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Land surface changes can have substantial impacts on biosphere–atmosphere interactions. In South America, rainforests abundantly emit biogenic volatile organic compounds (BVOCs), which, when coupled with pyrogenic emissions from deforestation fires, can have substantial impacts on regional air quality. We use novel and long-term satellite records of five trace gases, namely isoprene (C 5 H 8), formaldehyde (HCHO), methanol (CH 3 OH), carbon monoxide (CO), and nitrogen dioxide (NO 2), in addition to aerosol optical depth (AOD), vegetation (land cover and leaf area index), and burned area. We characterise the impacts of biogenic and pyrogenic emissions on atmospheric composition for the period 2001 to 2019 in the southern Amazon, a region of substantial deforestation. The seasonal cycle for all of the atmospheric constituents peaks in the dry season (August–October), and the year-to-year variability in CO, HCHO, NO 2 , and AOD is strongly linked to the burned area. We find a robust relationship between the broadleaf forest cover and total column C 5 H 8 (R2 = 0.59), while the burned area exhibits an approximate fifth root power law relationship with tropospheric column NO 2 (R2 = 0.32) in the dry season. Vegetation and burned area together show a relationship with HCHO (R2 = 0.23). Wet-season AOD and CO follow the forest cover distribution. The land surface variables are very weakly correlated with CH 3 OH, suggesting that other factors drive its spatial distribution. Overall, we provide a detailed observational quantification of biospheric process influences on southern Amazon regional atmospheric composition, which in future studies can be used to help constrain the underpinning processes in Earth system models. [ABSTRACT FROM AUTHOR]

Ozone is a potent air pollutant in the lower troposphere and an important short-lived climate forcer (SLCF) in the upper troposphere. Studies investigating long-term trends in the tropospheric column ozone (TCO 3) have shown large-scale spatio-temporal inconsistencies. Here, we investigate the long-term trends in lower-tropospheric column ozone (LTCO 3 , surface–450 hPa sub-column) by exploiting a synergy of satellite and ozonesonde data sets and an Earth system model (UK's Earth System Model, UKESM) over North America, Europe, and East Asia for the decade 2008–2017. Overall, we typically find small LTCO 3 linear trends with large uncertainty ranges using the Ozone Monitoring Instrument (OMI) and the Infrared Atmospheric Sounding Interferometer (IASI), while model simulations indicate a stable LTCO 3 tendency. The satellite a priori data sets show negligible trends, indicating that any year-to-year changes in the spatio-temporal sampling of these satellite data sets over the period concerned have not artificially influenced their LTCO 3 temporal evolution. The application of the satellite averaging kernels (AKs) to the UKESM simulated ozone profiles, accounting for the satellite vertical sensitivity and allowing for like-for-like comparisons, has a limited impact on the modelled LTCO 3 tendency in most cases. While, in relative terms, this is more substantial (e.g. on the order of 100 %), the absolute magnitudes of the model trends show negligible change. However, as the model has a near-zero tendency, artificial trends were imposed on the model time series (i.e. LTCO 3 values rearranged from smallest to largest) to test the influence of the AKs, but simulated LTCO 3 trends remained small. Therefore, the LTCO 3 tendencies between 2008 and 2017 in northern-hemispheric regions are likely to be small, with large uncertainties, and it is difficult to detect any small underlying linear trends due to interannual variability or other factors which require further investigation (e.g. the radiative transfer scheme (RTS) used and/or the inputs (e.g. meteorological fields) used in the RTS). [ABSTRACT FROM AUTHOR]

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

Ozone is a potent air pollutant in the lower troposphere and an important short-lived climate forcer (SLCF) in the upper troposphere. Studies investigating long-term trends in tropospheric column ozone (TCO3) have shown large-scale spatiotemporal inconsistencies. Here, we investigate the long-term trends in lower tropospheric column ozone (LTCO3, surface-450 hPa sub-column) by exploiting a synergy of satellite and ozonesonde datasets and an Earth System Model (UKESM) over North America, Europe and East Asia for the decade 2008-2017. Overall, we typically find small LTCO3 linear trends with large uncertainty ranges from the Ozone Monitoring Instrument (OMI) and the Infrared Atmospheric Sounding Interferometer (IASI), while model simulations indicate a stable LTCO3 tendency. Trends in the satellite a priori datasets show negligible trends indicating year-to-year sampling is not an issue. The application of the satellite averaging kernels AKs) to the UKESM ozone profiles, accounting for the satellite vertical sensitivity and allowing for like-for41 like comparisons, has a limited impact on the modelled LTCO3 tendency in most cases. While, in relative terms, this is more substantial (e.g. in the order of 100%), the absolute magnitudes of the model trends show negligible change. However, as the model has a near-zero tendency, artificial trends were imposed on the model time-series (i.e. LTCO3 values rearranged from smallest to largest) to test the influence of the AKs but simulated LTCO3 trends remained small. Therefore, the LTCO3 tendency between 2008 and 2017 in northern hemispheric regions are likely small, with large uncertainties, and it is difficult to detect any small underlying linear trends due to inter-annual variability or other factors which require further investigation. [ABSTRACT FROM AUTHOR]

Ozone is a potent air pollutant in the lower troposphere and an important short-lived climate forcer (SLCF) in the upper troposphere. Studies investigating long-term trends in tropospheric column ozone (TCO3) have shown large-scale spatiotemporal inconsistencies. Here, we investigate the long-term trends in lower tropospheric column ozone (LTCO3, surface-450 hPa sub-column) by exploiting a synergy of satellite and ozonesonde datasets and an Earth System Model (UKESM) over North America, Europe and East Asia for the decade 2008–2017. Overall, we typically find small LTCO3 linear trends with large uncertainty ranges from the Ozone Monitoring Instrument (OMI) and the Infrared Atmospheric Sounding Interferometer (IASI), while model simulations indicate a stable LTCO3 tendency. Trends in the satellite a priori datasets show negligible trends indicating year-to-year sampling is not an issue. The application of the satellite averaging kernels (AKs) to the UKESM ozone profiles, accounting for the satellite vertical sensitivity and allowing for like-for-like comparisons, has a limited impact on the modelled LTCO3 tendency in most cases. While, in relative terms, this is more substantial (e.g. in the order of 100 %), the absolute magnitudes of the model trends show negligible change. However, as the model has a near-zero tendency, artificial trends were imposed on the model time-series (i.e. LTCO3 values rearranged from smallest to largest) to test the influence of the AKs but simulated LTCO3 trends remained small. Therefore, the LTCO3 tendency between 2008 and 2017 in northern hemispheric regions are likely small, with large uncertainties, and it is difficult to detect any small underlying linear trends due to inter-annual variability or other factors which require further investigation. [ABSTRACT FROM AUTHOR]

