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The stratospheric aerosol layer is important for stratospheric chemistry, climate change and in geo-engineering. Yet the processes governing the transport of sulfur to the stratosphere are poorly quantified. We present model calculations of the chemistry of sulfur dioxide (SO2) and its transport to the stratosphere and perform numerous sensitivity runs to assess the range of uncertainty of these calculations. The transport model is based on backward trajectories from the ATLAS model driven by ECMWF ERA 5. A simplified chemical box model constrained by CAMS data is used to calculate the SO2 chemistry. Sensitivity experiments explore the sensitivity to changes in OH, H2O2, DMS, cloud water, cloud pH value and in the driving analysis data. Input parameters were varied and their differences have been explored. The effect of El Nino and La Nina on SO2 transport was investigated. The SO2 reaching the stratosphere was quantified and the sources in the troposphere were determined. The model’s results were compared to POSIDON Aircraft measurements.

The Polar SWIFT model is a fast scheme for calculating the chemistry of stratospheric ozone depletion in the polar vortex in winter. It is intended for use in general circulation models (GCMs) and earth system models (ESMs) to enable the simulation of interactions between the ozone layer and climate when a full stratospheric chemistry scheme is computationally too expensive. In addition to the simulation of chemistry, ozone has to be transported in the GCM. As an alternative to the general schemes for the transport and mixing of tracers in the GCMs, a parameterization of the transport of ozone can be used in order to obtain the total change of ozone as the sum of the change by transport and by chemistry. One of the benefits of this approach is the easy and self-contained coupling to a GCM. Another potential advantage is that a transport parameterization based on reanalysis data and measurements can avoid deficiencies in the representation of transport in the GCMs, such as deficits in the representation of the Brewer–Dobson circulation caused by the gravity wave parameterization. Hence, we present a transport parameterization for the Polar SWIFT model that simulates the change in vortex-averaged ozone by transport in a fast and simple way without the need for a complex transport scheme in the GCM.

Common representations of the stratospheric ozone layer in climate modeling are widely considered only in a very simplified way. Neglecting the mutual interactions of ozone with atmospheric temperature and dynamics has the effect of making climate projections less accurate. Although, more elaborate and interactive models of the stratospheric ozone layer are available, they require far too much computation time to be coupled with climate models. Our aim with this project was to break new ground and pursue an interdisciplinary strategy that spans the fields of machine learning, atmospheric physics and climate modelling.In this work, we present an implicit neural representation of the extrapolar stratospheric ozone chemistry (SWIFT-AI). An implicitly defined hyperspace of the stratospheric ozone chemistry offers a continuous and even differentiable representation that can be parameterized by artificial neural networks. We analysed different parameter-efficient variants of multilayer perceptrons. This was followed by an intensive, as far as possible energy-efficient search for hyperparameters involving Bayesian optimisation and early stopping techniques.Our data source is the Lagrangian chemistry and transport model ATLAS. Using its full model of stratospheric ozone chemistry, we focused on simulating a wide range of stratospheric variability that will occur in future climate (e.g. temperature and meridional circulation changes). We conducted a simulation for several years and created a data-set with over 200E+6 input and output pairs. Each output is the 24h ozone tendency of a trajectory. We performed a dimensionality reduction of the input parameters by using the concept of chemical families and by performing a sensitivity analysis to choose a set of robust input parameters.We coupled the resulting machine learning models with the Lagrangian chemistry and transport model ATLAS, substituting the full stratospheric chemistry model. We validated a two-year simulation run by comparing to the differences in accuracy and computation time from both the full stratospheric chemistry model and the previous polynomial approach of extrapolar SWIFT. We found that SWIFT-AI consistently outperforms the previous polynomial approach of SWIFT, both in terms of test data and simulation results. We discovered that the computation time of SWIFT-AI is more than twice as fast as the previous polynomial approach SWIFT and 700 times faster than the full stratospheric chemistry scheme of ATLAS, resulting in minutes instead of weeks of computation time per model year – a speed-up of several orders of magnitude.To ensure reproducibility and transparency, we developed a machine learning pipeline, published a benchmark dataset and made our repository open to the public.In summary, we could show that the application of state-of-the-art machine learning methods to the field of atmospheric physics holds great potential. The achieved speed-up of an interactive and very precise ozone layer enables a novel way of representing the ozone layer in climate models. This in turn will increase the quality of climate projections, which are crucial for policy makers and of great importance for our planet.

