Global Chemistry-climate Model Research Articles

Technical note: An assessment of the performance of statistical bias correction techniques for global chemistry–climate model surface ozone fields

Abstract. State-of-the-art chemistry–climate models (CCMs) still show biases compared to ground-level ozone observations, illustrating the difficulties and challenges remaining in the simulation of atmospheric processes governing ozone production and loss. Therefore, CCM output is frequently bias-corrected in studies seeking to explore the health or environmental impacts from changing air quality burdens. Here, we assess four statistical bias correction techniques of varying complexities and their application to surface ozone fields simulated with four CCMs and evaluate their performance against gridded observations in the EU and US. We focus on two time periods (2005–2009 and 2010–2014), where the first period is used for development and training and the second to evaluate the performance of techniques when applied to model projections. We find that all methods are capable of significantly reducing the model bias. However, biases are lowest when we apply more complex approaches such as quantile mapping and delta functions. We also highlight the sensitivity of the correction techniques to individual CCM skill at reproducing the observed distributional change in surface ozone. Ensemble simulations available for one CCM indicate that model ozone biases are likely more sensitive to the process representation embedded in chemical mechanisms than to meteorology.

One-third of global population at cancer risk due to elevated volatile organic compounds levels

Outdoor air pollution, particularly volatile organic compounds (VOCs), significantly contributes to the global health burden. Previous analyses of VOC exposure have typically focused on regional and national scales, thereby limiting global health burden assessments. In this study, we utilized a global chemistry-climate model to simulate VOC distributions and estimate related cancer risks from 2000 to 2019. Our findings indicated a 10.2% rise in global VOC emissions during this period, with substantial increases in Sub-Saharan Africa, the Rest of Asia, and China, but decreases in the U.S. and Europe due to reductions in the transportation and residential sectors. Carcinogenic VOCs such as benzene, formaldehyde, and acetaldehyde contributed to a lifetime cancer burden affecting 0.60 [95% confidence interval (95CI): 0.40–0.81] to 0.85 [95CI: 0.56–1.14] million individuals globally. We projected that between 36.4% and 39.7% of the global population was exposed to harmful VOC levels, with the highest exposure rates found in China (82.8–84.3%) and considerably lower exposure in Europe (1.7–5.8%). Open agricultural burning in less-developed regions amplified VOC-induced cancer burdens. Significant disparities in cancer burdens between high-income and low-to-middle-income countries were identified throughout the study period, primarily due to unequal population growth and VOC emissions. These findings underscore health disparities among different income nations and emphasize the persistent need to address the environmental injustice related to air pollution exposure.

Development, intercomparison, and evaluation of an improved mechanism for the oxidation of dimethyl sulfide in the UKCA model

Abstract. Dimethyl sulfide (DMS) is an important trace gas emitted from the ocean. The oxidation of DMS has long been recognised as being important for global climate through the role DMS plays in setting the sulfate aerosol background in the troposphere. However, the mechanisms in which DMS is oxidised are very complex and have proved elusive to accurately determine in spite of decades of research. As a result the representation of DMS oxidation in global chemistry–climate models is often greatly simplified. Recent field observations and laboratory and ab initio studies have prompted renewed efforts in understanding the DMS oxidation mechanism, with implications for constraining the uncertainty in the oxidation mechanism of DMS as incorporated in global chemistry–climate models. Here we build on recent evidence and develop a new DMS mechanism for inclusion in the UK Chemistry Aerosol (UKCA) chemistry–climate model. We compare our new mechanism (CS2-HPMTF) to a number of existing mechanisms used in UKCA (including the highly simplified three-reactions–two-species mechanism used in CMIP6 studies with the model) and to a range of recently developed mechanisms reported in the literature through a series of global and box model experiments. Global model runs with the new mechanism enable us to simulate the global distribution of hydroperoxylmethyl thioformate (HPMTF), which we calculate to have a burden of 2.6–26 Gg S (in good agreement with the literature range of 0.7–18 Gg S). We show that the sinks of HPMTF dominate uncertainty in the budget, not the rate of the isomerisation reaction forming it and that, based on the observed DMS / HPMTF ratio from the global surveys during the NASA Atmospheric Tomography mission (ATom), rapid cloud uptake of HPMTF worsens the model–observation comparison. Our box model experiments highlight that there is significant variance in simulated secondary oxidation products from DMS across mechanisms used in the literature, with significant divergence in the sensitivity of the rates of formation of these products to temperature exhibited; especially for methane sulfonic acid (MSA). Our global model studies show that our updated DMS scheme performs better than the current scheme used in UKCA when compared against a suite of surface and aircraft observations. However, sensitivity studies underscore the need for further laboratory and observational constraints. In particular our results suggest that as a priority long-term DMS observations be made to better constrain the highly uncertain inputs into the system and that laboratory studies be performed that address (1) the uptake of HPMTF onto aerosol surfaces and the products of this reaction and (2) the kinetics and products of the following reactions: CH3SO3 decomposition, CH3S + O2, CH3SOO decomposition, and CH3SO + O3.