Net-zero emission policies principally target climate change but may have a profound influence on surface ozone pollution. To investigate this, we use a chemistry–climate model to simulate surface ozone changes in China under a net-zero pathway and examine the different drivers that govern these changes. We find large monthly mean surface ozone decreases of up to 16 ppb in summer and small ozone decreases of 1 ppb in winter. Local emissions are shown to have the largest influence on future ozone changes, outweighing the effects of changes in emissions outside China, changes in global methane concentrations, and a warmer climate. Impacts of local and external emissions show strong seasonality, with the largest contributions to surface ozone in summer, while changes in global methane concentrations have a more uniform effect throughout the year. We find that while a warmer climate has a minor impact on ozone change compared to the net-zero scenario, it will alter the spatial patterns of ozone in China, leading to ozone increases in the south and ozone decreases in the north. We also apply a deep learning model to correct biases in our ozone simulations and to provide a more robust assessment of ozone changes. We find that emission controls may lead to a surface ozone decrease of 5 ppb in summer. The number of days with high-ozone episodes with daily mean ozone greater than 50 ppb will be reduced by 65 % on average. This is smaller than that simulated with the chemistry–climate model, reflecting overestimated ozone formation under present-day conditions. Nevertheless, this assessment clearly shows that the strict emission policies needed to reach net zero will have a major benefit in reducing surface ozone pollution and the occurrence of high-ozone episodes, particularly in high-emission regions in China. [ABSTRACT FROM AUTHOR]

Hydrogen is expected to play a key role in the global energy transition to net zero emissions in many scenarios. However, fugitive emissions of hydrogen into the atmosphere during its production, storage, distribution and use could reduce the climate benefit and also have implications for air quality. Here, we explore the atmospheric composition and climate impacts of increases in atmospheric hydrogen abundance using the UK Earth System Model (UKESM1) chemistry–climate model. Increases in hydrogen result in increases in methane, tropospheric ozone and stratospheric water vapour, resulting in a positive radiative forcing. However, some of the impacts of hydrogen leakage are partially offset by potential reductions in emissions of methane, carbon monoxide, nitrogen oxides and volatile organic compounds from the consumption of fossil fuels. We derive a refined methodology for determining indirect global warming potentials (GWPs) from parameters derived from steady-state simulations, which is applicable to both shorter-lived species and those with intermediate and longer lifetimes, such as hydrogen. Using this methodology, we determine a 100-year global warming potential for hydrogen of 12 ± 6. Based on this GWP and hydrogen leakage rates of 1 % and 10 %, we find that hydrogen leakage offsets approximately 0.4 % and 4 % respectively of total equivalent CO 2 emission reductions in our global hydrogen economy scenario. To maximise the benefit of hydrogen as an energy source, emissions associated with hydrogen leakage and emissions of the ozone precursor gases need to be minimised. [ABSTRACT FROM AUTHOR]

Humans can act as fire starters or suppressors, changing fire regimes by increasing the number of ignitions, changing their timing, and altering fuel structure and abundance, which can be considered a human--environmental coupling. Considering the human influences on fire activity, representing socio-economic impacts on fires in global fire models is crucial to underpin the confidence in these modelling frameworks. In this work we implement a socio-economic factor in the fire ignition and suppression parametrisation in INFERNO based on a Human Development Index (HDI). HDI captures human development's income, health, and education dimensions leading to a representation where if there is more effort to improve human development, the population also invests in higher fire suppression. Including this representation of socio-economic factors in INFERNO reduces the annual mean burnt area (between 1997 - 2016) positive biases found in Temperate North America, Central America, Europe and Southern Hemisphere South America, by more than 100 % without statistically significant impact to other areas. In addition, it improves the representation of the burnt area trends, especially in Africa. Central Asia and Australia where observations show negative trends. Including socio-economic impacts on fire based on HDI in INFERNO provides a simple and linear representation of these effects on fire ignition and suppression, leading to an improvement of the model performance, especially in developed regions, These impacts are especially relevant to understand future climate regimes and inform policymakers on effects of fire policy in a changing climate. [ABSTRACT FROM AUTHOR]

Elevated surface concentrations of ozone and fine particulate matter (PM2.5) can lead to poor air quality and detrimental impacts on human health. These pollutants are also termed Near‐Term Climate Forcers (NTCFs) as they can also influence the Earth's radiative balance on timescales shorter than long‐lived greenhouse gases. Here we use the Earth system model, UKESM1, to simulate the change in surface ozone and PM2.5 concentrations from different NTCF mitigation scenarios, conducted as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). These are then combined with relative risk estimates and projected changes in population demographics, to estimate the mortality burden attributable to long‐term exposure to ambient air pollution. Scenarios that involve the strong mitigation of air pollutant emissions yield large future benefits to human health (25%), particularly across Asia for black carbon (7%), when compared to the future reference pathway. However, if anthropogenic emissions follow the reference pathway, then impacts to human health worsen over South Asia in the short term (11%) and across Africa (20%) in the longer term. Future climate change impacts on air pollutants can offset some of the health benefits achieved by emission mitigation measures over Europe for PM2.5 and East Asia for ozone. In addition, differences in the future chemical environment over regions are important considerations for mitigation measures to achieve the largest benefit to human health. Future policy measures to mitigate climate warming need to also consider the impact on air quality and human health across different regions to achieve the maximum co‐benefits. Plain Language Summary: Ground level ozone (O3) and fine particulate matter (PM2.5) are two major air pollutants that are associated with adverse effects to human health. In addition, changes in their atmospheric concentrations can also influence the rate of climate change on a timeframe shorter than that for long‐lived greenhouse gases. In this study we use a global Earth system model to simulate the change in concentrations of surface O3 and PM2.5 across numerous future mitigation scenarios, which are then used to quantify the impact on the air pollution health burden. A large reduction in the air pollutant health burden of the population, particularly across Asia, is calculated in scenarios that have large reductions in air pollutant sources. However, impacts on health can increase across large parts of Africa in a scenario where emissions of air pollutants are not reduced. Future climate warming increases the exposure to air pollutants across regions such as Europe and East Asia, with a detrimental impact on human health. Measures to limit future climate warming and improve regional air pollutant health burdens are interconnected and important to consider together when designing future policies. Key Points: Strong mitigation of aerosols and ozone precursors leads to large future benefits to the air pollution health burden, particularly over AsiaFuture climate change can offset the health benefits of a reduced air pollution health burden from emissions mitigation over Europe and East AsiaIt is important to consider future chemical environments when designing measures to maximize benefits to climate, air quality, and health [ABSTRACT FROM AUTHOR]