Arctic warming was more pronounced than warming in midlatitudes in the last decades making this region a hotspot of climate change. Associated with this, a rapid decline of sea-ice extent and a decrease of its thickness has been observed. Sea-ice retreat allows for an increased transport of heat and momentum from the ocean up to the tropo- and stratosphere by enhanced upward propagation of planetary-scale atmospheric waves. In the upper atmosphere, these waves deposit the momentum transported, disturbing the stratospheric polar vortex, which can lead to a breakdown of this circulation with the potential to also significantly impact the troposphere in mid- to late-winter and early spring. Therefore, an accurate representation of stratospheric processes in climate models is necessary to improve the understanding of the impact of retreating sea ice on the atmospheric circulation. By modeling the atmospheric response to a prescribed decline in Arctic sea ice, we show that including interactive stratospheric ozone chemistry in atmospheric model calculations leads to an improvement in tropo-stratospheric interactions compared to simulations without interactive chemistry. This suggests that stratospheric ozone chemistry is important for the understanding of sea ice related impacts on atmospheric dynamics.

The chemical loss of ozone during Arctic winter and spring due to anthropogenic halogens is driven by temperature at high latitudes, with more loss occurring during cold years with meteorological conditions that are favourable for formation of polar stratospheric clouds (PSCs). We show that a positive, statistically significant rise in the local maxima of PSC formation potential (PFPLM), i.e. seasonal integrals of the fraction of the vortex volume below the formation temperature of PSCs, within the Northern Hemisphere polar vortex over the past four decades is apparent in data from four meteorological centres. Output from numerous General Circulation Models (GCMs) that submitted results to the CMIP5 and CMIP6 archives also exhibits positive trends in PFPLM over 1950 to 2100, with the highest values occurring at end of century for model runs driven by increasing radiative forcing of climate due to greenhouse gases (GHGs) (i.e., the RCP 8.5 scenario for CMIP5 and the SSP5-8.5 scenario for CMIP6). We combine projections of the future decline in stratospheric halogen loading and possible future increases in stratospheric humidity with GCM-based forecasts of PFP to suggest that conditions favourable for large, seasonal loss of Arctic column O3 could persist until the end of this century, especially for GCM simulations constrained by either the RCP 8.5 or SSP5-8.5 GHG scenario. Conversely, if future GHG loading follow the SSP1-2.6 scenario, conditions favourable for chemical loss of Arctic O3 are projected to decline throughout the rest of this century.

Motivated by previous measurements of very low tropospheric ozone concentrations in the Tropical West Pacific (TWP) and the implied low oxidizing capacity of this key region for transport into the stratosphere in boreal winter (e.g. Rex et al. 2014), we set up an atmospheric research station in Palau (7°N 134°E) as part of the StratoClim campaign. Our analysis of regular balloon-borne tropospheric ozone observations at Palau from 01/2016-12/2019 gives unprecedented insights into transport processes and air mass origin in the TWP. We confirm the year-round dominance of a low ozone background in the mid-troposphere. Layers of enhanced ozone are often anti-correlated with water vapor and occur frequently. Moreover, the occurrence of respective layers shows a strong seasonality. Dry and ozone-rich air masses between 5 and 10 km altitude were observed in 71 % of the profiles from February until April compared to 25 % from August until October. By defining monthly atmospheric background profiles for ozone and relative humidity based on observed statistics, we found that the deviations from this background reveal a bimodal distribution of RH anomalies. A previously proposed universal bimodal structure of free tropospheric ozone in the TWP could not be verified (Pan et al. 2015).Back trajectory calculations (ATLAS) confirm that throughout the year the mid-tropospheric background is controlled by local convective processes and the origin of air masses is thus close to or East of Palau in the Pacific Ocean. Dry and ozone-rich air originates in tropical Asia and reaches Palau in anticyclonic conditions over an area stretching from India to the Philippines. This supports the controversial hypothesis of several studies which attribute ozone enhancement against the ozone-poor background to remote pollution events on the ground such as biomass burning (e.g. Andersen et al. 2016). A potential vorticity analysis revealed no stratospheric influence and we thus propose large-scale descent within the tropical troposphere as responsible for dehydration of air masses on their way to Palau.

In the Antarctic ozone hole, ozone mixing ratios have been decreasing to extremely low values of 0.01–0.1 ppm in nearly all spring seasons since the late 1980s, corresponding to 95–99% local chemical loss. In contrast, Arctic ozone loss has been much more limited and mixing ratios have never before fallen below 0.5 ppm. In Arctic spring 2020, however, ozonesonde measurements in the most depleted parts of the polar vortex show a highly depleted layer, with ozone loss averaged over sondes peaking at 93% at 18 km. Typical minimum mixing ratios of 0.2 ppm were observed, with individual profiles showing values as low as 0.13 ppm (96% loss). The reason for the unprecedented chemical loss was an unusually strong, long-lasting, and cold polar vortex, showing that for individual winters the effect of the slow decline of ozone-depleting substances on ozone depletion may be counteracted by low temperatures.

