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Ozone trends in the upper troposphere and lower stratosphere (UTLS) remain highly uncertain because of sharp spatial gradients and high variability caused by competing transport, chemical, and mixing processes near the upper-tropospheric jets and extratropical tropopause as well as inhomogeneous spatially and temporally limited observations of the region. Subtropical jets and the tropopause act as transport barriers, delineating boundaries between atmospheric regimes controlled by different processes; they can thus be used to separate data taken in those different regimes for numerous purposes, including trend assessment. As part of the Observed Composition Trends And Variability in the UTLS (OCTAV-UTLS) Stratosphere-troposphere Processes And their Role in Climate (SPARC) activity, we assess the effectiveness of several coordinate systems in segregating air into different atmospheric regimes. To achieve this, a comprehensive dynamical dataset is used to reference every measurement from various observing systems to the locations of jets and tropopauses in different coordinates (e.g., altitude, pressure, potential temperature, latitude, and equivalent latitude). We assess which coordinate combinations are most useful for dividing the measurements into bins such that the data in each bin are affected by the same processes, thus minimizing the variability induced when combining measurements from different dynamical regimes, each characterized by different physical processes. Such bins will be particularly suitable for combining measurements with different sampling characteristics and for assessing trends and attributing them to changing atmospheric dynamics. Overall, the use of equivalent latitude and potential temperature leads to the most substantial reduction in binned variability across the UTLS. This coordinate pairing uses potential vorticity (PV) on isentropic surfaces, thus aligning with the adiabatic transport of tracers.

Haze events in the North China Plain (NCP) and a decline in ozone levels in Southern Coast China (SC) from 21 January to 9 February 2020 during the COVID-19 lockdown have attracted public curiosity and scholarly attention. Most previous studies focused on the impact of atmospheric chemistry processes associated with anomalous weather elements in these cases, but fewer studies quantified the impact of various weather elements within the context of a specific weather pattern. To identify the weather patterns responsible for inducing this unexpected situation and to further quantify the importance of different meteorological factors during the haze event, two approaches are employed. These approaches implemented the comparisons of observations in 2020 with climatology averaged over the years 2015–2019 with a novel structural SOM (self-organising map) model and with the prediction of the “business as usual” (hereafter referred to as BAU) emission strength by the GBM (gradient-boosting machine) model, respectively. The results reveal that the unexpected PM2.5 pollution and O3 decline from the climatology in NCP and SC could be effectively explained by the presence of a double-centre high-pressure system across China. Moreover, the GBM results provided a quantitative assessment of the importance of each meteorological factor in driving the predictions of PM2.5 and O3 under the specific weather system. These results indicate that temperature played the most crucial role in the haze event in NCP, as well as in the O3 change in SC. This valuable information will ultimately contribute to our ability to predict air pollution under future emission scenarios and changing weather patterns that may be influenced by climate change.