Net Zero emission policies principally target climate change, but may have a profound influence on surface ozone pollution. To investigate this, we use a chemistry-climate model to simulate surface ozone changes in China under a Net Zero pathway, and examine the different drivers that govern these changes. We find large monthly mean surface ozone decreases of up to 16 ppb in summer and small ozone decreases of 1 ppb in winter. Local emissions are shown to have the largest influence on future ozone changes, outweighing the effects of changes in emissions outside China, changes in global methane concentrations and a warmer climate. Impacts of local and external emissions show strong seasonality, with the largest contributions to surface ozone in summer, while changes in global methane concentrations have a more uniform effect throughout the year. We find that while a warmer climate has a minor impact on ozone change compared to the Net Zero scenario, it will alter the spatial patterns of ozone in China, leading to ozone increases in the south and ozone decreases in the north. We also apply a deep learning model to correct biases in our ozone simulations, and to provide a more robust assessment of ozone changes. We find that emission controls may lead to a surface ozone decrease of 5 ppb in summer. This is smaller than that simulated with the chemistry-climate model, reflecting overestimated ozone formation under present-day conditions. Nevertheless, this assessment clearly shows that the strict emission policies needed to reach Net Zero will have a major benefit in reducing surface ozone pollution and the occurrence of high ozone episodes, particularly in high-emission regions in China. [ABSTRACT FROM AUTHOR]

The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood and diversity in climate model experiments persists as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article synthesizes current challenges and emphasizes opportunities for advancing our understanding of climate change and model diversity. The perspective of this article is based on expert views from three multi-model intercomparison projects (MIPs) - the Precipitation Driver Response MIP (PDRMIP), the Aerosol and Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specialisms across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation-response paradigm through multi-model ensembles of Earth System Models of varying complexity. It specifically facilitated contributions to the research field through sharing knowledge on best practices for the design of model diagnostics and experimental strategies across MIP boundaries, e.g., for estimating effective radiative forcing. We discuss the challenges of gaining insights from highly complex models that have specific biases and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible, and machine learning approaches for faster and better sub-grid scale parameterizations where they are needed. Both would improve our ability to adopt a smart experimental design with an optimal tradeoff between resolution, complexity and simulation length. Future experiments can be evaluated and improved with sophisticated methods that leverage multiple observational datasets, and thereby, help to advance the understanding of climate change and its impacts. [ABSTRACT FROM AUTHOR]

We use the United Kingdom Earth System Model, UKESM1, to investigate the influence of the winter large-scale circulation on daily concentrations of PM 2.5 (particulate matter with an aerodynamic diameter of 2.5 µ m or less) and their sensitivity to emissions over major populated regions of China over the period 1999–2019. We focus on the Yangtze River delta (YRD), where weak flow of cold, dry air from the north and weak inflow of maritime air are particularly conducive to air pollution. These provide favourable conditions for the accumulation of local pollution but limit the transport of air pollutants into the region from the north. Based on the dominant large-scale circulation, we construct a new index using the north–south pressure gradient and apply it to characterise PM 2.5 concentrations over the region. We show that this index can effectively distinguish different levels of pollution over YRD and explain changes in PM 2.5 sensitivity to emissions from local and surrounding regions. We then project future changes in PM 2.5 concentrations using this index and find an increase in PM 2.5 concentrations over the region due to climate change that is likely to partially offset the effect of emission control measures in the near-term future. To benefit from future emission reductions, more stringent emission controls are required to offset the effects of climate change. [ABSTRACT FROM AUTHOR]

Using nine chemistry‐climate and eight associated no‐chemistry models, we investigate the persistence and timing of cold episodes occurring in the Arctic and Antarctic stratosphere during the period 1980–2014. We find systematic differences in behavior between members of these model pairs. In a first group of chemistry models whose dynamical configurations mirror their no‐chemistry counterparts, we find an increased persistence of such cold polar vortices, such that these cold episodes often start earlier and last longer, relative to the times of occurrence of the lowest temperatures. Also the date of occurrence of the lowest temperatures, both in the Arctic and the Antarctic, is often delayed by 1–3 weeks in chemistry models, versus their no‐chemistry counterparts. This behavior exacerbates a widespread problem occurring in most or all models, a delayed occurrence, in the median, of the most anomalously cold day during such cold winters. In a second group of model pairs there are differences beyond just ozone chemistry. In particular, here the chemistry models feature more levels in the stratosphere, a raised model top, and differences in non‐orographic gravity wave drag versus their no‐chemistry counterparts. Such additional dynamical differences can completely mask the above influence of ozone chemistry. The results point toward a need to retune chemistry‐climate models versus their no‐chemistry counterparts. Plain Language Summary: Ozone is a chemical constituent of the atmosphere acting as an absorber of both solar ultraviolet light and infrared radiation emitted by the Earth. It therefore needs to be considered in climate models. Explicit ozone chemistry is a computationally challenging addition to a climate model; hence in most cases ozone is simply prescribed. Especially during relatively cold stratospheric winter/spring seasons, Antarctic and Arctic ozone depletion can be considerable. Such anomalous ozone loss is not reflected in the imposed ozone field, and hence differences in behavior are expected for such situations between chemistry‐ and no‐chemistry models. Indeed for such cold winters/springs, we find an enhanced persistence of such cold spells in a set of chemistry‐climate models, versus their no‐chemistry counterparts; such enhanced persistence generally makes the chemistry model less realistic than its no‐chemistry counterpart. However, if there are substantial further differences between the members of these model pairs, such as regarding their grid configuration or physical processes beyond chemistry, these can obscure the effect of ozone chemistry. We thus claim that adding stratospheric ozone chemistry to a climate model necessitates retuning to counteract a deterioration of the simulated stratospheric climate that can otherwise occur. Key Points: Coupling in ozone chemistry causes an increase in persistence of low temperature anomalies over both polesIn the Antarctic, coupling in chemistry amplifies pre‐existing stratospheric cold biasesThese effects can be masked by other dynamical differences present in some models [ABSTRACT FROM AUTHOR]

We use the United Kingdom Earth System Model, UKESM1, to investigate the influence of the winter large-scale circulation on daily concentrations of PM2.5 (particulate matter with an aerodynamic diameter of 2.5 μm or less) and their sensitivity to emissions over major populated regions of China over the period 1999--2019. We focus on the Yangtze River Delta (YRD), where weak flow of cold, dry air from the north and weak inflow of maritime air are particularly conducive to air pollution. These provide favourable conditions for the accumulation of local pollution but limit the transport of air pollutants into the region from the north. Based on the dominant large-scale circulation, we construct a new index using the north-south pressure gradient and apply it to characterize PM2.5 concentrations over the region. We show that this index can effectively distinguish different levels of pollution over YRD and explain changes in PM2.5 sensitivity to emissions from local and surrounding regions. We then project future changes in PM2.5 concentrations using this index and find an increase in PM2.5 concentrations over the region due to climate change that is likely to partially offset the effect of emission control measures in the near-term future. To benefit from future emission reductions, more stringent emission controls are required to offset the effects of climate change. [ABSTRACT FROM AUTHOR]