Motivated by previous measurements of very low tropospheric ozone concentrations in the Tropical West Pacific (TWP) and the implied low oxidizing capacity of this key region for transport into the stratosphere (e.g. Rex et al. 2014), we set up an atmospheric research station in Palau (7° N 134° E). Our analysis of regular balloon-borne tropospheric ozone observations at Palau from 01/2016-10/2019 confirms the year-round dominance of a low ozone background in the mid-troposphere. Layers of enhanced ozone are often anti-correlated with water vapor and occur frequently. Moreover, the occurrence of respective layers shows a strong seasonality. Dry and ozone-rich air masses between 5 and 10 km altitude were observed in 71 % of the profiles from February until April compared to 25 % from August until October. By defining monthly atmospheric background profiles for ozone and relative humidity based on observed statistics, we found that the deviations from this background reveal a bimodal distribution of RH anomalies. A previously proposed universal bimodal structure of free tropospheric ozone in the TWP could not be verified (Pan et al. 2015). Back trajectory calculations confirm that throughout the year the mid-tropospheric background is controlled by local convective processes and the origin of air masses is thus close to or East of Palau in the Pacific Ocean. Dry and ozone-rich air originates in tropical Asia and reaches Palau in anticyclonic conditions over an area stretching from India to the Philippines. This supports the hypothesis of several studies which attribute ozone enhancement against the low ozone background to remote pollution events on the ground such as biomass burning (e.g. Andersen et al. 2016). A potential vorticity analysis revealed no stratospheric influence and we thus propose large-scale descent within the tropical troposphere as responsible for dehydration of air masses on their way to Palau.

Due to the intensive ozone research in recent decades, the processes that influence stratospheric ozone are well understood. The chemistry and transport model ATLAS was developed to simulate the chemistry and transport of stratospheric ozone globally. The chemical rate of change of ozone is calculated at each model point and time step of the model by solving a system of differential equations that requires 55 input parameters (chemical species, temperatures, ...). But the computational e!ort to solve this complex system of differential equations is very high, and with respect to the overall limited computation time, this prevents the inclusion of ozone chemistry into ESMs. This project proposes a data-driven machine learning approach to predict the rate of change of stratospheric ozone. To derive a data set from modelled data, ATLAS was run for several short model runs. The rate of change of ozone and 55 parameters were stored at each model point and time step. By observing the co-variances of the high-dimensional feature-space, a large data set with reduced dimensionality has been created. A supervised learning algorithm used this data set of input and output pairs to train a deep feed- forward neural network (NN). This involved the identification and optimisation of several hyperparameters and to find a well- functioning combination of depth (number of layers) and width (number of neurons per layer). In this way, the NN model capacity is optimised with respect to the data itself. To evaluate this approach, the results were compared with another data-driven approach called SWIFT. The SWIFT model employs a repro-modelling approach that uses polynomials to approximate the rate of change of ozone. The resulting NN model is not only capable of learning the context of an eleven-dimensional hyperplane, but also improves the RMSE by about one order of magnitude compared to SWIFT’s previous polynomial approach. In addition, the deviations of the predictions at the boundaries (altitude and latitude) are significantly lower, which is a challenge for the polynomial approach. Only fully coupled ozone climate set ups are able to consider the complex interactions of the stratospheric ozone layer and climate. This is a step towards a computationally very fast but accurate application of an interactive ozone scheme in climate models.

We present the first high-resolution measurements of pollutant trace gases in the Asian summer monsoon upper troposphere and lowermost stratosphere (UTLS) from the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) during the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) campaign based in Kathmandu, Nepal, 2017. Measurements of peroxyacetyl nitrate (PAN), acetylene (C2H2), and formic acid (HCOOH) show strong local enhancements up to altitudes of 16 km. More than 500 pptv of PAN, more than 200 pptv of C2H2, and more than 200 pptv of HCOOH are observed. Air masses with increased volume mixing ratios of PAN and C2H2 at altitudes up to 18 km, reaching to the lowermost stratosphere, were present at these altitudes for more than 10 d, as indicated by trajectory analysis. A local minimum of HCOOH is correlated with a previously reported maximum of ammonia (NH3), which suggests different washout efficiencies of these species in the same air masses. A backward trajectory analysis based on the models Alfred Wegener InsTitute LAgrangian Chemistry/Transport System (ATLAS) and TRACZILLA, using advanced techniques for detection of convective events, and starting at geolocations of GLORIA measurements with enhanced pollution trace gas concentrations, has been performed. The analysis shows that convective events along trajectories leading to GLORIA measurements with enhanced pollutants are located close to regions where satellite measurements by the Ozone Monitoring Instrument (OMI) indicate enhanced tropospheric columns of nitrogen dioxide (NO2) in the days prior to the observation. A comparison to the global atmospheric models Copernicus Atmosphere Monitoring Service (CAMS) and ECHAM/MESSy Atmospheric Chemistry (EMAC) has been performed. It is shown that these models are able to reproduce large-scale structures of the pollution trace gas distributions for one part of the flight, while the other part of the flight reveals large discrepancies between models and measurement. These discrepancies possibly result from convective events that are not resolved or parameterized in the models, uncertainties in the emissions of source gases, and uncertainties in the rate constants of chemical reactions.

