examine the SWCRE responses to CO2, black carbon (BC) aerosols, and sulfate aerosols in boreal summer over the Northern Hemisphere. We found that CO2 causes positive SWCRE changes over most of the NH, and BC causes similar positive responses over North America, Europe, and eastern China but negative SWCRE over India and tropical Africa. When normalized by effective radiative forcing, the SWCRE from BC is roughly 3–5 times larger than that from CO2. SWCRE change is mainly due to cloud cover changes resulting from changes in relative humidity (RH) and, to a lesser extent, changes in cloud liquid water, circulation, dynamics, and stability. The SWCRE response to sulfate aerosols, however, is negligible compared to that for CO2 and BC because part of the radiation scattered by clouds under all-sky conditions will also be scattered by aerosols under clear-sky conditions. Using a multilinear regression model, it is found that mean daily maximum temperature (Tmax) increases by 0.15 and 0.13 K per watt per square meter (W m−2) increase in local SWCRE under the CO2 and BC experiment, respectively. When domain-averaged, the contribution of SWCRE change to summer mean Tmax changes was 10 %–30 % under CO2 forcing and 30 %–50 % under BC forcing, varying by region, which can have important implications for extreme climatic events and socioeconomic activities.

The hydroxyl radical (OH) plays critical roles within the troposphere, such as determining the lifetime of methane (CH4), yet is challenging to model due to its fast cycling and dependence on a multitude of sources and sinks. As a result, the reasons for variations in OH and the resulting methane lifetime (τCH4), both between models and in time, are difficult to diagnose. We apply a neural network (NN) approach to address this issue within a group of models that participated in the Chemistry-Climate Model Initiative (CCMI). Analysis of the historical specified dynamics simulations performed for CCMI indicates that the primary drivers of τCH4 differences among 10 models are the flux of UV light to the troposphere (indicated by the photolysis frequency JO1D), the mixing ratio of tropospheric ozone (O3), the abundance of nitrogen oxides (NOx≡NO+NO2), and details of the various chemical mechanisms that drive OH. Water vapour, carbon monoxide (CO), the ratio of NO:NOx, and formaldehyde (HCHO) explain moderate differences in τCH4, while isoprene, methane, the photolysis frequency of NO2 by visible light (JNO2), overhead ozone column, and temperature account for little to no model variation in τCH4. We also apply the NNs to analysis of temporal trends in OH from 1980 to 2015. All models that participated in the specified dynamics historical simulation for CCMI demonstrate a decline in τCH4 during the analysed timeframe. The significant contributors to this trend, in order of importance, are tropospheric O3, JO1D, NOx, and H2O, with CO also causing substantial interannual variability in OH burden. Finally, the identified trends in τCH4 are compared to calculated trends in the tropospheric mean OH concentration from previous work, based on analysis of observations. The comparison reveals a robust result for the effect of rising water vapour on OH and τCH4, imparting an increasing and decreasing trend of about 0.5 % decade−1, respectively. The responses due to NOx, ozone column, and temperature are also in reasonably good agreement between the two studies.

Emissions of anthropogenic aerosols are expected to change drastically over the coming decades, with potentially significant climate implications. Using the most recent generation of harmonized emission scenarios, the Shared Socioeconomic Pathways (SSPs) as input to a global chemistry transport and radiative transfer model, we provide estimates of the projected future global and regional burdens and radiative forcing of anthropogenic aerosols under three contrasting pathways for air pollution levels: SSP1-1.9, SSP2-4.5 and SSP3-7.0. We find that the broader range of future air pollution emission trajectories spanned by the SSPs compared to previous scenarios translates into total aerosol forcing estimates in 2100 relative to 1750 ranging from −0.04 in SSP1-1.9 to −0.51 W m−2 in SSP3-7.0. Compared to our 1750–2015 estimate of −0.55 W m−2, this shows that, depending on the success of air pollution policies and socioeconomic development over the coming decades, aerosol radiative forcing may weaken by nearly 95 % or remain close to the preindustrial to present-day level. In all three scenarios there is a positive forcing in 2100 relative to 2015, from 0.51 in SSP1-1.9 to 0.04 W m−2 in SSP3-7.0. Results also demonstrate significant differences across regions and scenarios, especially in South Asia and Africa. While rapid weakening of the negative aerosol forcing following effective air quality policies will unmask more of the greenhouse-gas-induced global warming, slow progress on mitigating air pollution will significantly enhance the atmospheric aerosol levels and risk to human health in these regions. In either case, the resulting impacts on regional and global climate can be significant.

Water vapour in the atmosphere is the source of a major climate feedback mechanism and potential increases in the availability of water vapour could have important consequences for mean and extreme precipitation. Future precipitation changes further depend on how the hydrological cycle responds to different drivers of climate change, such as greenhouse gases and aerosols. Currently, neither the total anthropogenic influence on the hydrological cycle nor that from individual drivers is constrained sufficiently to make solid projections. We investigate how integrated water vapour (IWV) responds to different drivers of climate change. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulfate have been perturbed separately. While the global-mean IWV is usually assumed to increase by ∼7 % per kelvin of surface temperature change, we find that the feedback response of IWV differs somewhat between drivers. Fast responses, which include the initial radiative effect and rapid adjustments to an external forcing, amplify these differences. The resulting net changes in IWV range from 6.4±0.9 % K−1 for sulfate to 9.8±2 % K−1 for BC. We further calculate the relationship between global changes in IWV and precipitation, which can be characterized by quantifying changes in atmospheric water vapour lifetime. Global climate models simulate a substantial increase in the lifetime, from 8.2±0.5 to 9.9±0.7 d between 1986–2005 and 2081–2100 under a high-emission scenario, and we discuss to what extent the water vapour lifetime provides additional information compared to analysis of IWV and precipitation separately. We conclude that water vapour lifetime changes are an important indicator of changes in precipitation patterns and that BC is particularly efficient in prolonging the mean time, and therefore likely the distance, between evaporation and precipitation.