The Year 1850 to 2014 increase in methane from 808 to 1831 ppb leads to an effective radiative forcing (ERF) of 0.97 ± 0.04 W m−2 in the United Kingdom's Earth System Model, UKESM1. The direct methane contribution is 0.54 ± 0.04 W m−2. It is better represented in UKESM1 than in its predecessor model HadGEM2 due to shortwave and longwave absorption improvements and the absence of an anomalous dust response in the UKESM1 simulations. An indirect ozone ERF of 0.13–0.20 W m−2 is due to the tropospheric ozone increase outweighing that of the stratospheric decrease. The indirect water vapor ERF of 0.02–0.07 W m−2 is consistent with previous estimates. The methane increase also leads to a cloud radiative effect of 0.12 ± 0.02 W m−2 from thermodynamic adjustments and aerosol‐cloud interactions (aci). Shortwave and longwave contributions of 0.23 and −0.35 W m−2 to the cloud forcing arise from radiative heating and stabilization of the upper troposphere, reducing convection and global cloud cover. The aerosol‐mediated contribution (0.28–0.30 W m−2) is due to changes in oxidants reducing new particle formation (−8%), shifting the aerosol size distribution toward fewer but larger particles. Cloud droplet number concentration decreases and cloud droplet effective radius increases. This reduction in the Twomey effect switches the cloud forcing sign (−0.14 to 0.12 W m−2) and is due to chemistry‐aerosol‐cloud coupling in UKESM1. Despite uncertainties in rapid adjustments and process representation in models, these results highlight the potential importance of chemistry‐aerosol‐cloud interactions and dynamical adjustments in climate forcing. Plain Language Summary: Methane is the second most important greenhouse gas after carbon dioxide. Methane is also chemically reactive in the atmosphere, and can cause changes in ozone, which is also a greenhouse gas. Methane can also affect the amount of water vapor (WV) in the atmosphere, where it too acts as a greenhouse gas. Aerosols, formed in the atmosphere through chemical processing, are also affected by methane. This study quantifies the impact of changes in methane concentration since the pre‐industrial period on the Earth's energy budget at the present day and examines the impact from methane itself, as well as the impact from the additional methane‐driven changes in ozone, WV, aerosols, and clouds. The biggest impact (∼55%) is from methane itself, and of the remaining impact on the Earth's energy budget from methane, most can be attributed to ozone and clouds. The contribution from clouds is partly driven by changes in aerosol properties and partly driven by heating and a reduction in cloud cover. The impact from WV is small and is consistent with previous estimates. This study highlights the potential importance of including chemistry‐aerosol‐cloud interactions when quantifying the effect of pre‐industrial to present‐day changes in atmospheric constituents on climate. Key Points: The direct radiative effect of methane in UKESM1 is consistent with line‐by‐line radiative transfer calculationsThe total methane effective radiative forcing (ERF) in UKESM1 includes an aerosol‐mediated cloud forcing due to changes in cloud activationThe ERF also includes a dynamically driven cloud forcing from tropospheric warming and a reduction in cloud fraction [ABSTRACT FROM AUTHOR]

Weaknesses in process representation in chemistry–climate models lead to biases in simulating surface ozone and to uncertainty in projections of future ozone change. We here develop a deep learning model to demonstrate the feasibility of ozone bias correction in a global chemistry–climate model. We apply this approach to identify the key factors causing ozone biases and to correct projections of future surface ozone. Temperature and the related geographic variables latitude and month show the strongest relationship with ozone biases. This indicates that ozone biases are sensitive to temperature and suggests weaknesses in representation of temperature-sensitive physical or chemical processes. Photolysis rates are also an important factor, highlighting the sensitivity of biases to simulated cloud cover and insolation. Atmospheric chemical species such as the hydroxyl radical, nitric acid and peroxyacyl nitrate show strong positive relationships with ozone biases on a regional scale. These relationships reveal the conditions under which ozone biases occur, although they reflect association rather than direct causation. We correct model projections of future ozone under different climate and emission scenarios following the shared socio-economic pathways. We find that changes in seasonal ozone mixing ratios from the present day to the future are generally smaller than those simulated without bias correction, especially in high-emission regions. This suggests that the ozone sensitivity to changing emissions and climate may be overestimated with chemistry–climate models. Given the uncertainty in simulating future ozone, we show that deep learning approaches can provide improved assessment of the impacts of climate and emission changes on future air quality, along with valuable information to guide future model development. [ABSTRACT FROM AUTHOR]

Climate change has the potential to increase surface ozone (O3) concentrations, known as the "ozone–climate penalty", through changes to atmospheric chemistry, transport and dry deposition. In the tropics, the response of surface O3 to changing climate is relatively understudied but has important consequences for air pollution and human and ecosystem health. In this study, we evaluate the change in surface O3 due to climate change over South America and Africa using three state-of-the-art Earth system models that follow the Shared Socioeconomic Pathway 3-7.0 emission scenario from CMIP6. In order to quantify changes due to climate change alone, we evaluate the difference between simulations including climate change and simulations with a fixed present-day climate. We find that by 2100, models predict an ozone–climate penalty in areas where O3 is already predicted to be high due to the impacts of precursor emissions, namely urban and biomass burning areas, although on average, models predict a decrease in surface O3 due to climate change. We identify a small but robust positive trend in annual mean surface O3 over polluted areas. Additionally, during biomass burning seasons, seasonal mean O3 concentrations increase by 15 ppb (model range 12 to 18 ppb) in areas with substantial biomass burning such as the arc of deforestation in the Amazon. The ozone–climate penalty in polluted areas is shown to be driven by an increased rate of O3 chemical production, which is strongly influenced by NOx concentrations and is therefore specific to the emission pathway chosen. Multiple linear regression finds the change in NOx concentration to be a strong predictor of the change in O3 production, whereas increased isoprene emission rate is positively correlated with increased O3 destruction, suggesting NOx -limited conditions over the majority of tropical Africa and South America. However, models disagree on the role of climate change in remote, low- NOx regions, partly because of significant differences in NOx concentrations produced by each model. We also find that the magnitude and location of the ozone–climate penalty in the Congo Basin has greater inter-model variation than that in the Amazon, so further model development and validation are needed to constrain the response in central Africa. We conclude that if the climate were to change according to the emission scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of high O3 exposure, irrespective of any direct impacts on O3 via the prescribed emission scenario. [ABSTRACT FROM AUTHOR]

