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The remoteness and extreme conditions of the Southern Ocean and Antarctic region have meant that observations in this region are rare, and typically restricted to summertime during research or resupply voyages. Observations of aerosols outside of the summer season are typically limited to long-term stations, such as Kennaook / Cape Grim (KCG; 40.7∘ S, 144.7∘ E), which is situated in the northern latitudes of the Southern Ocean, and Antarctic research stations, such as the Japanese operated Syowa (SYO; 69.0∘ S, 39.6∘ E). Measurements in the midlatitudes of the Southern Ocean are important, particularly in light of recent observations that highlighted the latitudinal gradient that exists across the region in summertime. Here we present 2 years (March 2016–March 2018) of observations from Macquarie Island (MQI; 54.5∘ S, 159.0∘ E) of aerosol (condensation nuclei larger than 10 nm, CN10) and cloud condensation nuclei (CCN at various supersaturations) concentrations. This important multi-year data set is characterised, and its features are compared with the long-term data sets from KCG and SYO together with those from recent, regionally relevant voyages. CN10 concentrations were the highest at KCG by a factor of ∼50 % across all non-winter seasons compared to the other two stations, which were similar (summer medians of 530, 426 and 468 cm−3 at KCG, MQI and SYO, respectively). In wintertime, seasonal minima at KCG and MQI were similar (142 and 152 cm−3, respectively), with SYO being distinctly lower (87 cm−3), likely the result of the reduction in sea spray aerosol generation due to the sea ice ocean cover around the site. CN10 seasonal maxima were observed at the stations at different times of year, with KCG and MQI exhibiting January maxima and SYO having a distinct February high. Comparison of CCN0.5 data between KCG and MQI showed similar overall trends with summertime maxima and wintertime minima; however, KCG exhibited slightly (∼10 %) higher concentrations in summer (medians of 158 and 145 cm−3, respectively), whereas KCG showed ∼40 % lower concentrations than MQI in winter (medians of 57 and 92 cm−3, respectively). Spatial and temporal trends in the data were analysed further by contrasting data to coincident observations that occurred aboard several voyages of the RSV Aurora Australis and the RV Investigator. Results from this study are important for validating and improving our models and highlight the heterogeneity of this pristine region and the need for further long-term observations that capture the seasonal cycles.

Walking is essential for the health and well-being of communities as well as meeting environmental challenges of the 21st Century. There have been significant research contributions in recent decades to understanding factors that can influence the likelihood of citizens choosing active travel modes, with great advances in understanding the built environment, particularly macro-scaled urban factors such as land-use mix, population density, and street patterns. So why are people still not walking? And is there anything we can do to try to change this? To answer these questions, this paper explores walking environment assessment approaches using a trans-disciplinary narrative approach, touching on multiple critical disciplinary knowledge areas. We find that while much of the research into the built environment’s influence on walking has made positive contributions in helping identify areas of cities that discourage active travel, the capacity to improve these areas has been limited. While macro-scaled factors commonly considered in ‘walkability’ analysis are highly influential to mode choice, unless working on green-field development, these factors may require re-zoning private land, substantial demolition and renewal, and may be financially or politically infeasible and thus extremely difficult to change. There is a need to augment macro-scaled analysis with micro-scaled tools, and to establish multi-criterion spatio-temporal design decision support approaches drawing from emerging technologies to make informed, integrated and effective urban design changes. These methods applied at precinct and streetscape levels have the potential to make feasible improvements to the ‘walk-quality’ of the built environment and contribute to facilitating active travel.

Coral reefs have been found to produce the sulfur compound dimethyl sulfide (DMS), a climatically relevant aerosol precursor predominantly associated with phytoplankton. Until recently, the role of coral-reef-derived DMS within the climate system had not been quantified. A study preceding the present work found that DMS produced by corals had negligible long-term climatic forcing at the global–regional scale. However, at sub-daily timescales more typically associated with aerosol and cloud formation, the influence of coral-reef-derived DMS on local aerosol radiative effects remains unquantified. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) has been used in this work to study the role of coral-reef-derived DMS at sub-daily timescales for the first time. WRF-Chem was run to coincide with an October 2016 field campaign over the Great Barrier Reef, Queensland, Australia, against which the model was evaluated. After updating and scaling the DMS surface water climatology, the model reproduced DMS and sulfur concentrations well. The inclusion of coral-reef-derived DMS resulted in no significant change in sulfate aerosol mass or total aerosol number. Subsequently, no direct or indirect aerosol effects were detected. The results suggest that the co-location of the Great Barrier Reef with significant anthropogenic aerosol sources along the Queensland coast prevents coral-reef-derived aerosol from having a modulating influence on local aerosol burdens in the current climate.