In the Antarctic ozone hole, ozone mixing ratios have been decreasing to extremely low values of 0.01–0.1 ppm in nearly all spring seasons since the late 1980s, corresponding to 95–99% local chemical loss. In contrast, Arctic ozone loss has been much more limited and mixing ratios have never before fallen below 0.5 ppm. In Arctic spring 2020, however, ozonesonde measurements in the most depleted parts of the polar vortex show a highly depleted layer, with ozone loss averaged over sondes peaking at 93% at 18 km. Typical minimum mixing ratios of 0.2 ppm were observed, with individual profiles showing values as low as 0.13 ppm (96% loss). The reason for the unprecedented chemical loss was an unusually strong, long-lasting, and cold polar vortex, showing that for individual winters the effect of the slow decline of ozone-depleting substances on ozone depletion may be counteracted by low temperatures.

Chemical loss of Arctic ozone due to anthropogenic halogens is driven by temperature, with more loss occurring during cold winters favourable for formation of polar stratospheric clouds (PSCs). We show that a positive, statistically significant rise in the local maxima of PSC formation potential (PFPLM) for cold winters is apparent in meteorological data collected over the past half century. Output from numerous General Circulation Models (GCMs) also exhibits positive trends in PFPLM over 1950 to 2100, with highest values occurring at end of century, for simulations driven by a large rise in the radiative forcing of climate from greenhouse gases (GHGs). We combine projections of stratospheric halogen loading and humidity with GCM-based forecasts of temperature to suggest that conditions favourable for large, seasonal loss of Arctic column O3 could persist or even worsen until the end of this century, if future abundances of GHGs continue to steeply rise., Despite a ban on ozone depleting substances, ozone depletion during cold winters in the Arctic stratosphere has been increasing in recent decades. Here, the authors show conditions favourable for Arctic ozone depletion could worsen as a response of stratospheric temperature and water to continued release of greenhouse gases.

We will present trace gas measurements obtained by the airborne imaging limb sounder GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) instrument that has been operated on the Geophysica research aircraft in area of the Indian subcontinent with basis in Kathmandu, Nepal during the StratoClim campaign in July/August 2017.We will show retrievals of two-dimensional trace-gas distributions derived from GLORIA observations in the UTLS (Upper Troposphere Lower Stratosphere) region during the Asian monsoon. Targeted gases are, amongst others, O3, HNO3, PAN, C2H2, and HCOOH. We will present an analysis of retrieval performance including diagnostics of spatial resolution and an estimated error budget. In our contribution, we compare these GLORIA measurements with results of the atmospheric models EMAC (ECHAM/MESSy Atmospheric Chemistry) and CAMS (Copernicus Atmosphere Monitoring Service) reanalysis and discuss the influence of non-methane volatile organic compound emissions by sensitivity simulations with the EMAC model. Using trajectories from the models ATLAS and TRACZILLA, measured pollution trace gas plumes are connected to possible sources of origin. Due to the high convective activity in the region of the Asian monsoon, both trajectory sets consider vertical transport by convection, however in a different manner. We show that there are very delicate structures of pollutant trace gases in the Asian monsoon UTLS, and that atmospheric models have difficulties in reproducing these structures, which is likely to be caused by insufficient vertical transport from convection in meteorological fields or by missing sources in the emission inventories used by the models.

Strong convection within the Asian monsoon system quickly transports polluted air masses from the boundary layer into the upper troposphere where secondary aerosol formation can take place. Here we present remote sensing observations by infrared limb sounding systems providing vertical and horizontal distributions of ammonia (NH3) and solid ammonium nitrate (AN) aerosol particles. Besides the identification of trace gases, characteristic signatures in the mid-infrared spectral region are used to infer information about composition and phase of the aerosol particles. We will show an analysis of AN and NH3 in the Asian monsoon upper troposphere from a combination of two satellite limb sounders, CRISTA on SPAS in August 1997 and MIPAS on Envisat, from 2002-2011.In addition, limb-imaging measurements obtained with the GLORIA instrument on board the Geophysica high-altitude aircraft provided the opportunity to obtain vertical cross sections along the flight path of AN aerosol mass and NH3 volume mixing ratios during the Asian monsoon field campaign of the StratoClim project in summer 2017. We analysed the airborne dataset with the help of trajectory calculations combined with temporally and locally connected satellite data of nadir-pointing instruments, like IASI, to infer the distribution of NH3 in the lower troposphere, as well as geostationary satellites to deduce the presence of convective influence.Further, we performed experiments at the AIDA cloud and aerosol chamber laboratory (a) to support the analysis of the aerosol infrared spectral signature in remote sensing, (b) to investigate the conditions leading to the unexpected solid phase of AN particles as well as, (c) to study their potential to act as ice nucleating particles.