Sudden stratospheric warmings (SSWs) are abrupt disturbances to the Northern Hemisphere wintertime stratospheric polar vortex that can lead to pronounced regional changes in surface temperature and precipitation. SSWs also strongly impact the distribution of chemical constituents within the stratosphere, but the implications of these changes for stratosphere–troposphere exchange (STE) and radiative effects in the upper troposphere–lower stratosphere (UTLS) have not been extensively studied. Here we show, based on a specified-dynamics simulations from the European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) chemistry–climate model, that SSWs lead to a pronounced increase in high-latitude ozone just above the tropopause (>25 % relative to climatology), persisting for up to 50 d for the ∼50 % of events classified as downward propagating following Hitchcock et al. (2013). This anomalous feature in lowermost-stratospheric ozone is verified from ozone sonde soundings and using the Copernicus Atmospheric Monitoring Service (CAMS) atmospheric composition reanalysis product. A significant dipole anomaly (>± 25 %) in water vapour also persists in this region for up to 75 d, with a drying signal above a region of moistening, also evident within the CAMS reanalysis. An enhancement in STE leads to a significant 5 %–10 % increase in near-surface ozone of stratospheric origin over the Arctic, with a typical time lag between 20 and 80 d. The signal also propagates to mid-latitudes, leading to significant enhancements in UTLS ozone and also, with weakened strength, in free tropospheric and near-surface ozone up to 90 d after the event. In quantifying the potential significance for surface air quality breaches above ozone regulatory standards, a risk enhancement of up to a factor of 2 to 3 is calculated following such events. The chemical composition perturbations in the Arctic UTLS result in radiatively driven Arctic stratospheric temperature changes of around 2 K. An idealized sensitivity evaluation highlights the changing radiative importance of both ozone and water vapour perturbations with seasonality. Our results highlight that, whilst any background increase in near-surface ozone due to SSW-related stratosphere-to-troposphere (STT) transport is likely to be small, this could be of greater importance locally (e.g. mountainous regions more susceptible to elevated ozone levels). Accurate representation of UTLS composition (namely ozone and water vapour), through its effects on local temperatures, may also help improve numerical weather prediction forecasts on sub-seasonal to seasonal timescales.

Ozone trend estimates have shown large uncertainties in the upper troposphere–lower stratosphere (UTLS) region despite multi-decadal observations available from ground-based, balloon, aircraft, and satellite platforms. These uncertainties arise from large natural variability driven by dynamics (reflected in tropopause and jet variations) as well as the strength in constituent transport and mixing. Additionally, despite all the community efforts there is still a lack of representative high-quality global UTLS measurements to capture this variability. The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Observed Composition Trends and Variability in the UTLS (OCTAV-UTLS) activity aims to reduce uncertainties in UTLS composition trend estimates by accounting for this dynamically induced variability. In this paper, we describe the production of dynamical diagnostics using meteorological information from reanalysis fields that facilitate mapping observations from several platforms into numerous geophysically based coordinates (including tropopause and upper tropospheric jet relative coordinates). Suitable coordinates should increase the homogeneity of the air masses analyzed together, thus reducing the uncertainty caused by spatiotemporal sampling biases in the quantification of UTLS composition trends. This approach thus provides a framework for comparing measurements with diverse sampling patterns and leverages the meteorological context to derive maximum information on UTLS composition and trends and its relationships to dynamical variability. The dynamical diagnostics presented here are the first comprehensive set describing the meteorological context for multi-decadal observations by ozonesondes, lidar, aircraft, and satellite measurements in order to study the impact of dynamical processes on observed UTLS trends by different sensors on different platforms. Examples using these diagnostics to map multi-platform datasets into different geophysically based coordinate systems are provided. The diagnostics presented can also be applied to analysis of greenhouse gases other than ozone that are relevant to surface climate and UTLS chemistry.

The methane chemical sink estimated by atmospheric chemistry models (bottom-up method) is significantly larger than estimates based on methyl chloroform (MCF) inversions (top-down method). The difference is partly attributable to large uncertainties in hydroxyl radical (OH) concentrations simulated by the atmospheric chemistry models used to derive the bottom-up estimates. In this study, we propose a new approach based on OH precursor observations and a chemical box model. This approach contributes to improving the 3D distributions of tropospheric OH radicals obtained from atmospheric chemistry models and reconciling bottom-up and top-down estimates of the chemical loss of atmospheric methane. By constraining simulated OH precursors with observations, the global mean tropospheric column-averaged air-mass-weighted OH concentration ([OH]trop-M) is ∼10×105 molec. cm−3 (which is 2×105 molec. cm−3 lower than the original model-simulated global [OH]trop-M) and agrees with that obtained by the top-down method based on MCF inversions. With OH constrained by precursor observations, the methane chemical loss is 471–508 Tg yr−1, averaged from 2000 to 2009. The new adjusted estimate is in the range of the latest top-down estimate of the Global Carbon Project (GCP) (459–516 Tg yr−1), contrary to the bottom-up estimates that use the original model-simulated OH fields (577–612 Tg yr−1). The overestimation of global [OH]trop-M and methane chemical loss simulated by the atmospheric chemistry models is caused primarily by the models' underestimation of carbon monoxide and total ozone column, and overestimation of nitrogen dioxide. Our results highlight that constraining the model-simulated OH fields with available OH precursor observations can help improve bottom-up estimates of the global methane sink.