Dimethyl sulfide (DMS) is a naturally occurring aerosol precursor gas which plays an important role in the global sulfur budget, aerosol formation and climate. While DMS is produced predominantly by phytoplankton, recent observational literature has suggested that corals and their symbionts produce a comparable amount of DMS, which is unaccounted for in models. It has further been hypothesised that the coral reef source of DMS may modulate regional climate. This hypothesis presents a particular concern given the current threat to coral reefs under anthropogenic climate change. In this paper, a global climate model with online chemistry and aerosol is used to explore the influence of coral-reef-derived DMS on atmospheric composition and climate. A simple representation of coral-reef-derived DMS is developed and added to a common DMS surface water climatology, resulting in an additional flux of 0.3 Tg yr−1 S, or 1.7 % of the global sulfur flux from DMS. By comparing the differences between both nudged and free-running ensemble simulations with and without coral-reef-derived DMS, the influence of coral-reef-derived DMS on regional climate is quantified. In the Maritime Continent–Australian region, where the highest density of coral reefs exists, a small decrease in nucleation- and Aitken-mode aerosol number concentration and mass is found when coral reef DMS emissions are removed from the system. However, these small responses are found to have no robust effect on regional climate via direct and indirect aerosol effects. This work emphasises the complexities of the aerosol–climate system, and the limitations of current modelling capabilities are highlighted, in particular surrounding convective responses to changes in aerosol. In conclusion, we find no robust evidence that coral-reef-derived DMS influences global and regional climate.

South-eastern Australia has been identified by modelling studies as a hotspot of biogenic volatile organic compound (VOC) emissions; however, long-term observational VOC studies are lacking in this region. Here, 2.5 years of multi-axis differential optical absorption spectroscopy (MAX-DOAS) formaldehyde (HCHO) measurements in Australasia are presented, from Broadmeadows, in northern Melbourne, Australia, and from Lauder, a rural site in the South Island of New Zealand. Across the measurement period from December 2016 to November 2019, the mean formaldehyde columns measured by the MAX-DOAS were 2.50±0.61×1015 molec. cm−2 at Lauder and 5.40±1.59×1015 molec. cm−2 at Broadmeadows. In both locations, the seasonal cycle showed a pronounced peak in Austral summer (December–January–February) consistent with temperature-dependent formaldehyde production from biogenic precursor gases. The amplitude of the seasonal cycle was 0.7×1015 molec. cm−2 at Lauder, and it was 2.0×1015 molec. cm−2 at Broadmeadows. The Lauder MAX-DOAS HCHO measurements are compared with 27 months of co-located Fourier transform infrared (FTIR) observations. The seasonal variation of Lauder MAX-DOAS HCHO, smoothed by the FTIR averaging kernels, showed good agreement with the FTIR measurements, with a linear regression slope of 1.03 and an R2 of 0.66 for monthly averaged formaldehyde partial columns (0–4 km). In addition to ground-based observations, a clear way to address the VOC measurement gap in areas such as Australasia is with satellite measurements. Here, we demonstrate that the TROPOspheric Monitoring Instrument (TROPOMI) can be used to distinguish formaldehyde hotspots in forested and agricultural regions of south-eastern Australia. The MAX-DOAS measurements are also compared to TROPOMI HCHO vertical columns at Lauder and Melbourne; very strong monthly average agreement is found for Melbourne (regression slope of 0.61 and R2 of 0.95) and a strong agreement is found at Lauder (regression slope of 0.73 and R2 of 0.61) for MAX-DOAS vs. TROPOMI between May 2018 and November 2019. This study, the first long-term satellite comparison study using MAX-DOAS in the Southern Hemisphere, highlights the improvement offered by TROPOMI's high resolution over previous satellite products and provides the groundwork for future studies using ground-based and satellite DOAS for studying VOCs in Australasia.

Transport from the Northern Hemisphere (NH) midlatitudes to the Arctic plays a crucial role in determining the abundance of trace gases and aerosols that are important to Arctic climate via impacts on radiation and chemistry. Here we examine this transport using an idealized tracer with a fixed lifetime and predominantly midlatitude land-based sources in models participating in the Chemistry Climate Model Initiative (CCMI). We show that there is a 25 %–45 % difference in the Arctic concentrations of this tracer among the models. This spread is correlated with the spread in the location of the Pacific jet, as well as the spread in the location of the Hadley Cell (HC) edge, which varies consistently with jet latitude. Our results suggest that it is likely that the HC-related zonal-mean meridional transport rather than the jet-related eddy mixing is the major contributor to the inter-model spread in the transport of land-based tracers into the Arctic. Specifically, in models with a more northern jet, the HC generally extends further north and the tracer source region is mostly covered by surface southward flow associated with the lower branch of the HC, resulting in less efficient transport poleward to the Arctic. During boreal summer, there are poleward biases in jet location in free-running models, and these models likely underestimate the rate of transport into the Arctic. Models using specified dynamics do not have biases in the jet location, but do have biases in the surface meridional flow, which may result in differences in transport into the Arctic. In addition to the land-based tracer, the midlatitude-to-Arctic transport is further examined by another idealized tracer with zonally uniform sources. With equal sources from both land and ocean, the inter-model spread of this zonally uniform tracer is more related to variations in parameterized convection over oceans rather than variations in HC extent, particularly during boreal winter. This suggests that transport of land-based and oceanic tracers or aerosols towards the Arctic differs in pathways and therefore their corresponding inter-model variabilities result from different physical processes.