We present a quantitative analysis of the chemical reactions involved in polar ozone depletion in the stratosphere and of the relevant reaction pathways and cycles. While the reactions involved in polar ozone depletion are well known, quantitative estimates of the importance of individual reactions or reaction cycles are rare. In particular, there is no comprehensive and quantitative study of the reaction rates and cycles averaged over the polar vortex under conditions of heterogeneous chemistry so far. We show time series of reaction rates averaged over the core of the polar vortex in winter and spring for all relevant reactions and indicate which reaction pathways and cycles are responsible for the vortex-averaged net change of the key species involved in ozone depletion, i.e., ozone, chlorine species (ClOx, HCl, ClONO2), bromine species, nitrogen species (HNO3, NOx) and hydrogen species (HOx). For clarity, we focus on one Arctic winter (2004–2005) and one Antarctic winter (2006) in a layer in the lower stratosphere around 54 hPa and show results for additional pressure levels and winters in the Supplement. Mixing ratios and reaction rates are obtained from runs of the ATLAS Lagrangian chemistry and transport model (CTM) driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis data. An emphasis is put on the partitioning of the relevant chemical families (nitrogen, hydrogen, chlorine, bromine and odd oxygen) and activation and deactivation of chlorine.

The Polar SWIFT model is a fast scheme for calculating the chemistry of stratospheric ozone depletion in polar winter. It is intended for use in global climate models (GCMs) and Earth system models (ESMs) to enable the simulation of mutual interactions between the ozone layer and climate. To date, climate models often use prescribed ozone fields, since a full stratospheric chemistry scheme is computationally very expensive. Polar SWIFT is based on a set of coupled differential equations, which simulate the polar vortex-averaged mixing ratios of the key species involved in polar ozone depletion on a given vertical level. These species are O3, chemically active chlorine (ClOx), HCl, ClONO2 and HNO3. The only external input parameters that drive the model are the fraction of the polar vortex in sunlight and the fraction of the polar vortex below the temperatures necessary for the formation of polar stratospheric clouds. Here, we present an update of the Polar SWIFT model introducing several improvements over the original model formulation. In particular, the model is now trained on vortex-averaged reaction rates of the ATLAS Chemistry and Transport Model, which enables a detailed look at individual processes and an independent validation of the different parameterizations contained in the differential equations. The training of the original Polar SWIFT model was based on fitting complete model runs to satellite observations and did not allow for this. A revised formulation of the system of differential equations is developed, which closely fits vortex-averaged reaction rates from ATLAS that represent the main chemical processes influencing ozone. In addition, a parameterization for the HNO3 change by denitrification is included. The rates of change of the concentrations of the chemical species of the Polar SWIFT model are purely chemical rates of change in the new version, whereas in the original Polar SWIFT model, they included a transport effect caused by the original training on satellite data. Hence, the new version allows for an implementation into climate models in combination with an existing stratospheric transport scheme. Finally, the model is now formulated on several vertical levels encompassing the vertical range in which polar ozone depletion is observed. The results of the Polar SWIFT model are validated with independent Microwave Limb Sounder (MLS) satellite observations and output from the original detailed chemistry model of ATLAS.

The rise of ammonia emissions in Asia is predicted to increase radiative cooling and air pollution by forming ammonium nitrate particles in the lower troposphere. There is, however, a severe lack of knowledge about ammonia and ammoniated aerosol particles in the upper troposphere and their possible effects on the formation of clouds. Here we employ satellite observations and high-altitude aircraft measurements, combined with atmospheric trajectory simulations and cloud-chamber experiments, to demonstrate the presence of ammonium nitrate particles and also track the source of the ammonia that forms into the particles. We found that during the Asian monsoon period, solid ammonium nitrate particles are surprisingly ubiquitous in the upper troposphere from the Eastern Mediterranean to the Western Pacific—even as early as in 1997. We show that this ammonium nitrate aerosol layer is fed by convection that transports large amounts of ammonia from surface sources into the upper troposphere. Impurities of ammonium sulfate allow the crystallization of ammonium nitrate even in the conditions, such as a high relative humidity, that prevail in the upper troposphere. Solid ammonium nitrate particles in the upper troposphere play a hitherto neglected role in ice cloud formation and aerosol indirect radiative forcing. Solid ammonium nitrate particles are formed in the upper troposphere during the Asian monsoons, which bring large amounts of ground ammonia to this altitude, according to integrated analyses of measurements on ammoniated aerosol, together with model simulations.