The quasi-biennial oscillation (QBO) is a major mode of climate variability in the tropical stratosphere with quasi-periodically descending westerly and easterly winds, modulating transport and distributions of key greenhouse gases such as water vapour and ozone. In 2016 and 2020, anomalous QBO easterlies disrupted the QBO's mean period of about 28 months previously observed. Here, we quantify the impact of these two QBO disruption events on the Brewer–Dobson circulation and respective distributions of water vapour and ozone using the ERA5 reanalysis and Microwave Limb Sounder (MLS) satellite observations, respectively. In 2016, both water vapour and ozone in the lower stratosphere decreased globally during the QBO disruption event by up to about 20 %. In 2020, the lower-stratospheric ozone only weakly decreased during the QBO disruption event, by up to about 10 %, while the lower-stratospheric water vapour increased by up to about 15 %. These dissimilarities in the anomalous circulation and the related ozone response between the year 2016 and the year 2020 result from differences in the tropical upwelling and in the secondary circulation of the QBO caused by differences in anomalous planetary and gravity wave breaking in the lower stratosphere near the equatorward upper flanks of the subtropical jet. The anomalous planetary and gravity wave breaking was stronger in the lower stratosphere between the tropopause and the altitude of about 23 km during the QBO disruption events in 2016 than in 2020. However, the differences in the response of lower-stratospheric water vapour to the QBO disruption events between the year 2016 and the year 2020 are mainly due to the differences in cold-point temperatures induced by Australian wildfire, which moistened the lower stratosphere, thereby obscuring the impact of the QBO disruption event in 2020 on water vapour in the lower stratosphere. Our results highlight the need for a better understanding of the causes of the QBO disruption, their interplay with other modes of climate variability in the Indo-Pacific region, including the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), and their impacts on water vapour and ozone in the upper troposphere/lower stratosphere in the face of a changing climate.

The stratospheric meridional overturning circulation, also referred to as the Brewer–Dobson circulation (BDC), controls the composition of the stratosphere, which, in turn, affects radiation and climate. As the BDC cannot be directly measured, one has to infer its strength and trends indirectly. For instance, trace gas measurements allow the calculation of average transit times. Satellite measurements provide information on the distributions of trace gases for the entire stratosphere, with measurements of particularly long temporal and dense spatial coverage available for stratospheric water vapour (H2O). Although chemical processes and boundary conditions confound interpretation, the influence of methane (CH4) oxidation on H2O in the stratosphere is relatively straightforward, and thus H2O is an appealing tracer for transport analysis despite these caveats. In this work, we explore how mean age of air trends can be estimated from the combination of stratospheric H2O and CH4 data, by carrying out a proof of concept within the model environment of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In particular, we assess the methodological uncertainties related to the two commonly used approximations of (i) instantaneous stratospheric entry mixing ratio propagation and (ii) constant correlation between mean age and the fractional release factor of CH4. Performing various sensitivity studies with CLaMS, we test different methods of the mean age of air trend estimation, and we aim to provide simple and practical advice on the adjustment of the used approximations for obtaining more reliable mean age of air trends from the measurements of H2O and CH4. Our results show that the estimated mean age of air trends from the combination of stratospheric H2O and CH4 changes may be significantly affected by the assumed approximations. Depending on the investigated stratospheric region and the considered period, the error in estimated mean age of air trends can be large, especially in the lower stratosphere. For particular periods, the errors from the two approximations can lead to opposite effects, which may even cancel out. Finally, for a more reliable estimate of the mean age of air trends, we propose adjusting the approximation method by using an idealized age spectrum to propagate stratospheric entry mixing ratios. The findings of this work can be used for assessing the uncertainties in stratospheric BDC trend estimation from global satellite measurements.