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy data fusion to map global surface ozone concentration

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m−3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Emulating lateral gravity wave propagation in a global chemistry–climate model (EMAC v2.55.2) through horizontal flux redistribution

Abstract. The columnar approach of gravity wave (GW) parameterisations in weather and climate models has been identified as a potential reason for dynamical biases in middle-atmospheric dynamics. For example, GW momentum flux (GWMF) discrepancies between models and observations at 60∘ S arising through the lack of horizontal orographic GW propagation are suspected to cause deficiencies in representing the Antarctic polar vortex. However, due to the decomposition of the model domains onto different computing tasks for parallelisation, communication between horizontal grid boxes is computationally extremely expensive, making horizontal propagation of GWs unfeasible for global chemistry–climate simulations. To overcome this issue, we present a simplified solution to approximate horizontal GW propagation through redistribution of the GWMF at one single altitude by means of tailor-made redistribution maps. To generate the global redistribution maps averaged for each grid box, we use a parameterisation describing orography as a set of mountain ridges with specified location, orientation and height combined with a ray-tracing model describing lateral propagation of so-generated mountain waves. In the global chemistry–climate model (CCM) EMAC (ECHAM MESSy Atmospheric Chemistry), these maps then allow us to redistribute the GW momentum flux horizontally at one level, obtaining an affordable overhead of computing resources. The results of our simulations show GWMF and drag patterns that are horizontally more spread out than with the purely columnar approach; GWs are now also present above the ocean and regions without mountains. In this paper, we provide a detailed description of how the redistribution maps are computed and how the GWMF redistribution is implemented in the CCM. Moreover, an analysis shows why 15 km is the ideal altitude for the redistribution. First results with the redistributed orographic GWMF provide clear evidence that the redistributed GW drag in the Southern Hemisphere has the potential to modify and improve Antarctic polar vortex dynamics, thereby paving the way for enhanced credibility of CCM simulations and projections of polar stratospheric ozone.

Meteorology-driven PM2.5 interannual variability over East Asia

Atmospheric fine particulate matter (PM2.5) is a human health risk factor, but its ambient concentration depends on both precursor emissions and meteorology. While emission reductions are used to set PM2.5-related health policies, the effect of meteorology is often overlooked. To explore this aspect, we examined PM2.5 interannual variability (IAV) associated with meteorological parameters using the long-term simulation from the Community Earth System Model (CESM1), a global climate-chemistry model, with fixed emissions. The results are subsequently contrasted with the MERRA-2 reanalysis dataset, which inherently considers emission and meteorology effects. Over continental East Asia, the CESM1 domain-average PM2.5 IAV is 6.7 %, mainly attributed to humidity, precipitation, and ventilation variation. The grid-cell PM2.5 IAVs over southern East China are larger, up to 12 % due to the more substantial influence of El Niño-induced meteorological anomalies. Under such climate extreme, sub-regional PM2.5 concentration may occasionally exceed WHO air quality guideline levels despite the compliance of the long-term mean. The simulated PM2.5 IAV over continental East Asia is ~25 % of that derived from the MERRA-2 data, which highlights the influence of both emission and meteorology-driven variations and trends inherent in the latter. Although emission-driven variability is significant to PM2.5 IAV, in remote areas downwind of major source regions in East Asia, North America, and Western Europe, the MERRA-2 data revealed that meteorological variations contributed more to PM2.5 IAV than emission variations. Thus, when setting policies for complying with the WHO PM2.5-related air quality guideline levels, the highest annual PM2.5 associated with climate extremes should be considered instead of that based on average climate conditions.