Climate models consistently predict an acceleration of the Brewer–Dobson circulation (BDC) due to climate change in the 21st century. However, the strength of this acceleration varies considerably among individual models, which constitutes a notable source of uncertainty for future climate projections. To shed more light upon the magnitude of this uncertainty and on its causes, we analyse the stratospheric mean age of air (AoA) of 10 climate projection simulations from the Chemistry-Climate Model Initiative phase 1 (CCMI-I), covering the period between 1960 and 2100. In agreement with previous multi-model studies, we find a large model spread in the magnitude of the AoA trend over the simulation period. Differences between future and past AoA are found to be predominantly due to differences in mixing (reduced aging by mixing and recirculation) rather than differences in residual mean transport. We furthermore analyse the mixing efficiency, a measure of the relative strength of mixing for given residual mean transport, which was previously hypothesised to be a model constant. Here, the mixing efficiency is found to vary not only across models, but also over time in all models. Changes in mixing efficiency are shown to be closely related to changes in AoA and quantified to roughly contribute 10 % to the long-term AoA decrease over the 21st century. Additionally, mixing efficiency variations are shown to considerably enhance model spread in AoA changes. To understand these mixing efficiency variations, we also present a consistent dynamical framework based on diffusive closure, which highlights the role of basic state potential vorticity gradients in controlling mixing efficiency and therefore aging by mixing.

Previous multi-model intercomparisons have shown that chemistry–climate models exhibit significant biases in tropospheric ozone compared with observations. We investigate annual-mean tropospheric column ozone in 15 models participating in the SPARC–IGAC (Stratosphere–troposphere Processes And their Role in Climate–International Global Atmospheric Chemistry) Chemistry-Climate Model Initiative (CCMI). These models exhibit a positive bias, on average, of up to 40 %–50 % in the Northern Hemisphere compared with observations derived from the Ozone Monitoring Instrument and Microwave Limb Sounder (OMI/MLS), and a negative bias of up to ∼ 30 % in the Southern Hemisphere. SOCOLv3.0 (version 3 of the Solar-Climate Ozone Links CCM), which participated in CCMI, simulates global-mean tropospheric ozone columns of 40.2 DU – approximately 33 % larger than the CCMI multi-model mean. Here we introduce an updated version of SOCOLv3.0, SOCOLv3.1, which includes an improved treatment of ozone sink processes, and results in a reduction in the tropospheric column ozone bias of up to 8 DU, mostly due to the inclusion of N2O5 hydrolysis on tropospheric aerosols. As a result of these developments, tropospheric column ozone amounts simulated by SOCOLv3.1 are comparable with several other CCMI models. We apply Gaussian process emulation and sensitivity analysis to understand the remaining ozone bias in SOCOLv3.1. This shows that ozone precursors (nitrogen oxides (NOx), carbon monoxide, methane and other volatile organic compounds, VOCs) are responsible for more than 90 % of the variance in tropospheric ozone. However, it may not be the emissions inventories themselves that result in the bias, but how the emissions are handled in SOCOLv3.1, and we discuss this in the wider context of the other CCMI models. Given that the emissions data set to be used for phase 6 of the Coupled Model Intercomparison Project includes approximately 20 % more NOx than the data set used for CCMI, further work is urgently needed to address the challenges of simulating sub-grid processes of importance to tropospheric ozone in the current generation of chemistry–climate models.

Toxic nitrogen oxides produced by high temperature combustion are prevalent in urban environments, contributing to a significant health burden. Nitrogen oxides such as NO2 and HONO in pollution are important for hydroxyl radical (OH) production and overall oxidative capacity in urban environments; however, current mechanisms cannot explain high daytime levels of HONO observed in many urban and rural locations around the world. Here we present HONO, NO2 and aerosol extinction vertical distributions retrieved from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in suburban Melbourne, which are the first MAX-DOAS results from the Australian continent. Using the optimal estimation algorithm HEIPRO we show that vertical profiles for NO2 and HONO can be calculated with a low dependence on the retrieval forward model and a priori parameters, despite a lack of independent co-located aerosol or trace gas measurements. Between December 2016 and April 2017 average peak NO2 values of 8±2 ppb indicated moderate traffic pollution levels, and high daytime peak values of HONO were frequently detected, averaging 220±30 ppt in the middle of the day. HONO levels measured in Melbourne were typically lower than those recorded in the morning in other places around the world, indicating minimal overnight accumulation, but peaked in the middle of the day to be commensurate with midday concentrations in locations with much higher NO2 pollution. Regular midday peaks in the diurnal cycle of HONO surface concentrations have only previously been reported in rural locations. The HONO measured implies a daytime source term 1 ppb h−1 above the predicted photostationary state (PSS) concentration and represents an OH radical source up to 4 times stronger than from ozone photolysis alone in the lowest 500 m of the troposphere. The dependence of the high midday HONO levels on soil moisture, combined with the observed diurnal and vertical profiles, provides evidence for a strong photoactivated and ground-based daytime HONO source.