We document the ability of the new-generation Oslo chemistry-transport model, Oslo CTM3, to accurately simulate present-day aerosol distributions. The model is then used with the new Community Emission Data System (CEDS) historical emission inventory to provide updated time series of anthropogenic aerosol concentrations and consequent direct radiative forcing (RFari) from 1750 to 2014.Overall, Oslo CTM3 performs well compared with measurements of surface concentrations and remotely sensed aerosol optical depth. Concentrations are underestimated in Asia, but the higher emissions in CEDS than previous inventories result in improvements compared to observations. The treatment of black carbon (BC) scavenging in Oslo CTM3 gives better agreement with observed vertical BC profiles relative to the predecessor Oslo CTM2. However, Arctic wintertime BC concentrations remain underestimated, and a range of sensitivity tests indicate that better physical understanding of processes associated with atmospheric BC processing is required to simultaneously reproduce both the observed features. Uncertainties in model input data, resolution, and scavenging affect the distribution of all aerosols species, especially at high latitudes and altitudes. However, we find no evidence of consistently better model performance across all observables and regions in the sensitivity tests than in the baseline configuration.Using CEDS, we estimate a net RFari in 2014 relative to 1750 of −0.17 W m−2, significantly weaker than the IPCC AR5 2011–1750 estimate. Differences are attributable to several factors, including stronger absorption by organic aerosol, updated parameterization of BC absorption, and reduced sulfate cooling. The trend towards a weaker RFari over recent years is more pronounced than in the IPCC AR5, illustrating the importance of capturing recent regional emission changes.

Abstract Stratospheric temperature adjustment (STA) is often a significant component of greenhouse gas radiative forcing (RF), for both the most widely used definition of RF and effective radiative forcing. It is well established that the magnitude and sign of STA differs among greenhouse gases, being negative (at the tropopause) for CO2 increases (because it induces a cooling of the stratosphere) and positive for many halocarbons (because they induce a warming of the stratosphere); this effect is strongly related to the opacity (and hence the effective emitting temperature) of the troposphere at the wavelengths at which gases absorb. Here the spectral variation of STA is examined for the first time by systematically imposing a weak absorber in each of 300 bands of a narrow‐band radiation code. For this weak absorber, STA is negative for wavelengths greater than about 13 μm and positive in the 8‐ to 13‐μm “window” except in the vicinity of the 9.6‐μm ozone band. By combining narrow‐band and line‐by‐line model results, these findings are used to improve a widely used fast method to estimate radiative efficiency (RE, the RF per unit change in concentration) directly from laboratory measurements or theoretical calculations of halocarbon absorption cross sections; the new method reproduces detailed RE calculations to better than 1.4%. This is a significant improvement over a cruder method used to account for STA in RE tabulations in the Intergovernmental Panel on Climate Change's Fifth Assessment Report, which were used to calculate metrics such as the Global Warming Potential, for halocarbons and related substances.

Inferred effective climate sensitivity (ECSinf) is estimated using a method combining radiative forcing (RF) time series and several series of observed ocean heat content (OHC) and near-surface temperature change in a Bayesian framework using a simple energy balance model and a stochastic model. The model is updated compared to our previous analysis by using recent forcing estimates from IPCC, including OHC data for the deep ocean, and extending the time series to 2014. In our main analysis, the mean value of the estimated ECSinf is 2.0 °C, with a median value of 1.9 °C and a 90 % credible interval (CI) of 1.2–3.1 °C. The mean estimate has recently been shown to be consistent with the higher values for the equilibrium climate sensitivity estimated by climate models. The transient climate response (TCR) is estimated to have a mean value of 1.4 °C (90 % CI 0.9–2.0 °C), and in our main analysis the posterior aerosol effective radiative forcing is similar to the range provided by the IPCC. We show a strong sensitivity of the estimated ECSinf to the choice of a priori RF time series, excluding pre-1950 data and the treatment of OHC data. Sensitivity analysis performed by merging the upper (0–700 m) and the deep-ocean OHC or using only one OHC dataset (instead of four in the main analysis) both give an enhancement of the mean ECSinf by about 50 % from our best estimate.

Atmospheric aerosols and greenhouse gases affect cloud properties, radiative balance and, thus, the hydrological cycle. Observations show that precipitation has decreased in the Mediterranean since the beginning of the 20th century, and many studies have investigated possible mechanisms. So far, however, the effects of aerosol forcing on Mediterranean precipitation remain largely unknown. Here we compare the modeled dynamical response of Mediterranean precipitation to individual forcing agents in a set of global climate models (GCMs). Our analyses show that both greenhouse gases and aerosols can cause drying in the Mediterranean and that precipitation is more sensitive to black carbon (BC) forcing than to well-mixed greenhouse gases (WMGHGs) or sulfate aerosol. In addition to local heating, BC appears to reduce precipitation by causing an enhanced positive sea level pressure (SLP) pattern similar to the North Atlantic Oscillation–Arctic Oscillation, characterized by higher SLP at midlatitudes and lower SLP at high latitudes. WMGHGs cause a similar SLP change, and both are associated with a northward diversion of the jet stream and storm tracks, reducing precipitation in the Mediterranean while increasing precipitation in northern Europe. Though the applied forcings were much larger, if forcings are scaled to those of the historical period of 1901–2010, roughly one-third (31±17 %) of the precipitation decrease would be attributable to global BC forcing with the remainder largely attributable to WMGHGs, whereas global scattering sulfate aerosols would have negligible impacts. Aerosol–cloud interactions appear to have minimal impacts on Mediterranean precipitation in these models, at least in part because many simulations did not fully include such processes; these merit further study. The findings from this study suggest that future BC and WMGHG emissions may significantly affect regional water resources, agricultural practices, ecosystems and the economy in the Mediterranean region.