Anthropogenic amplification of biogenic secondary organic aerosol production

Abstract. Biogenic secondary organic aerosols (SOAs) contribute to a large fraction of fine aerosols globally, impacting air quality and climate. The formation of biogenic SOA depends on not only emissions of biogenic volatile organic compounds (BVOCs) but also anthropogenic pollutants including primary organic aerosol, sulfur dioxide (SO2), and nitrogen oxides (NOx). However, the anthropogenic impact on biogenic SOA production (AIBS) remains unclear. Here we use the decadal trend and variability in observed organic aerosol (OA) in the southeast US, combined with a global chemistry–climate model, to better constrain AIBS. We show that the reduction in SO2 emissions can only explain 40 % of the decreasing decadal trend of OA in this region, constrained by the low summertime month-to-month variability in surface OA. We hypothesize that the rest of the OA decreasing trend is largely due to a reduction in NOx emissions. By implementing a scheme for monoterpene SOA with enhanced sensitivity to NOx, our model can reproduce the decadal trend and variability in OA in this region. Extending to a centennial scale, our model shows that global SOA production increases by 36 % despite BVOC reductions from the preindustrial period to the present day, largely amplified by AIBS. Our work suggests a strong coupling between anthropogenic and biogenic emissions in biogenic SOA production that is missing from current climate models.

Sensitivity of tropospheric ozone to halogen chemistry in the chemistry–climate model LMDZ-INCA vNMHC

Abstract. The atmospheric chemistry of halogenated species (Cl, Br, I) participates in the global chemical sink of tropospheric ozone and perturbs the oxidising capacity of the troposphere, notably by influencing the atmospheric lifetime of methane. Global chemistry–climate models are commonly used to assess the global budget of ozone and its sensitivity to emissions of its precursors, as well as to project its long-term evolution. Here, we report on the implementation of tropospheric sources and chemistry of halogens in the chemistry–climate model LMDZ-INCA (Laboratoire de Météorologie Dynamique general circulation model, LMDZ, and Interactions with Chemistry and Aerosols, INCA, version with Non-Methane HydroCarbon chemistry, vNMHC) and evaluate halogen effects on the tropospheric ozone budget. Overall, the results show that the model simulates satisfactorily the impact of halogens on the photo-oxidising system in the troposphere, in particular in the marine boundary layer. To quantify the effects of halogen chemistry in LMDZ-INCA, standard metrics representative of the behaviour of the tropospheric chemical system (Ox, HOx, NOx, CH4 and non-methane volatile organic compounds – NMVOCs) are computed with and without halogens. The addition of tropospheric halogens in the LMDZ-INCA model leads to a decrease of 22 % in the ozone burden, 8 % in OH and 33 % in NOx. Sensitivity simulations show for the first time that the inclusion of halogen chemistry makes ozone more sensitive to perturbations in CH4, NOx and NMVOCs. Consistent with other global model studies, the sensitivity of the tropospheric ozone burden to changes from pre-industrial to present-day emissions is found to be ∼20 % lower when tropospheric halogens are taken into account.

Regional Sources and Sinks of Atmospheric Particulate Selenium in the United States Based on Seasonality Profiles.