Natural aerosol emission represents one of the largest uncertainties in our understanding of the radiation budget. Sulfur emitted by marine organisms, as dimethyl sulfide (DMS), constitutes one-fifth of the global sulfur budget and yet the distribution, fluxes and fate of DMS remain poorly constrained. This study evaluates the Australian Community Climate and Earth System Simulator (ACCESS) United Kingdom Chemistry and Aerosol (UKCA) model in terms of cloud fraction, radiation and precipitation, and then quantifies the role of DMS in the chemistry–climate system. We find that ACCESS-UKCA has similar cloud and radiation biases to other global climate models. By removing all DMS, or alternatively significantly enhancing marine DMS, we find a top of the atmosphere radiative effect of 1.7 and −1.4 W m−2 respectively. The largest responses to these DMS perturbations (removal/enhancement) are in stratiform cloud decks in the Southern Hemisphere's eastern ocean basins. These regions show significant differences in low cloud (−9∕ + 6 %), surface incoming shortwave radiation (+7∕ − 5 W m−2) and large-scale rainfall (+15∕ − 10 %). We demonstrate a precipitation suppression effect of DMS-derived aerosol in stratiform cloud deck regions due to DMS, coupled with an increase in low cloud fraction. The difference in low cloud fraction is an example of the aerosol lifetime effect. Globally, we find a sensitivity of temperature to annual DMS flux of 0.027 and 0.019 K per Tg yr−1 of sulfur, respectively. Other areas of low cloud formation, such as the Southern Ocean and stratiform cloud decks in the Northern Hemisphere, have a relatively weak response to DMS perturbations. We highlight the need for greater understanding of the DMS–climate cycle within the context of uncertainties and biases of climate models as well as those of DMS–climate observations.

>We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20 DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ∼ 15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼ 15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models.

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

The stratospheric age of air (AoA) is a useful measure of the overall capabilities of a general circulation model (GCM) to simulate stratospheric transport. Previous studies have reported a large spread in the simulation of AoA by GCMs and coupled chemistry–climate models (CCMs). Compared to observational estimates, simulated AoA is mostly too low. Here we attempt to untangle the processes that lead to the AoA differences between the models and between models and observations. AoA is influenced by both mean transport by the residual circulation and two-way mixing; we quantify the effects of these processes using data from the CCM inter-comparison projects CCMVal-2 (Chemistry–Climate Model Validation Activity 2) and CCMI-1 (Chemistry–Climate Model Initiative, phase 1). Transport along the residual circulation is measured by the residual circulation transit time (RCTT). We interpret the difference between AoA and RCTT as additional aging by mixing. Aging by mixing thus includes mixing on both the resolved and subgrid scale. We find that the spread in AoA between the models is primarily caused by differences in the effects of mixing and only to some extent by differences in residual circulation strength. These effects are quantified by the mixing efficiency, a measure of the relative increase in AoA by mixing. The mixing efficiency varies strongly between the models from 0.24 to 1.02. We show that the mixing efficiency is not only controlled by horizontal mixing, but by vertical mixing and vertical diffusion as well. Possible causes for the differences in the models' mixing efficiencies are discussed. Differences in subgrid-scale mixing (including differences in advection schemes and model resolutions) likely contribute to the differences in mixing efficiency. However, differences in the relative contribution of resolved versus parameterized wave forcing do not appear to be related to differences in mixing efficiency or AoA.

Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances, and a combination of carbon dioxide and other greenhouse gases. We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

Stratosphere-to-troposphere transport (STT) provides an important natural source of ozone to the upper troposphere, but the characteristics of STT events in the Southern Hemisphere extratropics and their contribution to the regional tropospheric ozone budget remain poorly constrained. Here, we develop a quantitative method to identify STT events from ozonesonde profiles. Using this method we estimate the seasonality of STT events and quantify the ozone transported across the tropopause over Davis (69° S, 2006–2013), Macquarie Island (54° S, 2004–2013), and Melbourne (38° S, 2004–2013). STT seasonality is determined by two distinct methods: a Fourier bandpass filter of the vertical ozone profile and an analysis of the Brunt–Väisälä frequency. Using a bandpass filter on 7–9 years of ozone profiles from each site provides clear detection of STT events, with maximum occurrences during summer and minimum during winter for all three sites. The majority of tropospheric ozone enhancements owing to STT events occur within 2.5 and 3 km of the tropopause at Davis and Macquarie Island respectively. Events are more spread out at Melbourne, occurring frequently up to 6 km from the tropopause. The mean fraction of total tropospheric ozone attributed to STT during STT events is ∼ 1. 0–3. 5 % at each site; however, during individual events, over 10 % of tropospheric ozone may be directly transported from the stratosphere. The cause of STTs is determined to be largely due to synoptic low-pressure frontal systems, determined using coincident ERA-Interim reanalysis meteorological data. Ozone enhancements can also be caused by biomass burning plumes transported from Africa and South America, which are apparent during austral winter and spring and are determined using satellite measurements of CO. To provide regional context for the ozonesonde observations, we use the GEOS-Chem chemical transport model, which is too coarsely resolved to distinguish STT events but is able to accurately simulate the seasonal cycle of tropospheric ozone columns over the three southern hemispheric sites. Combining the ozonesonde-derived STT event characteristics with the simulated tropospheric ozone columns from GEOS-Chem, we estimate STT ozone flux near the three sites and see austral summer dominated yearly amounts of between 5. 7 and 8. 7 × 1017 molecules cm−2 a−1.

We present an overview of state-of-the-art chemistry–climate and chemistry transport models that are used within phase 1 of the Chemistry–Climate Model Initiative (CCMI-1). The CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models' projections of the stratospheric ozone layer, tropospheric composition, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to which CCMI-1 recommendations for simulations have been followed is necessary to understand model responses to anthropogenic and natural forcing and also to explain inter-model differences. This becomes even more important given the ongoing development and the ever-growing complexity of these models. This paper also provides an overview of the available CCMI-1 simulations with the aim of informing CCMI data users.

Better characterisation of aerosol processes in pristine, natural environments, such as Antarctica, have recently been shown to lead to the largest reduction in uncertainties in our understanding of radiative forcing. Our understanding of aerosols in the Antarctic region is currently based on measurements that are often limited to boundary layer air masses at spatially sparse coastal and continental research stations, with only a handful of studies in the vast sea-ice region. In this paper, the first observational study of sub-micron aerosols in the East Antarctic sea ice region is presented. Measurements were conducted aboard the icebreaker Aurora Australis in spring 2012 and found that boundary layer condensation nuclei (CN3) concentrations exhibited a five-fold increase moving across the polar front, with mean polar cell concentrations of 1130 cm−3 – higher than any observed elsewhere in the Antarctic and Southern Ocean region. The absence of evidence for aerosol growth suggested that nucleation was unlikely to be local. Air parcel trajectories indicated significant influence from the free troposphere above the Antarctic continent, implicating this as the likely nucleation region for surface aerosol, a similar conclusion to previous Antarctic aerosol studies. The highest aerosol concentrations were found to correlate with low-pressure systems, suggesting that the passage of cyclones provided an accelerated pathway, delivering air masses quickly from the free troposphere to the surface. After descent from the Antarctic free troposphere, trajectories suggest that sea-ice boundary layer air masses travelled equatorward into the low-albedo Southern Ocean region, transporting with them emissions and these aerosol nuclei which, after growth, may potentially impact on the region's radiative balance. The high aerosol concentrations and their transport pathways described here, could help reduce the discrepancy currently present between simulations and observations of cloud and aerosol over the Southern Ocean.

Chemistry–climate models are important tools for addressing interactions of composition and climate in the Earth system. In particular, they are used to assess the combined roles of greenhouse gases and ozone in Southern Hemisphere climate and weather. Here we present an evaluation of the Australian Community Climate and Earth System Simulator – chemistry–climate model (ACCESS-CCM), focusing on the Southern Hemisphere and the Australian region. This model is used for the Australian contribution to the international Chemistry–Climate Model Initiative, which is soliciting hindcast, future projection and sensitivity simulations. The model simulates global total column ozone (TCO) distributions accurately, with a slight delay in the onset and recovery of springtime Antarctic ozone depletion, and consistently higher ozone values. However, October-averaged Antarctic TCO from 1960 to 2010 shows a similar amount of depletion compared to observations. Comparison with model precursors shows large improvements in the representation of the Southern Hemisphere stratosphere, especially in TCO concentrations. A significant innovation is seen in the evaluation of simulated vertical profiles of ozone and temperature with ozonesonde data from Australia, New Zealand and Antarctica from 38 to 90° S. Excess ozone concentrations (greater than 26 % at Davis and the South Pole during winter) and stratospheric cold biases (up to 10 K at the South Pole during summer and autumn) outside the period of perturbed springtime ozone depletion are seen during all seasons compared to ozonesondes. A disparity in the vertical location of ozone depletion is seen: centred around 100 hPa in ozonesonde data compared to above 50 hPa in the model. Analysis of vertical chlorine monoxide profiles indicates that colder Antarctic stratospheric temperatures (possibly due to reduced mid-latitude heat flux) are artificially enhancing polar stratospheric cloud formation at high altitudes. The model's inability to explicitly simulate a supercooled ternary solution may also explain the lack of depletion at lower altitudes. Analysis of the simulated Southern Annular Mode (SAM) index compares well with ERA-Interim data, an important metric for correct representation of Australian climate. Accompanying these modulations of the SAM, 50 hPa zonal wind differences between 2001–2010 and 1979–1998 show increasing zonal wind strength southward of 60° S during December for both the model simulations and ERA-Interim data. These model diagnostics show that the model reasonably captures the stratospheric ozone-driven chemistry–climate interactions important for Australian climate and weather while highlighting areas for future model development.