We quantify the impacts of halogenated ozone‐depleting substances (ODSs), greenhouse gases (GHGs), and short‐lived ozone precursors on ozone changes between 1850 and 2014 using single‐forcing perturbation simulations from several Earth system models with interactive chemistry participating in the Coupled Model Intercomparison Project Aerosol and Chemistry Model Intercomparison Project. We present the responses of ozone to individual forcings and an attribution of changes in ozone columns and vertically resolved stratospheric and tropospheric ozone to these forcings. We find that whilst substantial ODS‐induced ozone loss dominates the stratospheric ozone changes since the 1970s, in agreement with previous studies, increases in tropospheric ozone due to increases in short‐lived ozone precursors and methane since the 1950s make increasingly important contributions to total column ozone (TCO) changes. Increases in methane also lead to substantial extra‐tropical stratospheric ozone increases. Impacts of nitrous oxide and carbon dioxide on stratospheric ozone are significant but their impacts on TCO are small overall due to several opposing factors and are also associated with large dynamical variability. The multi‐model mean (MMM) results show a clear change in the stratospheric ozone trends after 2000 due to now declining ODSs, but the trends are generally not significantly positive, except in the extra‐tropical upper stratosphere, due to relatively small changes in forcing over this period combined with large model uncertainty. Although the MMM ozone compares well with the observations, the inter‐model differences are large primarily due to the large differences in the models' representation of ODS‐induced ozone depletion. Plain Language Summary: Overhead ozone absorbs harmful solar ultraviolet light, protecting life on Earth. Due to human activities since the nineteenth century, emissions of greenhouse gases (GHGs) and ozone‐depleting substances (ODSs) containing chlorine and bromine have profoundly affected stratospheric ozone. Near the Earth' surface, ozone has increased substantially leading to worsening air quality. In this study, we use Earth system models to interactively assess the roles of ODSs, ozone‐forming pollutants, and GHGs including methane, carbon dioxide (CO2), and nitrous oxide (N2O) on ozone changes from the surface to the upper stratosphere. Whilst substantial reductions in stratospheric ozone due to ODSs occurred since the 1970s, the lower‐atmospheric ozone increases due to anthropogenic pollution have counteracted this decrease. Increases in GHGs lead to various positive and negative effects on stratospheric ozone in different regions, and their impacts vary with ODS levels in the atmosphere. Amongst the GHGs assessed here, the increase in methane leads to overwhelming positive trends in both stratospheric and tropospheric ozone through mainly chemical effects. The impact of changes in N2O and CO2 on total column ozone is more uncertain due to large inter‐model differences, although their overall impact is small during the simulation period. Key Points: New multi‐model results show significant positive effects of ozone precursors on near‐global ozone offsetting the negative effects of ozone‐depleting substances (ODSs)ODS and greenhouse gases dominate stratospheric ozone changes but with large inter‐model differences due to uncertainties in responses to ODS changesIncreases in carbon dioxide and nitrous oxide significantly impact stratospheric ozone, but their net effects on total columns are small due to cancellations [ABSTRACT FROM AUTHOR]

Near‐term climate forcers (NTCFs) can influence climate via interaction with the Earth's radiative balance and include both aerosols and trace gas constituents of the atmosphere (such as methane and ozone). Two of the principal NTCFs, aerosols (particulate matter) and tropospheric ozone (O3), can also affect local air quality when present in the lower levels of the atmosphere. Previous studies have shown that mitigation of NTCFs has the potential to improve air quality and reduce the rate of surface warming induced by long‐lived greenhouse gases. Here, we assess the combined air quality and climate impacts from changes in NTCFs under numerous different future mitigation scenarios, relative to a future reference scenario, that were conducted by a single Earth system model (UKESM1) as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Co‐benefits to both global air quality and climate are only achieved in the future scenario with strong mitigation measures applied to all NTCFs, particularly aerosols and methane, with penalties identified for inaction. When compared to the combined NTCF mitigation scenario, analysis of individual mitigation scenarios shows that there are important non‐linearities and interactions between NTCFs (e.g., aerosols and clouds). If only aerosol components are mitigated, there are still benefits to air quality but detrimental impacts on climate, particularly at the regional scale. In addition, other changes in future land‐use and climate could have important impacts on regional NTCFs, which should be considered when designing future mitigation measures to anthropogenic emissions. Plain Language Summary: Components of the Earth's lower atmosphere, such as methane, aerosols, and ozone, have an important influence on the rate by which the climate warms in the short‐term (2050s) and are identified as near‐term climate forcers (NTCFs). Elevated concentrations of these components at the surface can also lead to poor air quality and impacts on human health. Therefore, future strategies to reduce these components provide opportunities to benefit both the rate of climate warming and levels of air pollution. Using a global Earth system model, we simulate the combined impact on future climate and air quality from numerous different ways to reduce NTCFs. We show that the largest benefit to both future climate and air quality is achieved by reducing concentrations of methane and aerosols at the same time. If only aerosols are reduced, then this leads to a benefit to air quality but could accelerate the rate of near‐term warming. However, when reducing NTCFs there are important interactions with the Earth system that need further consideration. Our findings highlight that reducing different NTCFs can have different impacts, particularly regionally, and that measures to benefit both future climate and air quality need to be carefully designed. Key Points: Future changes in Near Term Climate Forcers have important implications for both air quality and climateCombined mitigation of aerosols and methane is required to achieve maximum co‐benefits to both future air quality and climateFuture changes in land‐use and climate also impact the level of mitigation required to anthropogenic sources of near‐term climate forcers [ABSTRACT FROM AUTHOR]

Weaknesses in process representation in chemistry-climate models lead to biases in simulating surface ozone and to uncertainty in projections of future ozone change. We develop a deep learning model to demonstrate the feasibility of ozone bias correction in a global chemistry-climate model. We apply this approach to identify the key factors causing ozone biases and to correct projections of future surface ozone. Temperature and the related geographic variables latitude and month show the strongest relationship with ozone biases. This indicates that ozone biases are sensitive to temperature and suggests weaknesses in representation of temperature-sensitive physical or chemical processes. Photolysis rates are also an important factor highlighting the sensitivity of biases to simulated cloud cover and insolation. Atmospheric chemical species such as the hydroxyl radical, nitric acid and peroxyacyl nitrate show strong positive relationships with ozone biases on a regional scale.We correct model projections of future ozone under different climate and emission scenarios following the shared socio-economic pathways. We find that changes in seasonal ozone mixing ratios from the present day to the future are generally smaller than those simulated without bias correction, especially in high-emission regions. This suggests that the ozone sensitivity to changing emissions and climate may be overestimated with chemistry-climate models. Given the uncertainty in simulating future ozone, we show that deep learning approaches can provide improved assessment of the impacts of climate and emission changes on future air quality, along with valuable information to guide future model development. [ABSTRACT FROM AUTHOR]