The Extrapolar SWIFT model is a fast ozone chemistry scheme for interactive calculation of the extrapolar stratospheric ozone layer in coupled general circulation models (GCMs). In contrast to the widely used prescribed ozone, the SWIFT ozone layer interacts with the model dynamics and can respond to atmospheric variability or climatological trends. The Extrapolar SWIFT model employs a repro-modelling approach, in which algebraic functions are used to approximate the numerical output of a full stratospheric chemistry and transport model (ATLAS). The full model solves a coupled chemical differential equation system with 55 initial and boundary conditions (mixing ratio of various chemical species and atmospheric parameters). Hence the rate of change of ozone over 24 h is a function of 55 variables. Using covariances between these variables, we can find linear combinations in order to reduce the parameter space to the following nine basic variables: latitude, pressure altitude, temperature, overhead ozone column and the mixing ratio of ozone and of the ozone-depleting families (Cly, Bry, NOy and HOy). We will show that these nine variables are sufficient to characterize the rate of change of ozone. An automated procedure fits a polynomial function of fourth degree to the rate of change of ozone obtained from several simulations with the ATLAS model. One polynomial function is determined per month, which yields the rate of change of ozone over 24 h. A key aspect for the robustness of the Extrapolar SWIFT model is to include a wide range of stratospheric variability in the numerical output of the ATLAS model, also covering atmospheric states that will occur in a future climate (e.g. temperature and meridional circulation changes or reduction of stratospheric chlorine loading). For validation purposes, the Extrapolar SWIFT model has been integrated into the ATLAS model, replacing the full stratospheric chemistry scheme. Simulations with SWIFT in ATLAS have proven that the systematic error is small and does not accumulate during the course of a simulation. In the context of a 10-year simulation, the ozone layer simulated by SWIFT shows a stable annual cycle, with inter-annual variations comparable to the ATLAS model. The application of Extrapolar SWIFT requires the evaluation of polynomial functions with 30–100 terms. Computers can currently calculate such polynomial functions at thousands of model grid points in seconds. SWIFT provides the desired numerical efficiency and computes the ozone layer 104 times faster than the chemistry scheme in the ATLAS CTM.

We present a Lagrangian convective transport scheme developed for Chemistry and Transport Models and ensemble trajectory simulations. Similar to existing schemes in other Lagrangian models, it is based on a statistical approach of calculating parcel displacements by convection. These schemes redistribute air parcels within a fixed time step by calculating probabilities for entrainment and the altitude of detrainment. Our scheme extends this approach by modelling vertical updraft velocities and the time that an air parcel spends inside the convective event, which is important for simulating the tropospheric chemistry of short-lived species, e.g. it determines the time available for heterogeneous processes on the surface of cloud droplets. Two different schemes for determining the vertical updraft velocities are introduced, which are based on constant or random convective area fraction profiles, respectively. SO2 is used as an example to show that there is a significant effect on species mixing ratios when modelling the time spent in convective updrafts compared to a nearly instantaneous redistribution of air parcels. The scheme is driven by convective mass fluxes and detrainment rates that originate from an external convective parameterization, which can be obtained from meteorological analysis data or General Circulation Models. Validation runs driven by ECMWF ERA Interim reanalysis data are performed with the scheme implemented into the ATLAS Chemistry and Transport Model. These include long-term global trajectory simulations of Radon-222 that are compared to measurements, and runs testing mass conservation and the reproduction of the convective mass fluxes and detrainment rates of ERA Interim. Simulated vertical updraft velocities are validated by wind profiler measurements in Darwin.

We examined observations of polar stratospheric clouds (PSCs) by CALIPSO and of HCl, ClO and HNO3 by MLS along air mass trajectories to investigate the dependence of the inferred PSC composition on the temperature history of the air parcels, and the dependence of the level of chlorine activation on PSC composition. Several case studies based on individual trajectories from the Arctic winter 2009/10 were conducted, with the trajectories chosen such that the first processing of the air mass by PSCs in this winter occurred on the trajectory. Transitions of PSC composition classes were observed to be highly dependent on the temperature history. In cases of a gradual temperature decrease, nitric acid trihydrate (NAT) and super-cooled ternary solution (STS) mixture clouds were observed. In cases of rapid temperature decrease, STS clouds were first observed, followed by NAT/STS mixture clouds. When temperatures dropped below the frost point, ice clouds formed, and then transformed into NAT/STS mixture clouds when temperature increased above the frost point. The threshold temperature for rapid chlorine activation on PSCs is approximately 4 K below the NAT existence temperature, TNAT. Furthermore, simulations of the ATLAS chemistry and transport box model along the trajectories were used to corroborate the measurements and show good agreement with the observations. Rapid chlorine activation was observed when an airmass encountered PSCs. The observed and modelled dependence of the rate of chlorine activation on the PSC composition class was small. Usually, chlorine activation was limited by the amount of available ClONO2. Where ClONO2 was not the limiting factor, a large dependence on temperature was evident.