The Stratosphere-troposphere Processes and their Role in Climate (SPARC) Data Initiative (SPARC, 2017) performed the first comprehensive assessment of currently available stratospheric composition measurements obtained from an international suite of space-based limb sounders. The initiative's main objectives were (1) to assess the state of data availability, (2) to compile time series of vertically resolved, zonal monthly mean trace gas and aerosol fields, and (3) to perform a detailed intercomparison of these time series, summarizing useful information and highlighting differences among datasets. The datasets extend over the region from the upper troposphere to the lower mesosphere (300–0.1 hPa) and are provided on a common latitude–pressure grid. They cover 26 different atmospheric constituents including the stratospheric trace gases of primary interest, ozone (O3) and water vapor (H2O), major long-lived trace gases (SF6, N2O, HF, CCl3F, CCl2F2, NOy), trace gases with intermediate lifetimes (HCl, CH4, CO, HNO3), and shorter-lived trace gases important to stratospheric chemistry including nitrogen-containing species (NO, NO2, NOx, N2O5, HNO4), halogens (BrO, ClO, ClONO2, HOCl), and other minor species (OH, HO2, CH2O, CH3CN), and aerosol. This overview of the SPARC Data Initiative introduces the updated versions of the SPARC Data Initiative time series for the extended time period 1979–2018 and provides information on the satellite instruments included in the assessment: LIMS, SAGE I/II/III, HALOE, UARS-MLS, POAM II/III, OSIRIS, SMR, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, SMILES, and OMPS-LP. It describes the Data Initiative's top-down climatological validation approach to compare stratospheric composition measurements based on zonal monthly mean fields, which provides upper bounds to relative inter-instrument biases and an assessment of how well the instruments are able to capture geophysical features of the stratosphere. An update to previously published evaluations of O3 and H2O monthly mean time series is provided. In addition, example trace gas evaluations of methane (CH4), carbon monoxide (CO), a set of nitrogen species (NO, NO2, and HNO3), the reactive nitrogen family (NOy), and hydroperoxyl (HO2) are presented. The results highlight the quality, strengths and weaknesses, and representativeness of the different datasets. As a summary, the current state of our knowledge of stratospheric composition and variability is provided based on the overall consistency between the datasets. As such, the SPARC Data Initiative datasets and evaluations can serve as an atlas or reference of stratospheric composition and variability during the “golden age” of atmospheric limb sounding. The updated SPARC Data Initiative zonal monthly mean time series for each instrument are publicly available and accessible via the Zenodo data archive (Hegglin et al., 2020).

Decadal trends and interannual variations in the hydroxyl radical (OH), while poorly constrained at present, are critical for understanding the observed evolution of atmospheric methane (CH4). Through analyzing the OH fields simulated by the model ensemble of the Chemistry–Climate Model Initiative (CCMI), we find (1) the negative OH anomalies during the El Niño years mainly corresponding to the enhanced carbon monoxide (CO) emissions from biomass burning and (2) a positive OH trend during 1980–2010 dominated by the elevated primary production and the reduced loss of OH due to decreasing CO after 2000. Both two-box model inversions and variational 4D inversions suggest that ignoring the negative anomaly of OH during the El Niño years leads to a large overestimation of the increase in global CH4 emissions by up to 10 ± 3 Tg yr−1 to match the observed CH4 increase over these years. Not accounting for the increasing OH trends given by the CCMI models leads to an underestimation of the CH4 emission increase by 23 ± 9 Tg yr−1 from 1986 to 2010. The variational-inversion-estimated CH4 emissions show that the tropical regions contribute most to the uncertainties related to OH. This study highlights the significant impact of climate and chemical feedbacks related to OH on the top-down estimates of the global CH4 budget.