Selenium (Se) is an essential nutrient for humans and enters our food chain through bioavailable Se in soil. Atmospheric deposition is a major source of Se to soils, driving the need to investigate the sources and sinks of atmospheric Se. Here, we used Se concentrations from PM2.5 data at 82 sites from 1988 to 2010 from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network in the US to identify the sources and sinks of particulate Se. We identified 6 distinct seasonal profiles of atmospheric Se, grouped by geographical location: West, Southwest, Midwest, Southeast, Northeast, and North Northeast. Across most of the regions, coal combustion is the largest Se source, with a terrestrial source dominating in the West. We also found evidence for gas-to-particle partitioning in the wintertime in the Northeast. Wet deposition is an important sink of particulate Se, as determined by Se/PM2.5 ratios. The Se concentrations from the IMPROVE network compare well to modeled output from a global chemistry-climate model, SOCOL-AER, except in the Southeast US. Our analysis constrains the sources and sinks of atmospheric Se, thereby improving the predictions of Se distribution under climate change.

Rapid increase in tropospheric ozone over Southeast Asia attributed to changes in precursor emission source regions and sectors

Observations indicate that tropospheric ozone (O3) concentrations over Southeast Asia have been increasing rapidly since the 1990s. Here, we quantify source contributions from geographical regions and emission sectors of the two distinct types of O3 precursors, i.e., nitrogen oxides (NOx) and volatile organic compounds (VOCs), to the increase in tropospheric O3 in Southeast Asia during 1990–2019 using an O3 source tagging technique implemented in a global chemistry-climate model. The results show that although local anthropogenic emission of NOx in Southeast Asia only contributes 18% of the annual averaged near-surface O3 concentration, the increase in local NOx emission dominates the increasing trend of O3 concentration in Southeast Asia, accounting for 107% of the regional averaged trend of 1.07 ppb decade−1. Increases in NOx emissions from East Asia and South Asia explain 29% of the increasing trend, but 9% is offset by the emission reduction in North America. The vertical O3 trends in the troposphere contributed by individual source regions are consistent with those near the surface. Ground transportation is responsible for 79% of the rapid O3 increase, followed by 39% contribution from international shipping. Because an increase in anthropogenic NOx emissions enhances the O3 production efficiency by VOCs, the increase in O3 concentrations in Southeast Asia is thereby largely contributed by methane and biogenic VOCs.

The historical ozone trends simulated with the SOCOLv4 and their comparison with observations and reanalyses

Abstract. There is evidence that the ozone layer has begun to recover owing to the ban on the production of halogenated ozone-depleting substances (hODS) accomplished by the Montreal Protocol and its amendments and adjustments (MPA). However, recent studies, while reporting an increase in tropospheric ozone from the anthropogenic NOx and CH4 and confirming the ozone recovery in the upper stratosphere from the effects of hODS, also indicate a continuing decline in the lower tropical and mid-latitudinal stratospheric ozone. While these are indications derived from observations, they are not reproduced by current global chemistry–climate models (CCMs), which show positive or near-zero trends for ozone in the lower stratosphere. This makes it difficult to robustly establish ozone evolution and has sparked debate about the ability of contemporary CCMs to simulate future ozone trends. We applied the new Earth system model (ESM) SOCOLv4 (SOlar Climate Ozone Links, version 4) to calculate long-term ozone trends between 1985–2018 and compare them with trends derived from the BAyeSian Integrated and Consolidated (BASIC) ozone composite and MERRA-2, ERA-5, and MSRv2 reanalyses. We designed the model experiment with a six-member ensemble to account for the uncertainty of the natural variability. The trend analysis is performed separately for the ozone depletion (1985–1997) and ozone recovery (1998–2018) phases of the ozone evolution. Within the 1998–2018 period, SOCOLv4 shows statistically significant positive ozone trends in the mesosphere, upper and middle stratosphere, and a steady increase in the tropospheric ozone. The SOCOLv4 results also suggest slightly negative trends in the extra-polar lower stratosphere, yet they barely agree with the BASIC ozone composite in terms of magnitude and statistical significance. However, in some realizations of the SOCOLv4 experiment, the pattern of ozone trends in the lower stratosphere resembles much of what is observed, suggesting that SOCOLv4 may be able to reproduce the observed trends in this region. Thus, the model results reveal marginally significant negative ozone changes in parts of the low-latitude lower stratosphere, which agrees in general with the negative tendencies extracted from the satellite data composite. Despite the slightly smaller significance and magnitude of the simulated ensemble mean, we confirm that modern CCMs such as SOCOLv4 are generally capable of simulating the observed ozone changes, justifying their use to project the future evolution of the ozone layer.