The SWIFT model is a fast scheme for calculating the chemistry of stratospheric ozone depletion in polar winter. It is intended for use in Global Climate Models (GCMs) and Earth System Models (ESMs) to enable the simulation of interactions between the ozone layer and climate. So far, climate models often use prescribed ozone fields, since a full stratospheric chemistry scheme is computationally very expensive. SWIFT is based on a set of coupled differential equations, which simulate the polar vortex averaged mixing ratios of the key species involved in polar ozone depletion on a given vertical level. These species are O3, active chlorine (ClOx), HCl, ClONO2 and HNO3. The only external input parameters that drive the model are the fraction of the polar vortex in sunlight and the fraction of the polar vortex below the temperatures necessary for the formation of polar stratospheric clouds. Here, we present an update of the SWIFT model introducing several improvements over the original model formulation. In particular, the model is now trained on vortex averaged reaction rates of the ATLAS Chemistry and Transport Model, which enables a detailed look at single processes and an independent validation of the different parameterizations for the single processes contained in the differential equations. The training of the original SWIFT model was based on fitting complete model runs to satellite observations and did not allow this. A revised formulation of the system of differential equations is developed, which closely fits vortex averaged reaction rates from ATLAS that represent the main chemical processes influencing ozone. In addition, a parameterization for the HNO3 change by denitrification is included. The rates of change of the concentrations of the chemical species of the SWIFT model are purely chemical rates of change in the new version, while the rates of change in the original SWIFT version included a transport effect caused by the original training on satellite data. Hence, the new version allows for an implementation into climate models in combination with an existing stratospheric transport scheme. Finally, the model is now formulated on several vertical levels encompassing the vertical range in which polar ozone depletion is observed. The results of the SWIFT model are validated with independent MLS satellite observations and the results of the original detailed chemistry model of ATLAS.

We present a quantitative analysis of the chemical reactions involved in polar ozone depletion in the stratosphere, and of the relevant reaction pathways and cycles. While the reaction pathways and cycles involved in polar ozone depletion are well known, quantitative estimates of the importance of single reactions or reaction cycles are rare. In particular, there is no comprehensive and quantitative study of the reaction rates and cycles averaged over the polar vortex under conditions of heterogeneous chemistry so far. We show time series of reaction rates averaged over the polar vortex in winter and spring for all relevant reactions and indicate which reaction pathways and cycles are responsible for the vortex-averaged net change of the key species involved in ozone depletion, that is ozone, chlorine species (ClOx, HCl, ClONO2), bromine species, nitrogen species (HNO3, NOx) and hydrogen species (HOx). For clarity, we focus on one Arctic winter (2004/2005) and one Antarctic winter (2006) in a layer in the lower stratosphere around 54 hPa. Mixing ratios and reaction rates are obtained from runs of the ATLAS Chemistry and Transport Model driven by ECMWF ERA Interim reanalysis data. An emphasis is put on the partitioning of the relevant chemical families (nitrogen, hydrogen, chlorine, bromine and odd oxygen) and activation and deactivation of chlorine.

An extremely fast model to estimate the degree of stratospheric ozone depletion during polar winters is described. It is based on a set of coupled differential equations that simulate the seasonal evolution of vortex-averaged hydrogen chloride (HCl), nitric acid (HNO3), chlorine nitrate (ClONO2), active forms of chlorine (ClOx = Cl + ClO + 2 ClOOCl) and ozone (O3) on isentropic levels within the polar vortices. Terms in these equations account for the chemical and physical processes driving the time rate of change of these species. Eight empirical fit coefficients associated with these terms are derived by iteratively fitting the equations to vortex-averaged satellite-based measurements of HCl, HNO3 and ClONO2 and observationally derived ozone loss rates. The system of differential equations is not stiff and can be solved with a time step of one day, allowing many years to be processed per second on a standard PC. The inputs required are the daily fractions of the vortex area covered by polar stratospheric clouds and the fractions of the vortex area exposed to sunlight. The resultant model, SWIFT (Semi-empirical Weighted Iterative Fit Technique), provides a fast yet accurate method to simulate ozone loss rates in polar regions. SWIFT's capabilities are demonstrated by comparing measured and modeled total ozone loss outside of the training period.

[1] The link between stratospheric ozone decline and ultraviolet (UV) radiation increase at the Earth's surface is well established. In the Northern Hemisphere extratropics, stratospheric ozone is accumulated from autumn to spring as a result of transport from its source region in the tropics. The amount of accumulated ozone varies from year to year due to natural dynamical variability and chemical destruction by natural and anthropogenic substances. Observational and modeling studies show that these total ozone anomalies persist in the extratropics from spring to summer. Here we analyze time series of ground-based UV measurements and satellite retrievals of total ozone and UV radiation and demonstrate that there is a strong link between springtime total ozone and summer UV anomalies in the Northern Hemisphere extratropics. In some regions, the interannual variability in springtime ozone abundance explains 20–40% of the summer UV variability, and this relation can be used for improving seasonal UV forecasts. Using chemistry transport models, we estimate the influence of polar chemical ozone loss on the summer UV north of 35°N. We estimate that the massive Arctic ozone depletion 2011 increased the March–August cumulative erythemal clear-sky UV dose in the Northern Hemisphere extratropics by 3–4% compared to the climatology, with about 75% of the increase accumulated after the breakup of the polar vortex. This result strongly suggests that the effect of seasonal ozone anomaly persistence should be included in the assessment of the impacts of polar ozone losses.