Simulations by six Coupled Model Intercomparison Project Phase 6 (CMIP6) Earth system models indicate that the seasonal cycle of baseline tropospheric ozone at northern midlatitudes has been shifting since the mid-20th century. Beginning in ∼ 1940, the magnitude of the seasonal cycle increased by ∼10 ppb (measured from seasonal minimum to maximum), and the seasonal maximum shifted to later in the year by about 3 weeks. This shift maximized in the mid-1980s, followed by a reversal – the seasonal cycle decreased in amplitude and the maximum shifted back to earlier in the year. Similar changes are seen in measurements collected from the 1970s to the present. The timing of the seasonal cycle changes is generally concurrent with the rise and fall of anthropogenic emissions that followed industrialization and the subsequent implementation of air quality emission controls. A quantitative comparison of the temporal changes in the ozone seasonal cycle at sites in both Europe and North America with the temporal changes in ozone precursor emissions across the northern midlatitudes found a high degree of similarity between these two temporal patterns. We hypothesize that changing precursor emissions are responsible for the shift in the ozone seasonal cycle; this is supported by the absence of such seasonal shifts in southern midlatitudes where anthropogenic emissions are much smaller. We also suggest a mechanism by which changing emissions drive the changing seasonal cycle: increasing emissions of NOx allow summertime photochemical production of ozone to become more important than ozone transported from the stratosphere, and increasing volatile organic compounds (VOCs) lead to progressively greater photochemical ozone production in the summer months, thereby increasing the amplitude of the seasonal ozone cycle. Decreasing emissions of both precursor classes then reverse these changes. The quantitative parameter values that characterize the seasonal shifts provide useful benchmarks for evaluating model simulations, both against observations and between models. [ABSTRACT FROM AUTHOR]

Tropospheric ozone is important to future air quality and climate. We investigate ozone changes and ozone sensitivity to changing emissions in the context of climate change from the present day (2004–2014) to the future (2045–2055) under a range of shared socio-economic pathways (SSPs). We apply the United Kingdom Earth System Model, UKESM1, with an extended chemistry scheme including more reactive volatile organic compounds (VOCs) to quantify ozone burdens as well as ozone sensitivities globally and regionally based on nitrogen oxide (NOx) and VOC mixing ratios. We show that the tropospheric ozone burden increases by 4 % under a development pathway with higher NOx and VOC emissions (SSP3-7.0) but decreases by 7 % under the same pathway if NOx and VOC emissions are reduced (SSP3-7.0-lowNTCF) and by 5 % if atmospheric methane (CH4) mixing ratios are reduced (SSP3-7.0-lowCH4). Global mean surface ozone mixing ratios are reduced by 3–5 ppb under SSP3-7.0-lowNTCF and by 2–3 ppb under SSP3-7.0-lowCH4. However, surface ozone changes vary substantially by season in high-emission regions under future pathways, with decreased ozone mixing ratios in summer and increased ozone mixing ratios in winter when NOx emissions are reduced. VOC-limited areas are more extensive in winter (7 %) than in summer (3 %) across the globe. North America, Europe, and East Asia are the dominant VOC-limited regions in the present day, but North America and Europe become more NOx -limited in the future mainly due to reductions in NOx emissions. The impacts of VOC emissions on ozone sensitivity are limited in North America and Europe because reduced anthropogenic VOC emissions are partly offset by higher biogenic VOC emissions. Ozone sensitivity is not greatly influenced by changing CH4 mixing ratios. South Asia becomes the dominant VOC-limited region under future pathways. We highlight that reductions in NOx emissions are required to transform ozone production from VOC to NOx limitation, but that these lead to increased ozone mixing ratios in high-emission regions, and hence emission controls on VOC and CH4 are also necessary. [ABSTRACT FROM AUTHOR]

Atmospheric methane removal (e.g. in situ methane oxidation to carbon dioxide) may be needed to offset continued methane release and limit the global warming contribution of this potent greenhouse gas. Because mitigating most anthropogenic emissions of methane is uncertain this century, and sudden methane releases from the Arctic or elsewhere cannot be excluded, technologies for methane removal or oxidation may be required. Carbon dioxide removal has an increasingly well-established research agenda and technological foundation. No similar framework exists for methane removal. We believe that a research agenda for negative methane emissions—'removal' or atmospheric methane oxidation—is needed. We outline some considerations for such an agenda here, including a proposed Methane Removal Model Intercomparison Project (MR-MIP). This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'. [ABSTRACT FROM AUTHOR]

Fire constitutes a key process in the Earth system (ES), being driven by climate as well as affecting the climate by changing atmospheric composition and impacting the terrestrial carbon cycle. However, studies on the effects of fires on atmospheric composition, radiative forcing and climate have been limited to date, as the current generation of ES models (ESMs) does not include fully atmosphere–composition–vegetation coupled fires feedbacks. The aim of this work is to develop and evaluate a fully coupled fire–composition–climate ES model. For this, the INteractive Fires and Emissions algoRithm for Natural envirOnments (INFERNO) fire model is coupled to the atmosphere-only configuration of the UK's Earth System Model (UKESM1). This fire–atmosphere interaction through atmospheric chemistry and aerosols allows for fire emissions to influence radiation, clouds and generally weather, which can consequently influence the meteorological drivers of fire. Additionally, INFERNO is updated based on recent developments in the literature to improve the representation of human and/or economic factors in the anthropogenic ignition and suppression of fire. This work presents an assessment of the effects of interactive fire coupling on atmospheric composition and climate compared to the standard UKESM1 configuration that uses prescribed fire emissions. Results show a similar performance when using the fire–atmosphere coupling (the "online" version of the model) when compared to the offline UKESM1 that uses prescribed fire. The model can reproduce observed present-day global fire emissions of carbon monoxide (CO) and aerosols, despite underestimating the global average burnt area. However, at a regional scale, there is an overestimation of fire emissions over Africa due to the misrepresentation of the underlying vegetation types and an underestimation over equatorial Asia due to a lack of representation of peat fires. Despite this, comparing model results with observations of CO column mixing ratio and aerosol optical depth (AOD) show that the fire–atmosphere coupled configuration has a similar performance when compared to UKESM1. In fact, including the interactive biomass burning emissions improves the interannual CO atmospheric column variability and consequently its seasonality over the main biomass burning regions – Africa and South America. Similarly, for aerosols, the AOD results broadly agree with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations. [ABSTRACT FROM AUTHOR]

Simulations by six CMIP6 Earth System Models indicate that the seasonal cycle of baseline tropospheric ozone at northern midlatitudes has been shifting since the mid-20th Century. Beginning in ~1940 the seasonal cycle increased in amplitude by ~10 ppb (measured from seasonal minimum to maximum), and the seasonal maximum shifted to later in the year by about 3 weeks. This shift maximized in the mid-1980s, followed by a reversal -- the seasonal cycle decreased in amplitude and the maximum shifted back to earlier in the year. Similar changes are seen in measurements collected from the 1970s to the present. The timing of the seasonal cycle changes is generally concurrent with the rise and fall of anthropogenic emissions that followed industrialization and subsequent implementation of air quality emission controls. We quantitatively compare the temporal changes of the ozone seasonal cycle at sites in both Europe and North America with the temporal changes of ozone precursor emissions across the northern midlatitudes and find a high degree of similarity between these two temporal patterns. We hypothesize that changing precursor emissions are responsible for the shift in the ozone seasonal cycle, and suggest the mechanism by which changing emissions drive the changing seasonal cycle: increasing emissions of NOX allow summertime photochemical production of ozone to become more important than ozone transported from the stratosphere and increasing VOCs lead to progressively greater photochemical ozone production in the summer months, thereby increasing the amplitude of the seasonal ozone cycle. Decreasing emissions of both precursor classes then reverse these changes. The quantitative parameter values that characterize the seasonal shifts provide useful benchmarks for evaluating model simulations, both against observations and between models. [ABSTRACT FROM AUTHOR]