Radiative impact of improved global parameterisations of oceanic dry deposition of ozone and lightning-generated NOx

Abstract. We investigated the radiative impact of recent process-based improvements to oceanic ozone (O3) dry deposition parameterisation and empirical improvements to lightning-generated oxides of nitrogen (LNOx) parameterisation by conducting a 5-year simulation of the Australian Community Climate and Earth System Simulator – United Kingdom Chemistry and Aerosol (ACCESS-UKCA) global chemistry–climate model, with radiative effects of O3, methane (CH4) and aerosol included. Compared to the base parameterisations, the global consequences of the two improved parameterisations on atmospheric composition are dominated by the LNOx change (which increases the LNOx production from 4.8 to 6.9 Tg N yr−1) and include (a) an increase in the O3 column of 3.75 DU, and this O3 change is centred on the tropical upper troposphere where O3 is most effective as a radiative forcer; (b) a decrease of 0.64 years in the atmospheric lifetime of CH4 due to an increase in hydroxyl radical, which corresponds to a decrease of 0.31 years in the CH4 lifetime per Tg N yr−1 change in LNOx; (c) an increase of 6.7 % in the column integrated condensation nuclei concentration; and (d) a slight increase in high-level cloud cover. The two combined parameterisation changes cause an increase of 86.3 mW m−2 in the globally-averaged all-sky net downward top-of-atmosphere (TOA) radiative flux (which is akin to instantaneous radiative forcing), and only 5 % of which is due to the dry deposition parameterisation change. Other global radiative changes from the use of the two parameterisations together include an increase in the downward longwave radiation and a decrease in the downward shortwave radiation at the earth's surface. The indirect effect of LNOx on aerosol and cloud cover can at least partly explain the differences in the downward shortwave flux at the surface. It is demonstrated that although the total global LNOx production may be the same, how LNOx is distributed spatially makes a difference to radiative transfer. We estimate that for a reported uncertainty range of 5±3 Tg N yr−1 in global estimates of LNOx, the uncertainty in the net downward TOA radiation is ±119 mW m−2. The corresponding uncertainly in the atmospheric methane lifetime is ±0.92 years. Thus, the value of LNOx used within a model will influence the effective radiative forcing (ERF) and global warming potential (GWP) of anthropogenic CH4, and influence the results of climate scenario modelling.

Correcting ozone biases in a global chemistry–climate model: implications for future ozone

Abstract. 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.

TransClim (v1.0): a chemistry–climate response model for assessing the effect of mitigation strategies for road traffic on ozone

Abstract. Road traffic emits not only carbon dioxide (CO2) and particulate matter, but also other pollutants such as nitrogen oxides (NOx), volatile organic compounds (VOCs) and carbon monoxide (CO). These chemical species influence the atmospheric chemistry and produce ozone (O3) in the troposphere. Ozone acts as a greenhouse gas and thus contributes to anthropogenic global warming. Technological trends and political decisions can help to reduce the O3 effect of road traffic emissions on climate. In order to assess the O3 response of such mitigation options on climate, we developed a chemistry–climate response model called TransClim (Modelling the effect of surface Transportation on Climate). The current version considers road traffic emissions of NOx, VOC and CO and determines the O3 change and its corresponding stratosphere-adjusted radiative forcing. Using a tagging method, TransClim is further able to quantify the contribution of road traffic emissions to the O3 concentration. Thus, TransClim determines the contribution to O3 as well as the change in total tropospheric O3 of a road traffic emission scenario. Both quantities are essential when assessing mitigation strategies. The response model is based on lookup tables which are generated by a set of emission variation simulations performed with the global chemistry–climate model EMAC (ECHAM5 v5.3.02, MESSy v2.53.0). Evaluating TransClim against independent EMAC simulations reveals low deviations of all considered species (0.01 %–10 %). Hence, TransClim is able to reproduce the results of an EMAC simulation very well. Moreover, TransClim is about 6000 times faster in computing the climate effect of an emission scenario than the complex chemistry–climate model. This makes TransClim a suitable tool to efficiently assess the climate effect of a broad range of mitigation options for road traffic or to analyse uncertainty ranges by employing Monte Carlo simulations.