Aerosol observations above the Southern Ocean and Antarctic sea ice are scarce. Measurements of aerosols and atmospheric composition were made in East Antarctic pack ice on board the Australian icebreaker Aurora Australis during the spring of 2012. One particle formation event was observed during the 32 days of observations. This event occurred on the only day to exhibit extended periods of global irradiance in excess of 600 W m−2. Within the single air mass influencing the measurements, number concentrations of particles larger than 3 nm (CN3) reached almost 7700 cm−3 within a few hours of clouds clearing, and grew at rates of 5.6 nm h−1. Formation rates of 3 nm particles were in the range of those measured at other Antarctic locations at 0.2–1.1 ± 0.1 cm−3 s−1. Our investigations into the nucleation chemistry found that there were insufficient precursor concentrations for known halogen or organic chemistry to explain the nucleation event. Modelling studies utilising known sulfuric acid nucleation schemes could not simultaneously reproduce both particle formation or growth rates. Surprising correlations with total gaseous mercury (TGM) were found that, together with other data, suggest a mercury-driven photochemical nucleation mechanism may be responsible for aerosol nucleation. Given the very low vapour pressures of the mercury species involved, this nucleation chemistry is likely only possible where pre-existing aerosol concentrations are low and both TGM concentrations and solar radiation levels are relatively high (∼ 1.5 ng m−3 and ≥ 600 W m−2, respectively), such as those observed in the Antarctic sea ice boundary layer in this study or in the global free troposphere, particularly in the Northern Hemisphere.

In this study we examine the simulated downward transport and mixing of stratospheric air into the upper tropical troposphere as observed on a research flight during the SCOUT-O3 campaign in connection with a deep convective system. We use the Advanced Research Weather and Research Forecasting (WRF-ARW) model with a horizontal resolution of 333 m to examine this downward transport. The simulation reproduces the deep convective system, its timing and overshooting altitudes reasonably well compared to radar and aircraft observations. Passive tracers initialised at pre-storm times indicate the downward transport of air from the stratosphere to the upper troposphere as well as upward transport from the boundary layer into the cloud anvils and overshooting tops. For example, a passive ozone tracer (i.e. a tracer not undergoing chemical processing) shows an enhancement in the upper troposphere of up to about 30 ppbv locally in the cloud, while the in situ measurements show an increase of 50 ppbv. However, the passive carbon monoxide tracer exhibits an increase, while the observations show a decrease of about 10 ppbv, indicative of an erroneous model representation of the transport processes in the tropical tropopause layer. Furthermore, it could point to insufficient entrainment and detrainment in the model. The simulation shows a general moistening of air in the lower stratosphere, but it also exhibits local dehydration features. Here we use the model to explain the processes causing the transport and also expose areas of inconsistencies between the model and observations.

The standard Dobson Umkehr methodology to retrieve coarse-resolution ozone profiles used by the National Oceanographic and Atmospheric Administration uses designated solar zenith angles (SZAs). However, some information may be lost if measurements lie outside the designated SZA range (between 60° and 90°), or do not conform to the fitting technique. Also, while Umkehr measurements can be taken using multiple wavelength pairs (A, C and D), past retrieval methods have focused on a single pair (C). Here we present an Umkehr inversion method that uses measurements at all SZAs (termed operational) and all wavelength pairs. (Although, we caution direct comparison to other algorithms.) Information content for a Melbourne, Australia (38° S, 145° E) Umkehr measurement case study from 28 January 1994, with SZA range similar to that designated in previous algorithms is shown. When comparing the typical single wavelength pair with designated SZAs to the operational measurements, the total degrees of freedom (independent pieces of information) increases from 3.1 to 3.4, with the majority of the information gain originating from Umkehr layers 2 + 3 and 4 (10–20 km and 25–30 km respectively). In addition to this, using all available wavelength pairs increases the total degrees of freedom to 5.2, with the most significant increases in Umkehr layers 2 + 3 to 7 and 9+ (10–40 and 45–80 km). Investigating a case from 13 April 1970 where the measurements extend beyond the 90° SZA range gives further information gain, with total degrees of freedom extending to 6.5. Similar increases are seen in the information content. Comparing the retrieved Melbourne Umkehr time series with ozonesondes shows excellent agreement in layers 2 + 3 and 4 (10–20 and 25–30 km) for both C and A + C + D-pairs. Retrievals in layers 5 and 6 (25–30 and 30–35 km) consistently show lower ozone partial column compared to ozonesondes. This is likely due to stray light effects that are not accounted for in the forward model, and under represented stratospheric aerosol.