Precipitation changes are strongly linked to the Earth’s energy budget. Here the authors show that changes in sensible heat are the dominant contributor to the present global-mean precipitation change since pre-industrial time.

An assessment of global particulate nitrate and ammonium aerosol based on simulations from nine models participating in the Aerosol Comparisons between Observations and Models (AeroCom) phase III study is presented. A budget analysis was conducted to understand the typical magnitude, distribution, and diversity of the aerosols and their precursors among the models. To gain confidence regarding model performance, the model results were evaluated with various observations globally, including ground station measurements over North America, Europe, and east Asia for tracer concentrations and dry and wet depositions, as well as with aircraft measurements in the Northern Hemisphere mid-to-high latitudes for tracer vertical distributions. Given the unique chemical and physical features of the nitrate occurrence, we further investigated the similarity and differentiation among the models by examining (1) the pH-dependent NH3 wet deposition; (2) the nitrate formation via heterogeneous chemistry on the surface of dust and sea salt particles or thermodynamic equilibrium calculation including dust and sea salt ions; and (3) the nitrate coarse-mode fraction (i.e., coarse/total). It is found that HNO3, which is simulated explicitly based on full O3-HOx-NOx-aerosol chemistry by all models, differs by up to a factor of 9 among the models in its global tropospheric burden. This partially contributes to a large difference in NO3−, whose atmospheric burden differs by up to a factor of 13. The atmospheric burdens of NH3 and NH4+ differ by 17 and 4, respectively. Analyses at the process level show that the large diversity in atmospheric burdens of NO3−, NH3, and NH4+ is also related to deposition processes. Wet deposition seems to be the dominant process in determining the diversity in NH3 and NH4+ lifetimes. It is critical to correctly account for contributions of heterogeneous chemical production of nitrate on dust and sea salt, because this process overwhelmingly controls atmospheric nitrate production (typically > 80 %) and determines the coarse- and fine-mode distribution of nitrate aerosol.

Atmospheric aerosols from anthropogenic and natural sources reach the polar regions through long-range transport and affect the local radiation balance. Such transport is, however, poorly constrained in present-day global climate models, and few multi-model evaluations of polar anthropogenic aerosol radiative forcing exist. Here we compare the aerosol optical depth (AOD) at 550 nm from simulations with 16 global aerosol models from the AeroCom Phase II model intercomparison project with available observations at both poles. We show that the annual mean multi-model median is representative of the observations in Arctic, but that the intermodel spread is large. We also document the geographical distribution and seasonal cycle of the AOD for the individual aerosol species: black carbon (BC) from fossil fuel and biomass burning, sulfate, organic aerosols (OAs), dust, and sea-salt. For a subset of models that represent nitrate and secondary organic aerosols (SOAs), we document the role of these aerosols at high latitudes.The seasonal dependence of natural and anthropogenic aerosols differs with natural aerosols peaking in winter (sea-salt) and spring (dust), whereas AOD from anthropogenic aerosols peaks in late spring and summer. The models produce a median annual mean AOD of 0.07 in the Arctic (defined here as north of 60° N). The models also predict a noteworthy aerosol transport to the Antarctic (south of 70° S) with a resulting AOD varying between 0.01 and 0.02. The models have estimated the shortwave anthropogenic radiative forcing contributions to the direct aerosol effect (DAE) associated with BC and OA from fossil fuel and biofuel (FF), sulfate, SOAs, nitrate, and biomass burning from BC and OA emissions combined. The Arctic modelled annual mean DAE is slightly negative (−0.12 W m−2), dominated by a positive BC FF DAE in spring and a negative sulfate DAE in summer. The Antarctic DAE is governed by BC FF. We perform sensitivity experiments with one of the AeroCom models (GISS modelE) to investigate how regional emissions of BC and sulfate and the lifetime of BC influence the Arctic and Antarctic AOD. A doubling of emissions in eastern Asia results in a 33 % increase in Arctic AOD of BC. A doubling of the BC lifetime results in a 39 % increase in Arctic AOD of BC. However, these radical changes still fall within the AeroCom model range.

The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and their climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. Specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.

Over the past few decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and air pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990–2015, as simulated by seven global atmospheric composition models. The models broadly reproduce large-scale changes in surface aerosol and ozone based on observations (e.g. −1 to −3 % yr−1 in aerosols over the USA and Europe). The global mean radiative forcing due to ozone and aerosol changes over the 1990–2015 period increased by +0.17 ± 0.08 W m−2, with approximately one-third due to ozone. This increase is more strongly positive than that reported in IPCC AR5. The main reasons for the increased positive radiative forcing of aerosols over this period are the substantial reduction of global mean SO2 emissions, which is stronger in the new emission inventory compared to that used in the IPCC analysis, and higher black carbon emissions.

In the Hemispheric Transport of Air Pollution Phase 2 (HTAP2) exercise, a range of global atmospheric general circulation and chemical transport models performed coordinated perturbation experiments with 20 % reductions in emissions of anthropogenic aerosols, or aerosol precursors, in a number of source regions. Here, we compare the resulting changes in the atmospheric load and vertically resolved profiles of black carbon (BC), organic aerosols (OA) and sulfate (SO4) from 10 models that include treatment of aerosols. We use a set of temporally, horizontally and vertically resolved profiles of aerosol forcing efficiency (AFE) to estimate the impact of emission changes in six major source regions on global radiative forcing (RF) pertaining to the direct aerosol effect, finding values between. 51.9 and 210.8 mW m−2 Tg−1 for BC, between −2.4 and −17.9 mW m−2 Tg−1 for OA and between −3.6 and −10.3 W m−2 Tg−1 for SO4. In most cases, the local influence dominates, but results show that mitigations in south and east Asia have substantial impacts on the radiative budget in all investigated receptor regions, especially for BC. In Russia and the Middle East, more than 80 % of the forcing for BC and OA is due to extra-regional emission reductions. Similarly, for North America, BC emissions control in east Asia is found to be more important than domestic mitigations, which is consistent with previous findings. Comparing fully resolved RF calculations to RF estimates based on vertically averaged AFE profiles allows us to quantify the importance of vertical resolution to RF estimates. We find that locally in the source regions, a 20 % emission reduction strengthens the radiative forcing associated with SO4 by 25 % when including the vertical dimension, as the AFE for SO4 is strongest near the surface. Conversely, the local RF from BC weakens by 37 % since BC AFE is low close to the ground. The fraction of BC direct effect forcing attributable to intercontinental transport, on the other hand, is enhanced by one-third when accounting for the vertical aspect, because long-range transport primarily leads to aerosol changes at high altitudes, where the BC AFE is strong. While the surface temperature response may vary with the altitude of aerosol change, the analysis in the present study is not extended to estimates of temperature or precipitation changes.