New Insights on the Radiative Impacts of Ozone‐Depleting Substances

AbstractThe global warming potential of Ozone‐depleting substances (ODS) has long been known to be thousands of times larger than the one of CO2, but their climate impacts as greenhouse gases, i.e. unmediated by ozone depletion, has received relatively little attention. Focusing on the period 1955–2005, we here present results from offline radiative forcing (RF) calculations from a global chemistry climate model. Using realistic distributions of ODS and consistent stratospheric ozone, we show that ODS dominate the adjusted stratospheric warming of the lower stratosphere, where CO2 has little radiative impact. We also show that the global mean RF of stratospheric ozone only cancels a fraction of the RF of ODS, leaving an important ODS contribution to anthropogenic forcing. Finally we show that the RF of ODS opposes Arctic amplification, its equator‐to‐pole gradient being larger than the one of CO2.

The impact of sulfur hexafluoride (SF<sub>6</sub>) sinks on age of air climatologies and trends

Abstract. Mean age of air (AoA) is a common diagnostic for the strength of the stratospheric overturning circulation in both climate models and observations. AoA climatologies and AoA trends over the recent decades of model simulations and proxies derived from observations of long-lived tracers do not agree. Satellite observations show much older air than climate models, and while most models compute a clear decrease in AoA over the last decades, a 30-year time series from measurements shows a statistically nonsignificant positive trend in the Northern Hemisphere extratropical middle stratosphere. Measurement-based AoA derivations are often founded on observations of the trace gas sulfur hexafluoride (SF6), a fairly long-lived gas with a near-linear increase in emissions during recent decades. However, SF6 has chemical sinks in the mesosphere that are not considered in most model studies. In this study, we explicitly compute the chemical SF6 sinks based on chemical processes in the global chemistry climate model EMAC (ECHAM/MESSy Atmospheric Chemistry). We show that good agreement between stratospheric AoA in EMAC and MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) is reached through the inclusion of chemical SF6 sinks, as these sinks lead to a strong increase in the stratospheric AoA and, therefore, to a better agreement with MIPAS satellite observations. Remaining larger differences at high latitudes are addressed, and possible reasons for these differences are discussed. Subsequently, we demonstrate that the AoA trends are also strongly influenced by the chemical SF6 sinks. Under consideration of the SF6 sinks, the AoA trends over the recent decades reverse sign from negative to positive. We conduct sensitivity simulations which reveal that this sign reversal does not result from trends in the stratospheric circulation strength nor from changes in the strength of the SF6 sinks. We illustrate that even a constant SF6 destruction rate causes a positive trend in the derived AoA, as the amount of depleted SF6 scales with increasing SF6 abundance itself. In our simulations, this effect overcompensates for the impact of the accelerating stratospheric circulation which naturally decreases AoA. Although various sources of uncertainties cannot be quantified in detail in this study, our results suggest that the inclusion of SF6 depletion in models has the potential to reconcile the AoA trends of models and observations. We conclude the study with a first approach towards a correction to account for SF6 loss and deduce that a linear correction might be applicable to values of AoA of up to 4 years.