The hydroxyl radical (OH), which is the dominant sink of methane (CH4), plays a key role in closing the global methane budget. Current top-down estimates of the global and regional CH4 budget using 3D models usually apply prescribed OH fields and attribute model–observation mismatches almost exclusively to CH4 emissions, leaving the uncertainties due to prescribed OH fields less quantified. Here, using a variational Bayesian inversion framework and the 3D chemical transport model LMDz, combined with 10 different OH fields derived from chemistry–climate models (Chemistry–Climate Model Initiative, or CCMI, experiment), we evaluate the influence of OH burden, spatial distribution, and temporal variations on the global and regional CH4 budget. The global tropospheric mean CH4-reaction-weighted [OH] ([OH]GM-CH4) ranges 10.3–16.3×105 molec cm−3 across 10 OH fields during the early 2000s, resulting in inversion-based global CH4 emissions between 518 and 757  Tg yr−1. The uncertainties in CH4 inversions induced by the different OH fields are similar to the CH4 emission range estimated by previous bottom-up syntheses and larger than the range reported by the top-down studies. The uncertainties in emissions induced by OH are largest over South America, corresponding to large inter-model differences of [OH] in this region. From the early to the late 2000s, the optimized CH4 emissions increased by 22±6  Tg yr−1 (17–30  Tg yr−1), of which ∼25  % (on average) offsets the 0.7  % (on average) increase in OH burden. If the CCMI models represent the OH trend properly over the 2000s, our results show that a higher increasing trend of CH4 emissions is needed to match the CH4 observations compared to the CH4 emission trend derived using constant OH. This study strengthens the importance of reaching a better representation of OH burden and of OH spatial and temporal distributions to reduce the uncertainties in the global and regional CH4 budgets.

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project.

The modeling study presented here aims to estimate how uncertainties in global hydroxyl radical (OH) distributions, variability, and trends may contribute to resolving discrepancies between simulated and observed methane (CH4) changes since 2000. A multi-model ensemble of 14 OH fields was analyzed and aggregated into 64 scenarios to force the offline atmospheric chemistry transport model LMDz (Laboratoire de Meteorologie Dynamique) with a standard CH4 emission scenario over the period 2000–2016. The multi-model simulated global volume-weighted tropospheric mean OH concentration ([OH]) averaged over 2000–2010 ranges between 8.7×105 and 12.8×105 molec cm−3. The inter-model differences in tropospheric OH burden and vertical distributions are mainly determined by the differences in the nitrogen oxide (NO) distributions, while the spatial discrepancies between OH fields are mostly due to differences in natural emissions and volatile organic compound (VOC) chemistry. From 2000 to 2010, most simulated OH fields show an increase of 0.1–0.3×105 molec cm−3 in the tropospheric mean [OH], with year-to-year variations much smaller than during the historical period 1960–2000. Once ingested into the LMDz model, these OH changes translated into a 5 to 15 ppbv reduction in the CH4 mixing ratio in 2010, which represents 7 %–20 % of the model-simulated CH4 increase due to surface emissions. Between 2010 and 2016, the ensemble of simulations showed that OH changes could lead to a CH4 mixing ratio uncertainty of >±30 ppbv. Over the full 2000–2016 time period, using a common state-of-the-art but nonoptimized emission scenario, the impact of [OH] changes tested here can explain up to 54 % of the gap between model simulations and observations. This result emphasizes the importance of better representing OH abundance and variations in CH4 forward simulations and emission optimizations performed by atmospheric inversions.