Predictions of temperature and precipitation responses to changes in the anthropogenic emissions of climate forcers require the quantification of the radiative forcing exerted by those changes. This task is particularly difficult for near-term climate forcers like aerosols, methane, and ozone precursors because their short atmospheric lifetimes cause regionally and temporally inhomogeneous radiative forcings. This study quantifies specific radiative forcing, defined as the radiative forcing per unit change in mass emitted, for eight near-term climate forcers as a function of their source regions and the season of emission by using dedicated simulations by four general circulation and chemistry-transport models. Although differences in the representation of atmospheric chemistry and radiative processes in different models impede the creation of a uniform dataset, four distinct findings can be highlighted. Firstly, specific radiative forcing for sulfur dioxide and organic carbon are stronger when aerosol–cloud interactions are taken into account. Secondly, there is a lack of agreement on the sign of the specific radiative forcing of volatile organic compound perturbations, suggesting they are better avoided in climate mitigation strategies. Thirdly, the strong seasonalities of the specific radiative forcing of most forcers allow strategies to minimise positive radiative forcing based on the timing of emissions. Finally, European and shipping emissions exert stronger aerosol specific radiative forcings compared to East Asia where the baseline is more polluted. This study can therefore form the basis for further refining climate mitigation options based on regional and seasonal controls on emissions. For example, reducing summertime emissions of black carbon and wintertime emissions of sulfur dioxide in the more polluted regions is a possible way to improve air quality without weakening the negative radiative forcing of aerosols.

The ability of seven state-of-the-art chemistry–aerosol models to reproduce distributions of tropospheric ozone and its precursors, as well as aerosols over eastern Asia in summer 2008, is evaluated. The study focuses on the performance of models used to assess impacts of pollutants on climate and air quality as part of the EU ECLIPSE project. Models, run using the same ECLIPSE emissions, are compared over different spatial scales to in situ surface, vertical profiles and satellite data. Several rather clear biases are found between model results and observations, including overestimation of ozone at rural locations downwind of the main emission regions in China, as well as downwind over the Pacific. Several models produce too much ozone over polluted regions, which is then transported downwind. Analysis points to different factors related to the ability of models to simulate VOC-limited regimes over polluted regions and NOx limited regimes downwind. This may also be linked to biases compared to satellite NO2, indicating overestimation of NO2 over and to the north of the northern China Plain emission region. On the other hand, model NO2 is too low to the south and west of this region and over South Korea/Japan. Overestimation of ozone is linked to systematic underestimation of CO particularly at rural sites and downwind of the main Chinese emission regions. This is likely to be due to enhanced destruction of CO by OH. Overestimation of Asian ozone and its transport downwind implies that radiative forcing from this source may be overestimated. Model-observation discrepancies over Beijing do not appear to be due to emission controls linked to the Olympic Games in summer 2008.With regard to aerosols, most models reproduce the satellite-derived AOD patterns over eastern China. Our study nevertheless reveals an overestimation of ECLIPSE model mean surface BC and sulphate aerosols in urban China in summer 2008. The effect of the short-term emission mitigation in Beijing is too weak to explain the differences between the models. Our results rather point to an overestimation of SO2 emissions, in particular, close to the surface in Chinese urban areas. However, we also identify a clear underestimation of aerosol concentrations over northern India, suggesting that the rapid recent growth of emissions in India, as well as their spatial extension, is underestimated in emission inventories. Model deficiencies in the representation of pollution accumulation due to the Indian monsoon may also be playing a role. Comparison with vertical aerosol lidar measurements highlights a general underestimation of scattering aerosols in the boundary layer associated with overestimation in the free troposphere pointing to modelled aerosol lifetimes that are too long. This is likely linked to too strong vertical transport and/or insufficient deposition efficiency during transport or export from the boundary layer, rather than chemical processing (in the case of sulphate aerosols). Underestimation of sulphate in the boundary layer implies potentially large errors in simulated aerosol–cloud interactions, via impacts on boundary-layer clouds.This evaluation has important implications for accurate assessment of air pollutants on regional air quality and global climate based on global model calculations. Ideally, models should be run at higher resolution over source regions to better simulate urban–rural pollutant gradients and/or chemical regimes, and also to better resolve pollutant processing and loss by wet deposition as well as vertical transport. Discrepancies in vertical distributions require further quantification and improvement since these are a key factor in the determination of radiative forcing from short-lived pollutants.