Surface ozone interannual variability, trends, and extremes in CCMI models

Tropospheric ozone exhibits variations at interannual to decadal timescales tied closely to climate variability. The fidelity of current-generation global chemistry-climate models (CCMs) in representing observed variations and extremes of troposphere ozone is an important aspect of model abilities to predict ozone but has not been comprehensively assessed. Here we evaluate multiple state-of-the-art CCMs participating in the Chemistry-Climate Model Initiative phase 1 (CCMI-1) in simulating the interannual variability (IAV), decadal trends, and extremes of surface ozone during 1990–2010 at northern mid-latitudes. We find that current CCMs tend to underestimate observed ozone IAV over the U.S., Europe, and East Asia in both spring and summer and fail to capture the springtime ozone trends in the eastern U.S. (EUS) and Europe. Specified-dynamics simulations constrained by reanalysis data outperform the free-running simulations with CCMs in terms of IAV and decadal trends of surface ozone. Observations show large surface ozone IAV in summer over the EUS, Europe, and East Asia (standard deviation = 3−6 ppbv or relative standard deviation = 8−15%) while all models substantially underestimate observed IAV by a factor of 2–3. Analysis in these populous/polluted regions unveils that the models significantly underestimate ozone extreme anomalies during heatwaves/droughts by 2–9 ppbv (17–55%) over the EUS and by 7–10 ppbv (42–59%) over Europe during the past two decades. These underestimates in summertime extreme anomalies contribute to the model biases in surface ozone IAV. Future model developments are needed to improve the ability of current CCMs to predict ozone extremes during heatwaves and droughts.

Mountain-wave-induced polar stratospheric clouds and their representation in the global chemistry model ICON-ART

Abstract. Polar stratospheric clouds (PSCs) are a driver for ozone depletion in the lower polar stratosphere. They provide surface for heterogeneous reactions activating chlorine and bromine reservoir species during the polar night. The large-scale effects of PSCs are represented by means of parameterisations in current global chemistry–climate models, but one process is still a challenge: the representation of PSCs formed locally in conjunction with unresolved mountain waves. In this study, we investigate direct simulations of PSCs formed by mountain waves with the ICOsahedral Nonhydrostatic modelling framework (ICON) with its extension for Aerosols and Reactive Trace gases (ART) including local grid refinements (nesting) with two-way interaction. Here, the nesting is set up around the Antarctic Peninsula, which is a well-known hot spot for the generation of mountain waves in the Southern Hemisphere. We compare our model results with satellite measurements of PSCs from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and gravity wave observations of the Atmospheric Infrared Sounder (AIRS). For a mountain wave event from 19 to 29 July 2008 we find similar structures of PSCs as well as a fairly realistic development of the mountain wave between the satellite data and the ICON-ART simulations in the Antarctic Peninsula nest. We compare a global simulation without nesting with the nested configuration to show the benefits of adding the nesting. Although the mountain waves cannot be resolved explicitly at the global resolution used (about 160 km), their effect from the nested regions (about 80 and 40 km) on the global domain is represented. Thus, we show in this study that the ICON-ART model has the potential to bridge the gap between directly resolved mountain-wave-induced PSCs and their representation and effect on chemistry at coarse global resolutions.

Assessing and improving cloud-height-based parameterisations of global lightning flash rate, and their impact on lightning-produced NO<sub><i>x</i></sub> and tropospheric composition in a chemistry–climate model