We have derived values of the ultraviolet index (UVI) at solar noon using the Tropospheric Ultraviolet Model (TUV) driven by ozone, temperature and aerosol fields from climate simulations of the first phase of the Chemistry-Climate Model Initiative (CCMI-1). Since clouds remain one of the largest uncertainties in climate projections, we simulated only the clear-sky UVI. We compared the modelled UVI climatologies against present-day climatological values of UVI derived from both satellite data (the OMI-Aura OMUVBd product) and ground-based measurements (from the NDACC network). Depending on the region, relative differences between the UVI obtained from CCMI/TUV calculations and the ground-based measurements ranged between −5.9 % and 10.6 %. We then calculated the UVI evolution throughout the 21st century for the four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0 and 8.5). Compared to 1960s values, we found an average increase in the UVI in 2100 (of 2 %–4 %) in the tropical belt (30∘ N–30∘ S). For the mid-latitudes, we observed a 1.8 % to 3.4 % increase in the Southern Hemisphere for RCPs 2.6, 4.5 and 6.0 and found a 2.3 % decrease in RCP 8.5. Higher increases in UVI are projected in the Northern Hemisphere except for RCP 8.5. At high latitudes, ozone recovery is well identified and induces a complete return of mean UVI levels to 1960 values for RCP 8.5 in the Southern Hemisphere. In the Northern Hemisphere, UVI levels in 2100 are higher by 0.5 % to 5.5 % for RCPs 2.6, 4.5 and 6.0 and they are lower by 7.9 % for RCP 8.5. We analysed the impacts of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) on UVI from 1960 by comparing CCMI sensitivity simulations (1960–2100) with fixed GHGs or ODSs at their respective 1960 levels. As expected with ODS fixed at their 1960 levels, there is no large decrease in ozone levels and consequently no sudden increase in UVI levels. With fixed GHG, we observed a delayed return of ozone to 1960 values, with a corresponding pattern of change observed on UVI, and looking at the UVI difference between 2090s values and 1960s values, we found an 8 % increase in the tropical belt during the summer of each hemisphere. Finally we show that, while in the Southern Hemisphere the UVI is mainly driven by total ozone column, in the Northern Hemisphere both total ozone column and aerosol optical depth drive UVI levels, with aerosol optical depth having twice as much influence on the UVI as total ozone column does.

The stratospheric contribution to tropospheric ozone (O3) has been a subject of much debate in recent decades but is known to have an important influence. Recent improvements in diagnostic and modelling tools provide new evidence that the stratosphere has a much larger influence than previously thought. This study aims to characterise the seasonal and geographical distribution of tropospheric ozone, its variability, and its changes and provide quantification of the stratospheric influence on these measures. To this end, we evaluate hindcast specified-dynamics chemistry–climate model (CCM) simulations from the European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model and the Canadian Middle Atmosphere Model (CMAM), as contributed to the International Global Atmospheric Chemistry – Stratosphere-troposphere Processes And their Role in Climate (IGAC-SPARC) (IGAC–SPARC) Chemistry Climate Model Initiative (CCMI) activity, together with satellite observations from the Ozone Monitoring Instrument (OMI) and ozone-sonde profile measurements from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) over a period of concurrent data availability (2005–2010). An overall positive, seasonally dependent bias in 1000–450 hPa (∼0–5.5 km) sub-column ozone is found for EMAC, ranging from 2 to 8 Dobson units (DU), whereas CMAM is found to be in closer agreement with the observations, although with substantial seasonal and regional variation in the sign and magnitude of the bias (∼±4 DU). Although the application of OMI averaging kernels (AKs) improves agreement with model estimates from both EMAC and CMAM as expected, comparisons with ozone-sondes indicate a positive ozone bias in the lower stratosphere in CMAM, together with a negative bias in the troposphere resulting from a likely underestimation of photochemical ozone production. This has ramifications for diagnosing the level of model–measurement agreement. Model variability is found to be more similar in magnitude to that implied from ozone-sondes in comparison with OMI, which has significantly larger variability. Noting the overall consistency of the CCMs, the influence of the model chemistry schemes and internal dynamics is discussed in relation to the inter-model differences found. In particular, it is inferred that CMAM simulates a faster and shallower Brewer–Dobson circulation (BDC) compared to both EMAC and observational estimates, which has implications for the distribution and magnitude of the downward flux of stratospheric ozone over the most recent climatological period (1980–2010). Nonetheless, it is shown that the stratospheric influence on tropospheric ozone is significant and is estimated to exceed 50 % in the wintertime extratropics, even in the lower troposphere. Finally, long-term changes in the CCM ozone tracers are calculated for different seasons. An overall statistically significant increase in tropospheric ozone is found across much of the world but particularly in the Northern Hemisphere and in the middle to upper troposphere, where the increase is on the order of 4–6 ppbv (5 %–10 %) between 1980–1989 and 2001–2010. Our model study implies that attribution from stratosphere–troposphere exchange (STE) to such ozone changes ranges from 25 % to 30 % at the surface to as much as 50 %–80 % in the upper troposphere–lower stratosphere (UTLS) across some regions of the world, including western Eurasia, eastern North America, the South Pacific and the southern Indian Ocean. These findings highlight the importance of a well-resolved stratosphere in simulations of tropospheric ozone and its implications for the radiative forcing, air quality and oxidation capacity of the troposphere.