Observations at surface sites show an increase in global mean surface methane (CH4) of about 180 parts per billion (ppb) (above 10 %) over the period 1984–2012. Over this period there are large fluctuations in the annual growth rate. In this work, we investigate the atmospheric CH4 evolution over the period 1970–2012 with the Oslo CTM3 global chemical transport model (CTM) in a bottom-up approach. We thoroughly assess data from surface measurement sites in international networks and select a subset suited for comparisons with the output from the CTM. We compare model results and observations to understand causes for both long-term trends and short-term variations. Employing Oslo CTM3 we are able to reproduce the seasonal and year-to-year variations and shifts between years with consecutive growth and stagnation, both at global and regional scales. The overall CH4 trend over the period is reproduced, but for some periods the model fails to reproduce the strength of the growth. The model overestimates the observed growth after 2006 in all regions. This seems to be explained by an overly strong increase in anthropogenic emissions in Asia, having global impact. Our findings confirm other studies questioning the timing or strength of the emission changes in Asia in the EDGAR v4.2 emission inventory over recent decades. The evolution of CH4 is not only controlled by changes in sources, but also by changes in the chemical loss in the atmosphere and soil uptake. The atmospheric CH4 lifetime is an indicator of the CH4 loss. In our simulations, the atmospheric CH4 lifetime decreases by more than 8 % from 1970 to 2012, a significant reduction of the residence time of this important greenhouse gas. Changes in CO and NOx emissions, specific humidity, and ozone column drive most of this, and we provide simple prognostic equations for the relations between those and the CH4 lifetime. The reduced lifetime results in substantial growth in the chemical CH4 loss (relative to its burden) and dampens the CH4 growth.

This paper presents a summary of the work done within the European Union's Seventh Framework Programme project ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants). ECLIPSE had a unique systematic concept for designing a realistic and effective mitigation scenario for short-lived climate pollutants (SLCPs; methane, aerosols and ozone, and their precursor species) and quantifying its climate and air quality impacts, and this paper presents the results in the context of this overarching strategy. The first step in ECLIPSE was to create a new emission inventory based on current legislation (CLE) for the recent past and until 2050. Substantial progress compared to previous work was made by including previously unaccounted types of sources such as flaring of gas associated with oil production, and wick lamps. These emission data were used for present-day reference simulations with four advanced Earth system models (ESMs) and six chemistry transport models (CTMs). The model simulations were compared with a variety of ground-based and satellite observational data sets from Asia, Europe and the Arctic. It was found that the models still underestimate the measured seasonality of aerosols in the Arctic but to a lesser extent than in previous studies. Problems likely related to the emissions were identified for northern Russia and India, in particular. To estimate the climate impacts of SLCPs, ECLIPSE followed two paths of research: the first path calculated radiative forcing (RF) values for a large matrix of SLCP species emissions, for different seasons and regions independently. Based on these RF calculations, the Global Temperature change Potential metric for a time horizon of 20 years (GTP20) was calculated for each SLCP emission type. This climate metric was then used in an integrated assessment model to identify all emission mitigation measures with a beneficial air quality and short-term (20-year) climate impact. These measures together defined a SLCP mitigation (MIT) scenario. Compared to CLE, the MIT scenario would reduce global methane (CH4) and black carbon (BC) emissions by about 50 and 80 %, respectively. For CH4, measures on shale gas production, waste management and coal mines were most important. For non-CH4 SLCPs, elimination of high-emitting vehicles and wick lamps, as well as reducing emissions from gas flaring, coal and biomass stoves, agricultural waste, solvents and diesel engines were most important. These measures lead to large reductions in calculated surface concentrations of ozone and particulate matter. We estimate that in the EU, the loss of statistical life expectancy due to air pollution was 7.5 months in 2010, which will be reduced to 5.2 months by 2030 in the CLE scenario. The MIT scenario would reduce this value by another 0.9 to 4.3 months. Substantially larger reductions due to the mitigation are found for China (1.8 months) and India (11–12 months). The climate metrics cannot fully quantify the climate response. Therefore, a second research path was taken. Transient climate ensemble simulations with the four ESMs were run for the CLE and MIT scenarios, to determine the climate impacts of the mitigation. In these simulations, the CLE scenario resulted in a surface temperature increase of 0.70 ± 0.14 K between the years 2006 and 2050. For the decade 2041–2050, the warming was reduced by 0.22 ± 0.07 K in the MIT scenario, and this result was in almost exact agreement with the response calculated based on the emission metrics (reduced warming of 0.22 ± 0.09 K). The metrics calculations suggest that non-CH4 SLCPs contribute ~ 22 % to this response and CH4 78 %. This could not be fully confirmed by the transient simulations, which attributed about 90 % of the temperature response to CH4 reductions. Attribution of the observed temperature response to non-CH4 SLCP emission reductions and BC specifically is hampered in the transient simulations by small forcing and co-emitted species of the emission basket chosen. Nevertheless, an important conclusion is that our mitigation basket as a whole would lead to clear benefits for both air quality and climate. The climate response from BC reductions in our study is smaller than reported previously, possibly because our study is one of the first to use fully coupled climate models, where unforced variability and sea ice responses cause relatively strong temperature fluctuations that may counteract (and, thus, mask) the impacts of small emission reductions. The temperature responses to the mitigation were generally stronger over the continents than over the oceans, and with a warming reduction of 0.44 K (0.39–0.49) K the largest over the Arctic. Our calculations suggest particularly beneficial climate responses in southern Europe, where surface warming was reduced by about 0.3 K and precipitation rates were increased by about 15 (6–21) mm yr−1 (more than 4 % of total precipitation) from spring to autumn. Thus, the mitigation could help to alleviate expected future drought and water shortages in the Mediterranean area. We also report other important results of the ECLIPSE project.