Abstract. Although lightning-generated oxides of nitrogen (LNOx) account for only approximately 10 % of the global NOx source, they have a disproportionately large impact on tropospheric photochemistry due to the conducive conditions in the tropical upper troposphere where lightning is mostly discharged. In most global composition models, lightning flash rates used to calculate LNOx are expressed in terms of convective cloud-top height via the Price and Rind (1992) (PR92) parameterisations for land and ocean, where the oceanic parameterisation is known to greatly underestimate flash rates. We conduct a critical assessment of flash-rate parameterisations that are based on cloud-top height and validate them within the Australian Community Climate and Earth System Simulator – United Kingdom Chemistry and Aerosol (ACCESS-UKCA) global chemistry–climate model using the Lightning Imaging Sensor and Optical Transient Detector (LIS/OTD) satellite data. While the PR92 parameterisation for land yields satisfactory predictions, the oceanic parameterisation, as expected, underestimates the observed flash-rate density severely, yielding a global average over the ocean of 0.33 flashes s−1 compared to the observed 9.16 flashes s−1 and leading to LNOx being underestimated proportionally. We formulate new flash-rate parameterisations following Boccippio's (2002) scaling relationships between thunderstorm electrical generator power and storm geometry coupled with available data. The new parameterisation for land performs very similarly to the corresponding PR92 one, as would be expected, whereas the new oceanic parameterisation simulates the flash-rate observations much more accurately, giving a global average over the ocean of 8.84 flashes s−1. The use of the improved flash-rate parameterisations in ACCESS-UKCA changes the modelled tropospheric composition – global LNOx increases from 4.8 to 6.6 Tg N yr−1; the ozone (O3) burden increases by 8.5 %; there is an increase in the mid- to upper-tropospheric NOx by as much as 40 pptv, a 13 % increase in the global hydroxyl radical (OH), a decrease in the methane lifetime by 6.7 %, and a decrease in the lower-tropospheric carbon monoxide (CO) by 3 %–7 %. Compared to observations, the modelled tropospheric NOx and ozone in the Southern Hemisphere and over the ocean are improved by this new flash-rate parameterisation.

Evaluation of polar stratospheric clouds in the global chemistry–climate model SOCOLv3.1 by comparison with CALIPSO spaceborne lidar measurements

Abstract. Polar stratospheric clouds (PSCs) contribute to catalytic ozone destruction by providing surfaces for the conversion of inert chlorine species into active forms and by denitrification. The latter describes the removal of HNO3 from the stratosphere by sedimenting PSC particles, which hinders chlorine deactivation by the formation of reservoir species. Therefore, an accurate representation of PSCs in chemistry–climate models (CCMs) is of great importance to correctly simulate polar ozone concentrations. Here, we evaluate PSCs as simulated by the CCM SOCOLv3.1 for the Antarctic winters 2006, 2007 and 2010 by comparison with backscatter measurements by CALIOP on board the CALIPSO satellite. The year 2007 represents a typical Antarctic winter, while 2006 and 2010 are characterized by above- and below-average PSC occurrence. The model considers supercooled ternary solution (STS) droplets, nitric acid trihydrate (NAT) particles, water ice particles and mixtures thereof. PSCs are parameterized in terms of temperature and partial pressures of HNO3 and H2O, assuming equilibrium between the gas and particulate phase. The PSC scheme involves a set of prescribed microphysical parameters, namely ice number density, NAT particle radius and maximum NAT number density. In this study, we test and optimize the parameter settings through several sensitivity simulations. The choice of the value for the ice number density affects simulated optical properties and dehydration, while modifying the NAT parameters impacts stratospheric composition via HNO3 uptake and denitrification. Depending on the NAT parameters, reasonable denitrification can be modeled. However, its impact on ozone loss is minor. The best agreement with the CALIOP optical properties and observed denitrification was for this case study found with the ice number density increased from the hitherto used value of 0.01 to 0.05 cm−3 and the maximum NAT number density from 5×10-4 to 1×10-3 cm−3. The NAT radius was kept at the original value of 5 µm. The new parameterization reflects the higher importance attributed to heterogeneous nucleation of ice and NAT particles following recent new data evaluations of the state-of-the-art CALIOP measurements. A cold temperature bias in the polar lower stratosphere results in an overestimated PSC areal coverage in SOCOLv3.1 by up to 40 %. Offsetting this cold bias by +3 K delays the onset of ozone depletion by about 2 weeks, which improves the agreement with observations. Furthermore, the occurrence of mountain-wave-induced ice, as observed mainly over the Antarctic Peninsula, is continuously underestimated in the model due to the coarse model resolution (T42L39) and the fixed ice number density. Nevertheless, we find overall good temporal and spatial agreement between modeled and observed PSC occurrence and composition. This work confirms previous studies indicating that simplified PSC schemes, which avoid nucleation and growth calculations in sophisticated but time-consuming microphysical process models, may also achieve good approximations of the fundamental properties of PSCs needed in CCMs.