We present ozone measurements made using state-of-the-art ultraviolet photometers onboard three long-duration stratospheric balloons launched as part of the Concordiasi campaign in austral spring 2010. Ozone loss rates calculated by matching air parcels sampled at different times and places during the polar spring are in agreement with rates previously derived from ozonesonde measurements, for the vortex average, ranging between 2 and 7 ppbv per sunlit hour or between 25 and 110 ppbv per day. However, the geographical coverage of these long-duration stratospheric balloon platforms provides new insights into the temporal and spatial patterns of ozone loss over Antarctica. Very large ozone loss rates of up to 230 ppbv per day (16 ppbv per sunlit hour) are observed for air masses that are downwind of the Antarctic Peninsula and/or over the East Antarctic region. The ozone loss rate maximum downstream of the Antarctic Peninsula region is consistent with high PSC occurrence from CALIPSO and large ClO abundances from MLS satellite observations for 12–22 September 2010, and with a chemical box model simulation using JPL 2011 kinetics with full chlorine activation.

Key kinetic parameters governing the partitioning of chlorine species in the Antarctic polar stratosphere were retrieved from 28 days of chlorine monoxide (ClO) microwave radiometer measurements made during the late winter/early spring of 2005 at Scott Base (77.85° S, 166.75° E). During day-time the loss of the ClO dimer chlorine peroxide (ClOOCl) occurs mainly by photolysis. Some time after sunrise, a photochemical equilibrium is established and the ClO/ClOOCl partitioning is determined by the ratio of the photolysis frequency, J, and the dimer formation rate, kf. The values of J and kf from laboratory studies remain uncertain to a considerable extent, and as a complement to these ongoing studies, the goal of this work is to provide a constraint on that uncertainty based on observations of ClO profiles in the Antarctic. First an optimal estimation technique was used to derive J/kf ratios for a range of Keq values. The optimal estimation forward model was a photochemical box model that takes J, kf, and Keq as inputs, together with a priori profiles of activated chlorine (ClOx = ClO+2×ClOOCl), profiles of ozone, temperature, and pressure. JPL06 kinetics are used as a priori in the optimal estimation and for all other chemistry in the forward model. Using the more recent JPL09 kinetics results in insignificant differences in the retrieved value of J/kf. A complementary approach was used to derive the optimal kinetic parameters; the full parameter space of J, kf, Keq and ClOx was sampled to find the minimum in differences between measured and modelled ClO profiles. Furthermore, values of Keq up to 2.0 times larger than recommended by JPL06 were explored to test the sensitivity of the J/kf ratio to changes in Keq. The results show that the retrieved J/kf ratios bracket the range of 1.23 to 1.97 times the J/kf value recommended by JPL06 over the range of Keq values considered. The retrieved J/kf ratios lie in the lower half of the large uncertainty range of J/kf recommended by JPL06 and towards the upper portion of the smaller uncertainty range recommended by JPL09.

We evaluate the sensitivity of Bry entering the stratosphere with a simplified model that allows calculations over a wide parameter range for parameters that are currently poorly quantified. The model examines the transport process uncertainties in the source concentrations and lifetimes, in the convective parameterization and in the inorganic bromine washout process due to dehydration. Source concentrations at the surface and lifetimes were found to have a slight effect on the resultant Bry (1 ppt), however this was highly dependent upon, with increasing significance, the BL component of convectively delivered air. Efficiency of convective delivery of boundary layer (BL) air to the tropical tropopause layer (TTL) along with washout at the CPT were found to substantially affect Bry at 400 K – altering the delivered Bry by 3.3 ppt and 2.9 ppt, respectively. We find that the results critically depend on free tropospheric bromine source gas concentrations due to dilution of convective updrafts, and the processes that control free tropospheric bromine source gas concentrations require further attention.