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealized, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere–ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all models showing an increase in surface temperature focussed in the Northern Hemisphere mid and (especially) high latitudes, and showing a corresponding increase in global mean precipitation. Changes in precipitation patterns are driven mostly by a northward shift in the ITCZ (Intertropical Convergence Zone), consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker response, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

In the presence of snow, the bias in the prediction of surface albedo by many climate models remains difficult to correct due to the difficulties of separating the albedo parameterizations from those describing snow and vegetation cover and structure. This can be overcome by extracting the albedo parameterizations in isolation, by executing them with observed meteorology and information on vegetation structure, and by comparing the resulting predictions to observations. Here, we employ an empirical data set of forest structure and daily meteorology for three snow cover seasons and for three case regions in boreal Norway to compute and evaluate predicted albedo to those based on daily MODIS retrievals. Forest and adjacent open area albedos are subsequently used to estimate bias in top-of-the-atmosphere (TOA) radiative forcings (RF) from albedo changes (Δα, Open–Forest) connected to land use and land cover changes (LULCC). As expected, given the diversity of approaches by which snow masking by tall-statured vegetation is parameterized, the magnitude and sign of the albedo biases varied considerably for forests. Large biases at the open sites were also detected, which was unexpected given that these sites were snow-covered throughout most of the analytical time period, therefore eliminating potential biases linked to snow-masking parameterizations. Biases at the open sites were mostly positive, exacerbating the strength of vegetation masking effects and hence the simulated LULCC Δα RF. Despite the large biases in both forest and open area albedos by some schemes in some months and years, the mean Δα RF bias over the 3-year period (November–May) was considerably small across models (−2.1 ± 1.04 Wm−2; 21 ± 11%); four of six models had normalized mean absolute errors less than 20%. Identifying systematic sources of the albedo prediction biases proved challenging, although for some schemes clear sources were identified.

Radiative forcing (RF) of black carbon (BC) in the atmosphere is estimated using radiative transfer codes of various complexities. Here we show that the two-stream radiative transfer codes used most in climate models give too strong forward scattering, leading to enhanced absorption at the surface and too weak absorption by BC in the atmosphere. Such calculations are found to underestimate the positive RF of BC by 10% for global mean, all sky conditions, relative to the more sophisticated multi-stream models. The underestimation occurs primarily for low surface albedo, even though BC is more efficient for absorption of solar radiation over high surface albedo.

Atmospheric black carbon (BC) absorbs solar radiation, and exacerbates global warming through exerting positive radiative forcing (RF). However, the contribution of BC to ongoing changes in global climate is under debate. Anthropogenic BC emissions, and the resulting distribution of BC concentration, are highly uncertain. In particular, long-range transport and processes affecting BC atmospheric lifetime are poorly understood. Here we discuss whether recent assessments may have overestimated present-day BC radiative forcing in remote regions. We compare vertical profiles of BC concentration from four recent aircraft measurement campaigns to simulations by 13 aerosol models participating in the AeroCom Phase II intercomparison. An atmospheric lifetime of BC of less than 5 days is shown to be essential for reproducing observations in remote ocean regions, in line with other recent studies. Adjusting model results to measurements in remote regions, and at high altitudes, leads to a 25% reduction in AeroCom Phase II median direct BC forcing, from fossil fuel and biofuel burning, over the industrial era. The sensitivity of modelled forcing to BC vertical profile and lifetime highlights an urgent need for further flight campaigns, close to sources and in remote regions, to provide improved quantification of BC effects for use in climate policy.

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

The aerosol direct radiative effect (ADRE) is defined as the change in the solar radiation flux, F, due to aerosol scattering and absorption. The difficulty in determining ADRE stems mainly from the need to estimate F without aerosols, F0, with either radiative transfer modeling and knowledge of the atmospheric state, or regression analysis of radiation data down to zero aerosol optical depth (AOD), if only F and AOD are observed. This paper examines the regression analysis method by using modeled surface data products provided by the Aerosol Robotic Network (AERONET). We extrapolated F0 by two functions: a straight linear line and an exponential nonlinear decay. The exponential decay regression is expected to give a better estimation of ADRE with a few percent larger extrapolated F0 than the linear regression. We found that, contrary to the expectation, in most cases the linear regression gives better results than the nonlinear. In such cases the extrapolated F0 represents an unrealistically low water vapor column (WVC), resulting in underestimation of attenuation caused by the water vapor, and hence too large F0 and overestimation of the magnitude of ADRE. The nonlinear ADRE is generally 40–50% larger in magnitude than the linear ADRE due to the extrapolated F0 difference. Since for a majority of locations, AOD and WVC have a positive correlation, the extrapolated F0 with the nonlinear regression fit represents an unrealistically low WVC, and hence too large F0. The systematic underestimation of F0 with the linear regression is compensated by the positive correlation between AOD and water vapor, providing the better result.

Equilibrium climate sensitivity (ECS) is constrained based on observed near-surface temperature change, changes in ocean heat content (OHC) and detailed radiative forcing (RF) time series from pre-industrial times to 2010 for all main anthropogenic and natural forcing mechanism. The RF time series are linked to the observations of OHC and temperature change through an energy balance model (EBM) and a stochastic model, using a Bayesian approach to estimate the ECS and other unknown parameters from the data. For the net anthropogenic RF the posterior mean in 2010 is 2.0 Wm−2, with a 90% credible interval (C.I.) of 1.3 to 2.8 Wm−2, excluding present-day total aerosol effects (direct + indirect) stronger than −1.7 Wm−2. The posterior mean of the ECS is 1.8 °C, with 90% C.I. ranging from 0.9 to 3.2 °C, which is tighter than most previously published estimates. We find that using three OHC data sets simultaneously and data for global mean temperature and OHC up to 2010 substantially narrows the range in ECS compared to using less updated data and only one OHC data set. Using only one OHC set and data up to 2000 can produce comparable results as previously published estimates using observations in the 20th century, including the heavy tail in the probability function. The analyses show a significant contribution of internal variability on a multi-decadal scale to the global mean temperature change. If we do not explicitly account for long-term internal variability, the 90% C.I. is 40% narrower than in the main analysis and the mean ECS becomes slightly lower, which demonstrates that the uncertainty in ECS may be severely underestimated if the method is too simple. In addition to the uncertainties represented through the estimated probability density functions, there may be uncertainties due to limitations in the treatment of the temporal development in RF and structural uncertainties in the EBM.