Tropospheric ozone is important to future air quality and climate. We investigate ozone changes and ozone sensitivity to changing emissions in the context of climate change from the present day (2004–2014) to the future (2045–2055) under a range of shared socio-economic pathways (SSPs). We apply the United Kingdom Earth System Model, UKESM1, with an extended chemistry scheme including more reactive volatile organic compounds (VOCs) to quantify ozone burdens as well as ozone sensitivities globally and regionally based on nitrogen oxide (NO?? ) and VOC concentrations. We show that the tropospheric ozone burden increases by 4 % under a development pathway with higher NO?? and VOC emissions (SSP3-7.0), but decreases by 7 % under the same pathway if NO?? and VOC emissions are reduced (SSP3-7.0-lowNTCF) and by 5 % if atmospheric methane (CH4) concentrations are reduced (SSP3-7.0-lowCH4). Global mean surface ozone concentrations are reduced by 3–5 ppb under SSP3-7.0-lowNTCF and by 2–3 ppb under SSP3-7.0-lowCH4. However, surface ozone changes vary substantially by season in high-emission regions under future pathways, with decreased ozone concentrations in summer and increased ozone concentrations in winter when NO?? emissions are reduced. VOC-limited areas are more extensive in winter (7 %) than in summer (3 %) across the globe. North America, Europe and East Asia are the dominant VOC-limited regions in the present day but North America and Europe become more NO??-limited in the future mainly due to reductions in NO?? emissions. The impacts of VOC emissions on ozone sensitivity are limited in North America and Europe because reduced anthropogenic VOC emissions are offset by higher biogenic VOC emissions. Ozone sensitivity is not greatly influenced by changing CH4 concentrations. South Asia becomes the dominant VOC-limited region under future pathways. We highlight that reductions in NO?? emissions are required to transform ozone production from VOC- to NO?? -limitation, but that these lead to increased ozone concentrations in high-emission regions, and hence emission controls on VOC and CH4 are also necessary. [ABSTRACT FROM AUTHOR]

The United Kingdom Chemistry and Aerosols (UKCA) chemistry–climate model is used to quantify the differences in chemical environment for surface O3 for six major industrial regions across China in summer 2016. We first enhance the UKCA gas-phase chemistry scheme by incorporating reactive volatile organic compound (VOC) tracers that are necessary to represent urban and regional-scale O3 photochemistry. We demonstrate that the model with the improved chemistry scheme captures the observed magnitudes and diurnal patterns of surface O3 concentrations across these regions well. Simulated O3 concentrations are highest in Beijing and Shijiazhuang on the North China Plain and in Chongqing, lower in Shanghai and Nanjing in the Yangtze River Delta, and lowest in Guangzhou in the Pearl River Delta despite the highest daytime O3 production rates in Guangzhou. NOx / VOC and H2O2 / HNO3 ratios indicate that O3 production across all regions except Chongqing is VOC limited. We confirm this by constructing O3 response surfaces for each region changing NOx and VOC emissions and further contrast the effectiveness of measures to reduce surface O3 concentrations. In VOC-limited regions, reducing NOx emissions by 20 % leads to a substantial O3 increase (11 %) in Shanghai. We find that reductions in NOx emissions alone of more than 70 % are required to decrease O3 concentrations across all regions. Reductions in VOC emissions alone of 20 % produce the largest decrease (- 11 %) in O3 levels in Shanghai and Guangzhou and the smallest decrease (- 1 %) in Chongqing. These responses are substantially different from those currently found in highly populated regions in other parts of the world, likely due to higher NOx emission levels in these Chinese regions. Our work provides an assessment of the effectiveness of emission control strategies to mitigate surface O3 pollution in these major industrial regions and emphasises that combined NOx and VOC emission controls play a pivotal role in effectively offsetting high O3 levels. It also demonstrates new capabilities in capturing regional air pollution that will permit this model to be used for future studies of regional air-quality–climate interactions. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the mineral dust aerosol modelled by five Earth system models (ESMs) within the project entitled Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach (CRESCENDO). We quantify the global dust cycle described by each model in terms of global emissions, together with dry and wet deposition, reporting large differences in the ratio of dry over wet deposition across the models not directly correlated with the range of particle sizes emitted. The multi-model mean dust emissions with five ESMs is 2836 Tgyr-1 but with a large uncertainty due mainly to the difference in the maximum dust particle size emitted. The multi-model mean of the subset of four ESMs without particle diameters larger than 10 µm is 1664 (σ=651) Tgyr-1. Total dust emissions in the simulations with identical nudged winds from reanalysis give us better consistency between models; i.e. the multi-model mean global emissions with three ESMs are 1613 (σ=278) Tgyr-1 , but 1834 (σ=666) Tgyr-1 without nudged winds and the same models. Significant discrepancies in the globally averaged dust mass extinction efficiency explain why even models with relatively similar global dust load budgets can display strong differences in dust optical depth. The comparison against observations has been done in terms of dust optical depths based on MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products, showing global consistency in terms of preferential dust sources and transport across the Atlantic. The global localisation of source regions is consistent with MODIS, but we found regional and seasonal differences between models and observations when we quantified the cross-correlation of time series over dust-emitting regions. To faithfully compare local emissions between models we introduce a re-gridded normalisation method that can also be compared with satellite products derived from dust event frequencies. Dust total deposition is compared with an instrumental network to assess global and regional differences. We find that models agree with observations within a factor of 10 for data stations distant from dust sources, but the approximations of dust particle size distribution at emission contributed to a misrepresentation of the actual range of deposition values when instruments are close to dust-emitting regions. The observed dust surface concentrations also are reproduced to within a factor of 10. The comparison of total aerosol optical depth with AERONET (AErosol RObotic NETwork) stations where dust is dominant shows large differences between models, although with an increase in the inter-model consistency when the simulations are conducted with nudged winds. The increase in the model ensemble consistency also means better agreement with observations, which we have ascertained for dust total deposition, surface concentrations and optical depths (against both AERONET and MODIS retrievals). We introduce a method to ascertain the contributions per mode consistent with the multi-modal direct radiative effects, which we apply to study the direct radiative effects of a multi-modal representation of the dust particle size distribution that includes the largest particles. [ABSTRACT FROM AUTHOR]