A new "Bayesian" minimization algorithm for the retrieval of the diurnal variation of UV/vis absorbing radicals (O3, NO2, BrO, OClO and HONO) from balloon-borne limb scattered skylight observations is discussed. The method evaluates spectroscopic measurements in combination with radiative transfer calculations to drive a mathematical inversion on a discrete time and height grid. Here, the proposed method is applied to data obtained during two deployments of the mini-DOAS instrument on different balloon payloads in northern Brazil in June 2005. The retrieval is tested by comparing the inferred profiles to in-situ ozone sounding data and to measurements of the ENVISAT/SCIAMACHY satellite instrument performed during a collocated overpass. The comparison demonstrates the strength and validity of our approach. In particular for time-varying radical concentrations, photochemical corrections due to temporal mismatch of the corresponding observations are rendered dispensable. Thus, limb scanning UV/vis spectrometry from balloon platforms offers a more direct and concise approach for satellite validation of radical measurements than solar occultation measurements. Furthermore, monitoring of the diurnal variation of stratospheric radicals allows us to constrain photochemical parameters which are critical for stratospheric ozone chemistry, such as the photolysis frequency of N2O5 by observations of the diurnal variation of NO2.

The "filling-in" (FI) of Fraunhofer lines, often referred to as the Ring effect, was examined using measurements of near ultraviolet sunlight scattered from the zenith sky above Boulder, Colorado during July and August 2005. The FI of the 344.1 nm Fe I line was directly determined by comparing direct sun and cloud-free zenith sky spectra recorded on the same day. The results, obtained over solar zenith angles (SZA) from 20° to 70°, are compared to the predictions of a simple rotational Raman Scattering (RRS) spectral model. The measured FI was found to be up to 70% greater than that predicted by first-order molecular scattering with a much stronger SZA dependence. Simultaneously measured aerosol optical depths and Monte Carlo calculations show that the combination of aerosol scattering and second-order molecular scattering can account for these differences, and potentially explain the contradictory SZA dependences in previously published measurements of FI. These two scattering processes also introduce a wavelength dependence to FI that complicates the fitting of diffuse sunlight observations in differential optical absorption spectroscopy (DOAS). A simple correction to improve DOAS retrievals by removing this wavelength dependence is described.

We present the results of an intercomparison exercise between six different radiative transfer (RT) models carried out in the framework of QUILT, an EU funded project based on the exploitation of the Network for the Detection of Stratospheric Change (NDSC). RT modelling is an important step in the interpretation of Differential Optical Absorption Spectroscopy (DOAS) observations. It allows the conversion of slant column densities (SCDs) into vertical column densities (VCDs) using calculated air mass factors (AMFs). The originality of our study resides in comparing SCD simulations in multi-axis (MAX) geometry (trace gases: NO2 and HCHO) and in taking into account photochemical enhancement for calculating SCDs of rapidly photolysing species (BrO, NO2, and OClO) in zenith-sky geometry. Concerning the zenith-sky simulations, the different models agree generally well, especially below 90° SZA. At higher SZA, larger discrepancies are obtained with relative differences ranging between 2% and 14% in some cases. In MAX geometry, good agreement is found between the models with the calculated NO2 and HCHO SCDs differing by no more than 5% in the elevation and solar zenith angle (SZA) ranges investigated (5°–20° and 35°–85°, respectively). The impacts of aerosol scattering, ground albedo, and relative azimuth on MAX simulations have also been tested. Significant discrepancies appear for the aerosol effect, suggesting differences between models in the treatment of aerosol scattering. A better agreement is found in case of the ground albedo and relative azimuth effects. The complete set of initialization data and results have been made publicly available through the QUILT project web site (http://nadir.nilu.no/quilt/), enabling the testing of other RT codes designed for the calculation of SCDs/AMFs.

Trends in derived from a 45 year integration of a chemistry-climate model (CCM) run have been compared with ground-based measurements at Lauder (45° S) and Arrival Heights (78° S). Observed trends in at both sites exceed the modelled trends in N2O, the primary source gas for stratospheric NO2. This suggests that the processes driving the trend are not solely dictated by changes in but are coupled to global atmospheric change, either chemically or dynamically or both. If CCMs are to accurately estimate future changes in ozone, it is important that they comprehensively include all processes affecting NOx (NO+NO2) because NOx concentrations are an important factor affecting ozone concentrations. Comparison of measured and modelled NO2 trends is a sensitive test of the degree to which these processes are incorporated in the CCM used here. At Lauder the 1980-2000 CCM NO2 trends (4.2% per decade at sunrise, 3.8% per decade at sunset) are lower than the observed trends (6.5% per decade at sunrise, 6.0% per decade at sunset) but not significantly different at the 2σ level. Large variability in both the model and measurement data from Arrival Heights makes trend analysis of the data difficult. CCM predictions (2001-2019) of NO2 at Lauder and Arrival Heights show significant reductions in the rate of increase of NO2 compared with the previous 20 years (1980-2000). The model results indicate that the partitioning of oxides of nitrogen changes with time and is influenced by both chemical forcing and circulation changes.