The diurnal variability of aerosol optical depth (AOD) can be significant, depending on location and dominant aerosol type. However, these diurnal cycles have rarely been taken into account in measurement-based estimates of aerosol direct radiative forcing (ADRF) or aerosol direct radiative effect (ADRE). The objective of our study was to estimate the influence of diurnal aerosol variability at the top of the atmosphere ADRE estimates. By including all the possible AERONET sites, we wanted to assess the influence on global ADRE estimates. While focusing also in more detail on some selected sites of strongest impact, our goal was to also see the possible impact regionally. We calculated ADRE with different assumptions about the daily AOD variability: taking the observed daily AOD cycle into account and assuming diurnally constant AOD. Moreover, we estimated the corresponding differences in ADREs, if the single AOD value for the daily mean was taken from the the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra or Aqua overpass times, instead of accounting for the true observed daily variability. The mean impact of diurnal AOD variability on 24 h ADRE estimates, averaged over all AERONET sites, was rather small and it was relatively small even for the cases when AOD was chosen to correspond to the Terra or Aqua overpass time. This was true on average over all AERONET sites, while clearly there can be much stronger impact in individual sites. Examples of some selected sites demonstrated that the strongest observed AOD variability (the strongest morning afternoon contrast) does not typically result in a significant impact on 24 h ADRE. In those cases, the morning and afternoon AOD patterns are opposite and thus the impact on 24 h ADRE, when integrated over all solar zenith angles, is reduced. The most significant effect on daily ADRE was induced by AOD cycles with either maximum or minimum AOD close to local noon. In these cases, the impact on 24 h ADRE was typically around 0.1–0.2 W m−2 (both positive and negative) in absolute values, 5–10% in relative ones.

Shipping is a growing sector in the global economy, and it contributions to global CO2 emissions are expected to increase. CO2 emissions from the world shipping fleet will likely be regulated in the near future, and studies have shown that significant emission reductions can be achieved at low cost. Regulations are being discussed for both existing ships as well as for future additions to the fleet. In this study a plausible CO2 emission reduction inventory is constructed for the cargo fleet existing in 2010, as well as for container ships, bulk ships and tankers separately. In the reduction inventories, CO2 emissions are reduced by 25–32% relative to baseline by applying 15 technical and operational emission reduction measures in accordance with a ship-type-specific cost-effectiveness criterion, and 9 other emission compounds are changed as a technical implication of reducing CO2. The overall climate and environmental effects of the changes to all 10 emission components in the reduction inventory are assessed using a chemical transport model, radiative forcing (RF) models and a simple climate model. We find substantial environmental and health benefits with up to 5% reduction in surface ozone levels, 15% reductions in surface sulfate and 10% reductions in wet deposition of sulfate in certain regions exposed to heavy ship traffic. The major ship types show distinctly different contributions in specific locations. For instance, the container fleet contributes 50% of the sulfate decline on the west coast of North America. The global radiative forcing from a 1 yr emission equal to the difference between baseline and reduction inventory shows an initial strong positive forcing from non-CO2 compounds. This warming effect is due to reduced cooling by aerosols and methane. After approximately 25 yr, the non-CO2 forcing is balanced by the CO2 forcing. For the global mean temperature change, we find a shift from warming to cooling after approximately 60 yr. The major ship types show significant differences in the short-term radiative forcing. For instance, the direct SO4 forcing from tankers is 30% higher than for container and bulk. The net long-term effects on RF are similar due to similar CO2 forcing. We assess an emission scenario where the reduction inventory is sustained on the fleet as it steadily diminishes over time due to scrapping and disappears in 2040. We find a net temperature increase lasting until approximately 2080. We conclude that changes in non-CO2 emission does matter significantly if reductions of CO2 emissions are made on the year 2010 cargo shipping fleet. In sum, we find that emission changes motivated by CO2 reductions in shipping will be beneficial from a long-term climate perspective, and that there are positive environmental and health effects identified as concentrations of key short-lived pollutants are reduced.

We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5–20 ppb) in the Southern Hemisphere (SH) and modest high bias (5–10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005–2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120 mW m−2 OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39 ± 41 m Wm−2 relative to TES data. We show that there is a correlation (R2 = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750–2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100 m Wm−2. Removing these models leads to a mean ozone radiative forcing of 394 ± 42 m Wm−2. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 ± 60 m Wm−2 derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.

The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) examined the short-lived drivers of climate change in current climate models. Here we evaluate the 10 ACCMIP models that included aerosols, 8 of which also participated in the Coupled Model Intercomparison Project phase 5 (CMIP5). The models reproduce present-day total aerosol optical depth (AOD) relatively well, though many are biased low. Contributions from individual aerosol components are quite different, however, and most models underestimate east Asian AOD. The models capture most 1980–2000 AOD trends well, but underpredict increases over the Yellow/Eastern Sea. They strongly underestimate absorbing AOD in many regions. We examine both the direct radiative forcing (RF) and the forcing including rapid adjustments (effective radiative forcing; ERF, including direct and indirect effects). The models' all-sky 1850 to 2000 global mean annual average total aerosol RF is (mean; range) −0.26 W m−2; −0.06 to −0.49 W m−2. Screening based on model skill in capturing observed AOD yields a best estimate of −0.42 W m−2; −0.33 to −0.50 W m−2, including adjustment for missing aerosol components in some models. Many ACCMIP and CMIP5 models appear to produce substantially smaller aerosol RF than this best estimate. Climate feedbacks contribute substantially (35 to −58%) to modeled historical aerosol RF. The 1850 to 2000 aerosol ERF is −1.17 W m−2; −0.71 to −1.44 W m−2. Thus adjustments, including clouds, typically cause greater forcing than direct RF. Despite this, the multi-model spread relative to the mean is typically the same for ERF as it is for RF, or even smaller, over areas with substantial forcing. The largest 1850 to 2000 negative aerosol RF and ERF values are over and near Europe, south and east Asia and North America. ERF, however, is positive over the Sahara, the Karakoram, high Southern latitudes and especially the Arctic. Global aerosol RF peaks in most models around 1980, declining thereafter with only weak sensitivity to the Representative Concentration Pathway (RCP). One model, however, projects approximately stable RF levels, while two show increasingly negative RF due to nitrate (not included in most models). Aerosol ERF, in contrast, becomes more negative during 1980 to 2000. During this period, increased Asian emissions appear to have a larger impact on aerosol ERF than European and North American decreases due to their being upwind of the large, relatively pristine Pacific Ocean. There is no clear relationship between historical aerosol ERF and climate sensitivity in the CMIP5 subset of ACCMIP models. In the ACCMIP/CMIP5 models, historical aerosol ERF of about −0.8 to −1.5 W m−2 is most consistent with observed historical warming. Aerosol ERF masks a large portion of greenhouse forcing during the late 20th and early 21st century at the global scale. Regionally, aerosol ERF is so large that net forcing is negative over most industrialized and biomass burning regions through 1980, but remains strongly negative only over east and southeast Asia by 2000. Net forcing is strongly positive by 1980 over most deserts, the Arctic, Australia, and most tropical oceans. Both the magnitude of and area covered by positive forcing expand steadily thereafter.