The stratospheric circulation determines the transport and lifetime of key trace gases in a changing climate, including water vapor and ozone, which radiatively impact surface climate. The unusually warm El Niño–Southern Oscillation (ENSO) event aligned with a disrupted Quasi-Biennial Oscillation (QBO) caused an unprecedented perturbation to this circulation in 2015–2016. Here, we quantify the impact of the alignment of these two phenomena in 2015–2016 on lower stratospheric water vapor and ozone from satellite observations. We show that the warm ENSO event substantially increased water vapor and decreased ozone in the tropical lower stratosphere. The QBO disruption significantly decreased global lower stratospheric water vapor and tropical ozone from early spring to late autumn. Thus, this QBO disruption reversed the lower stratosphere moistening triggered by the alignment of the warm ENSO event with westerly QBO in early boreal winter. Our results suggest that the interplay of ENSO events and QBO phases will be crucial for the distributions of radiatively active trace gases in a changing future climate, when increasing El Niño-like conditions and a decreasing lower stratospheric QBO amplitude are expected.

>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.

Stratospheric transport in global circulation models and chemistry–climate models is an important component in simulating the recovery of the ozone layer as well as changes in the climate system. The Brewer–Dobson circulation is not well constrained by observations and further investigation is required to resolve uncertainties related to the mechanisms driving the circulation. This study has assessed the specified dynamics mode of the Canadian Middle Atmosphere Model (CMAM30) by comparing to the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) profile measurements of CFC-11 (CCl3F), CFC-12 (CCl2F2), and N2O. In the CMAM30 specified dynamics simulation, the meteorological fields are nudged using the ERA-Interim reanalysis and a specified tracer was employed for each species, with hemispherically defined surface measurements used as the boundary condition. A comprehensive sampling technique along the line of sight of the ACE-FTS measurements has been utilized to allow for direct comparisons between the simulated and measured tracer concentrations. The model consistently overpredicts tracer concentrations of CFC-11, CFC-12, and N2O in the lower stratosphere, particularly in the northern hemispheric winter and spring seasons. The three mixing barriers investigated, including the polar vortex, the extratropical tropopause, and the tropical pipe, show that there are significant inconsistencies between the measurements and the simulations. In particular, the CMAM30 simulation underpredicts mixing efficiency in the tropical lower stratosphere during the June–July–August season.

Reanalysis data sets are widely used to understand atmospheric processes and past variability, and are often used to stand in as "observations" for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. In this paper, we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. We also provide a systematic documentation of the treatment of WV and O3 in current reanalyses to aid future research and guide the interpretation of differences amongst reanalysis fields.The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. However, significant biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses.In contrast to O3, reanalysis estimates of stratospheric WV are not directly constrained by assimilated data. Observations of atmospheric humidity are typically used only in the troposphere, below a specified vertical level at or near the tropopause. The fidelity of reanalysis stratospheric WV products is therefore mainly dependent on the reanalyses' representation of the physical drivers that influence stratospheric WV, such as temperatures in the tropical tropopause layer, methane oxidation, and the stratospheric overturning circulation. The lack of assimilated observations and known deficiencies in the representation of stratospheric transport in reanalyses result in much poorer agreement amongst observational and reanalysis estimates of stratospheric WV. Hence, stratospheric WV products from the current generation of reanalyses should generally not be used in scientific studies.