Early winter ozone mixing ratios in the Arctic middle stratosphere show an interannual variability of about 10%. We show that ozone variability in early January is caused by dynamical processes during Arctic polar vortex formation in autumn (September to December). Observational data from satellites and ozone sondes are used in conjunction with simulations of the chemistry and transport model ATLAS to examine the relationship between the meridional and vertical origin of air enclosed in the polar vortex and its ozone amount. For this, we use a set of artificial model tracers to deduce the origin of the air masses in the vortex in January in latitude and altitude in September. High vortex mean ozone mixing ratios are correlated with a high fraction of air from low latitudes enclosed in the vortex and a high fraction of air that experienced small net subsidence (in a Lagrangian sense). As a measure for the strength of the Brewer-Dobson circulation and meridional mixing in autumn, we use the Eliassen-Palm flux through the mid-latitude tropopause averaged from September to November. In the lower stratosphere, this quantity correlates well with the origin of air enclosed in the vortex and reasonably well with the ozone amount in early winter.

Dynamical processes during the formation phase of the Arctic stratospheric vortex in autumn (from September to December) can introduce considerable interannual variability in the amount of ozone that is incorporated into the vortex. Chemistry in autumn tends to remove part of this variability because ozone relaxes towards equilibrium. As a quantitative measure of how important dynamical variability during vortex formation is for the winter ozone abundances above the Arctic we analyze which fraction of an ozone anomaly induced during vortex formation persists until early winter (3 January). The work is based on the Lagrangian Chemistry Transport Model ATLAS. In a case study, model runs for the winter 1999–2000 are used to assess the fate of an ozone anomaly artificially introduced during the vortex formation phase on 16 September. In addition, runs with reduced resolution explore the sensitivity of the results to interannual changes in transport, mixing, temperatures and NOx. The runs provide information about the persistence of the induced ozone anomaly as a function of time, potential temperature and latitude. The induced ozone anomaly survives longer inside the polar vortex than outside the vortex. Half of the initial perturbation survives until 3 January at 550 K inside the polar vortex, with a rapid fall off towards higher levels, mainly due to NOx induced chemistry. Above 750 K the signal falls to values below 0.5%. Hence, dynamically induced ozone variability from the early vortex formation phase cannot significantly contribute to early winter variability above 750 K. At lower levels increasingly larger fractions of the initial perturbation survive, reaching 90% at 450 K. In this vertical range dynamical processes during the vortex formation phase are crucial for the ozone abundance in early winter.

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.

Chemical ozone destruction occurs over both polar regions in local winter–spring. In the Antarctic, essentially complete removal of lower-stratospheric ozone currently results in an ozone hole every year, whereas in the Arctic, ozone loss is highly variable and has until now been much more limited. Here we demonstrate that chemical ozone destruction over the Arctic in early 2011 was—for the first time in the observational record—comparable to that in the Antarctic ozone hole. Unusually long-lasting cold conditions in the Arctic lower stratosphere led to persistent enhancement in ozone-destroying forms of chlorine and to unprecedented ozone loss, which exceeded 80 per cent over 18–20 kilometres altitude. Our results show that Arctic ozone holes are possible even with temperatures much milder than those in the Antarctic. We cannot at present predict when such severe Arctic ozone depletion may be matched or exceeded. Since its emergence in the 1980s, the Antarctic ozone hole, the near-complete loss of lower-stratospheric ozone, has occurred every year. The possibility that a similar effect might occur in the Northern Hemisphere has been debated, but despite considerable variation in ozone levels in the Arctic, they had not reached the extremes seen in the south. Until this year. Observations made in the late winter and early spring of 2011 reveal ozone loss far outside the range previously observed over the Northern Hemisphere, comparable to some Antarctic ozone holes. The formation of the hole was driven by an unusually long cold snap and a high level of ozone-destroying chlorine. Although this effect is dramatic, it is difficult to predict whether similar Arctic ozone holes will develop in future.

ATLAS is a new global Lagrangian Chemistry and Transport Model (CTM), which includes a stratospheric chemistry scheme with 46 active species, 171 reactions, heterogeneous chemistry on polar stratospheric clouds and a Lagrangian denitrification module. Lagrangian (trajectory-based) models have several important advantages over conventional Eulerian models, including the absence of spurious numerical diffusion, efficient code parallelization and no limitation of the largest time step by the Courant-Friedrichs-Lewy criterion. This work describes and validates the stratospheric chemistry scheme of the model. Stratospheric chemistry is simulated with ATLAS for the Arctic winter 1999/2000, with a focus on polar ozone depletion and denitrification. The simulations are used to validate the chemistry module in comparison with measurements of the SOLVE/THESEO 2000 campaign. A Lagrangian denitrification module, which is based on the simulation of the nucleation, sedimentation and growth of a large number of polar stratospheric cloud particles, is used to model the substantial denitrification that occured in this winter.