As part of the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), we evaluate the historical black carbon (BC) aerosols simulated by 8 ACCMIP models against observations including 12 ice core records, long-term surface mass concentrations, and recent Arctic BC snowpack measurements. We also estimate BC albedo forcing by performing additional simulations using offline models with prescribed meteorology from 1996–2000. We evaluate the vertical profile of BC snow concentrations from these offline simulations using the recent BC snowpack measurements. Despite using the same BC emissions, the global BC burden differs by approximately a factor of 3 among models due to differences in aerosol removal parameterizations and simulated meteorology: 34 Gg to 103 Gg in 1850 and 82 Gg to 315 Gg in 2000. However, the global BC burden from preindustrial to present-day increases by 2.5–3 times with little variation among models, roughly matching the 2.5-fold increase in total BC emissions during the same period. We find a large divergence among models at both Northern Hemisphere (NH) and Southern Hemisphere (SH) high latitude regions for BC burden and at SH high latitude regions for deposition fluxes. The ACCMIP simulations match the observed BC surface mass concentrations well in Europe and North America except at Ispra. However, the models fail to predict the Arctic BC seasonality due to severe underestimations during winter and spring. The simulated vertically resolved BC snow concentrations are, on average, within a factor of 2–3 of the BC snowpack measurements except for Greenland and the Arctic Ocean. For the ice core evaluation, models tend to adequately capture both the observed temporal trends and the magnitudes at Greenland sites. However, models fail to predict the decreasing trend of BC depositions/ice core concentrations from the 1950s to the 1970s in most Tibetan Plateau ice cores. The distinct temporal trend at the Tibetan Plateau ice cores indicates a strong influence from Western Europe, but the modeled BC increases in that period are consistent with the emission changes in Eastern Europe, the Middle East, South and East Asia. At the Alps site, the simulated BC suggests a strong influence from Europe, which agrees with the Alps ice core observations. At Zuoqiupu on the Tibetan Plateau, models successfully simulate the higher BC concentrations observed during the non-monsoon season compared to the monsoon season but overpredict BC in both seasons. Despite a large divergence in BC deposition at two Antarctic ice core sites, some models with a BC lifetime of less than 7 days are able to capture the observed concentrations. In 2000 relative to 1850, globally and annually averaged BC surface albedo forcing from the offline simulations ranges from 0.014 to 0.019 W m−2 among the ACCMIP models. Comparing offline and online BC albedo forcings computed by some of the same models, we find that the global annual mean can vary by up to a factor of two because of different aerosol models or different BC-snow parameterizations and snow cover. The spatial distributions of the offline BC albedo forcing in 2000 show especially high BC forcing (i.e., over 0.1 W m−2) over Manchuria, Karakoram, and most of the Former USSR. Models predict the highest global annual mean BC forcing in 1980 rather than 2000, mostly driven by the high fossil fuel and biofuel emissions in the Former USSR in 1980.

The impact of black carbon (BC) aerosols on the global radiation balance is not well constrained. Here twelve global aerosol models are used to show that at least 20% of the present uncertainty in modeled BC direct radiative forcing (RF) is due to diversity in the simulated vertical profile of BC mass. Results are from phases 1 and 2 of the global aerosol model intercomparison project (AeroCom). Additionally, a significant fraction of the variability is shown to come from high altitudes, as, globally, more than 40% of the total BC RF is exerted above 5 km. BC emission regions and areas with transported BC are found to have differing characteristics. These insights into the importance of the vertical profile of BC lead us to suggest that observational studies are needed to better characterize the global distribution of BC, including in the upper troposphere.

Ozone (O3) from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has been used to calculate tropospheric ozone radiative forcings (RFs). All models applied a common set of anthropogenic emissions, which are better constrained for the present-day than the past. Future anthropogenic emissions follow the four Representative Concentration Pathway (RCP) scenarios, which define a relatively narrow range of possible air pollution emissions. We calculate a value for the pre-industrial (1750) to present-day (2010) tropospheric ozone RF of 410 mW m−2. The model range of pre-industrial to present-day changes in O3 produces a spread (±1 standard deviation) in RFs of ±17%. Three different radiation schemes were used – we find differences in RFs between schemes (for the same ozone fields) of ±10%. Applying two different tropopause definitions gives differences in RFs of ±3%. Given additional (unquantified) uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of ±30% for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (44±12%), nitrogen oxides (31 ± 9%), carbon monoxide (15 ± 3%) and non-methane volatile organic compounds (9 ± 2%); earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 42 mW m−2 DU−1, a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (mW m−2; relative to 1750) for the four future scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) of 350, 420, 370 and 460 (in 2030), and 200, 300, 280 and 600 (in 2100). Models show some coherent responses of ozone to climate change: decreases in the tropical lower troposphere, associated with increases in water vapour; and increases in the sub-tropical to mid-latitude upper troposphere, associated with increases in lightning and stratosphere-to-troposphere transport. Climate change has relatively small impacts on global mean tropospheric ozone RF.