Our quantitative understanding of natural tropospheric ozone concentrations is limited by the paucity of reliable measurements before the 1980s. We utilize the existing measurements to compare the long-term ozone changes that occurred within the marine boundary layer at northern and southern midlatitudes. Since 1950 ozone concentrations have increased by a factor of 2.1 ± 0.2 in the Northern Hemisphere (NH) and are presently larger than in the Southern Hemisphere (SH), where only a much smaller increase has occurred. These changes are attributed to increased ozone production driven by anthropogenic emissions of photochemical ozone precursors that increased with industrial development. The greater ozone concentrations and increases in the NH are consistent with the predominant location of anthropogenic emission sources in that hemisphere. The available measurements indicate that this interhemispheric gradient was much smaller and was likely reversed in the pre-industrial troposphere with higher concentrations in the SH. Six Earth system model (ESM) simulations indicate similar total NH increases (1.9 with a standard deviation of 0.3), but they occurred more slowly over a longer time period, and the ESMs do not find higher pre-industrial ozone in the SH. Several uncertainties in the ESMs may cause these model–measurement disagreements: the assumed natural nitrogen oxide emissions may be too large, the relatively greater fraction of ozone injected by stratosphere–troposphere exchange to the NH may be overestimated, ozone surface deposition to ocean and land surfaces may not be accurately simulated, and model treatment of emissions of biogenic hydrocarbons and their photochemistry may not be adequate. [ABSTRACT FROM AUTHOR]

The evolution of tropospheric ozone from 1850 to 2100 has been studied using data from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). We evaluate long-term changes using coupled atmosphere–ocean chemistry–climate models, focusing on the CMIP Historical and ScenarioMIP ssp370 experiments, for which detailed tropospheric-ozone diagnostics were archived. The model ensemble has been evaluated against a suite of surface, sonde and satellite observations of the past several decades and found to reproduce well the salient spatial, seasonal and decadal variability and trends. The multi-model mean tropospheric-ozone burden increases from 247 ± 36 Tg in 1850 to a mean value of 356 ± 31 Tg for the period 2005–2014, an increase of 44 %. Modelled present-day values agree well with previous determinations (ACCENT: 336 ± 27 Tg; Atmospheric Chemistry and Climate Model Intercomparison Project, ACCMIP: 337 ± 23 Tg; Tropospheric Ozone Assessment Report, TOAR: 340 ± 34 Tg). In the ssp370 experiments, the ozone burden increases to 416 ± 35 Tg by 2100. The ozone budget has been examined over the same period using lumped ozone production (PO3) and loss (LO3) diagnostics. Both ozone production and chemical loss terms increase steadily over the period 1850 to 2100, with net chemical production (PO3 - LO3) reaching a maximum around the year 2000. The residual term, which contains contributions from stratosphere–troposphere transport reaches a minimum around the same time before recovering in the 21st century, while dry deposition increases steadily over the period 1850–2100. Differences between the model residual terms are explained in terms of variation in tropopause height and stratospheric ozone burden. [ABSTRACT FROM AUTHOR]

The connection between the dominant mode of interannual variability in the tropical troposphere, the El Niño–Southern Oscillation (ENSO), and the entry of stratospheric water vapor is analyzed in a set of model simulations archived for the Chemistry-Climate Model Initiative (CCMI) project and for Phase 6 of the Coupled Model Intercomparison Project. While the models agree on the temperature response to ENSO in the tropical troposphere and lower stratosphere, and all models and observations also agree on the zonal structure of the temperature response in the tropical tropopause layer, the only aspect of the entry water vapor response with consensus in both models and observations is that La Niña leads to moistening in winter relative to neutral ENSO. For El Niño and for other seasons, there are significant differences among the models. For example, some models find that the enhanced water vapor for La Niña in the winter of the event reverses in spring and summer, some models find that this moistening persists, and some show a nonlinear response, with both El Niño and La Niña leading to enhanced water vapor in both winter, spring, and summer. A moistening in the spring following El Niño events, the signal focused on in much previous work, is simulated by only half of the models. Focusing on Central Pacific ENSO vs. East Pacific ENSO, or temperatures in the mid-troposphere compared with temperatures near the surface, does not narrow the inter-model discrepancies. Despite this diversity in response, the temperature response near the cold point can explain the response of water vapor when each model is considered separately. While the observational record is too short to fully constrain the response to ENSO, it is clear that most models suffer from biases in the magnitude of the interannual variability of entry water vapor. This bias could be due to biased cold-point temperatures in some models, but others appear to be missing forcing processes that contribute to observed variability near the cold point. [ABSTRACT FROM AUTHOR]

The UKCA chemistry-climate model is used to quantify the differences in chemical environment for surface O[sub 3] for six major industrial regions across China in summer 2016. We first enhance the UKCA gas-phase chemistry scheme by incorporating reactive VOC tracers that are necessary to represent urban and regional-scale O[sub 3] photochemistry. We demonstrate that the model with the improved chemistry scheme captures the observed magnitudes and diurnal patterns of surface O[sub 3] concentrations across these regions well. Simulated O[sub 3] concentrations are highest in Beijing and Shijiazhuang on the North China Plain and in Chongqing, lower in Shanghai and Nanjing in the Yangtze River Delta, and lowest in Guangzhou in the Pearl River Delta despite the highest daytime O[sub 3] production rates in Guangzhou. NO[sub x] / VOC and H[sub 2]O[sub 2] / HNO[sub 3] ratios indicate that O[sub 3] production across all regions except Chongqing is VOC limited. We confirm this by constructing O[sub 3] response surfaces for each region changing NO[sub x] and VOC emissions and further contrast the effectiveness of measures to reduce surface O[sub 3] concentrations. In VOC limited regions, reducing NO[sub x] emissions by 20 % leads to a substantial O[sub 3] increase (11 %) in Shanghai. We find that reductions in NO[sub x] emissions alone of more than 70 % are required to decrease O[sub 3] concentrations across all regions. Reductions in VOC emissions alone of 20 % produce the largest decrease (-11 %) in O[sub 3] levels in Shanghai and Guangzhou and the smallest decrease (-1 %) in Chongqing. These responses are substantially different from those currently found in highly populated regions in other parts of the world, likely due to higher NO[sub x] emission levels in these Chinese regions. Our work provides an assessment of the effectiveness of emission control strategies to mitigate surface O[sub 3] pollution in these major industrial regions, and emphasizes that combined NO[sub x] and VOC emission controls play a pivotal role in effectively offsetting high O[sub 3] levels. It also demonstrates new capabilities in capturing regional air pollution that will permit this model to be used for future studies of regional air quality-climate interactions. [ABSTRACT FROM AUTHOR]