The representation of upper tropospheric–lower stratospheric (UTLS) jet and tropopause characteristics is compared in five modern high-resolution reanalyses for 1980 through 2014. Climatologies of upper tropospheric jet, subvortex jet (the lowermost part of the stratospheric vortex), and multiple tropopause frequency distributions in MERRA (Modern-Era Retrospective analysis for Research and Applications), ERA-I (ERA-Interim; the European Centre for Medium-Range Weather Forecasts, ECMWF, interim reanalysis), JRA-55 (the Japanese 55-year Reanalysis), and CFSR (the Climate Forecast System Reanalysis) are compared with those in MERRA-2. Differences between alternate products from individual reanalysis systems are assessed; in particular, a comparison of CFSR data on model and pressure levels highlights the importance of vertical grid spacing. Most of the differences in distributions of UTLS jets and multiple tropopauses are consistent with the differences in assimilation model grids and resolution – for example, ERA-I (with coarsest native horizontal resolution) typically shows a significant low bias in upper tropospheric jets with respect to MERRA-2, and JRA-55 (the Japanese 55-year Reanalysis) a more modest one, while CFSR (with finest native horizontal resolution) shows a high bias with respect to MERRA-2 in both upper tropospheric jets and multiple tropopauses. Vertical temperature structure and grid spacing are especially important for multiple tropopause characterizations. Substantial differences between MERRA and MERRA-2 are seen in mid- to high-latitude Southern Hemisphere (SH) winter upper tropospheric jets and multiple tropopauses as well as in the upper tropospheric jets associated with tropical circulations during the solstice seasons; some of the largest differences from the other reanalyses are seen in the same times and places. Very good qualitative agreement among the reanalyses is seen between the large-scale climatological features in UTLS jet and multiple tropopause distributions. Quantitative differences may, however, have important consequences for transport and variability studies. Our results highlight the importance of considering reanalyses differences in UTLS studies, especially in relation to resolution and model grids; this is particularly critical when using high-resolution reanalyses as an observational reference for evaluating global chemistry–climate models.

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

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.

The climate research community uses atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere, yet different reanalyses may give very different results for the same diagnostics. The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare reanalysis data sets using a variety of key diagnostics. The objectives of this project are to identify differences among reanalyses and understand their underlying causes, to provide guidance on appropriate usage of various reanalysis products in scientific studies, particularly those of relevance to SPARC, and to contribute to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. The project focuses predominantly on differences among reanalyses, although studies that include operational analyses and studies comparing reanalyses with observations are also included when appropriate. The emphasis is on diagnostics of the upper troposphere, stratosphere, and lower mesosphere. This paper summarizes the motivation and goals of the S-RIP activity and extensively reviews key technical aspects of the reanalysis data sets that are the focus of this activity. The special issue The SPARC Reanalysis Intercomparison Project (S-RIP) in this journal serves to collect research with relevance to the S-RIP in preparation for the publication of the planned two (interim and full) S-RIP reports.

This paper discusses assimilation experiments of methane (CH4) and nitrous oxide (N2O) profiles retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Here we focus on data versions 6 and 7 provided by the ESA processor. These data sets have been assimilated by the Belgian Assimilation System for Chemical ObsErvations (BASCOE). The CH4 and N2O retrieved profiles can oscillate, especially in the tropical lower stratosphere. Using the averaging kernels of the observations and a background error covariance matrix, which has previously been calibrated, allows the system to partly remedy this issue and provide assimilated fields that are more regular vertically. In general, there is a good agreement between the BASCOE analyses and independent observations from ACE–FTS (CH4 and N2O) and MLS (N2O), demonstrating the general good quality of CH4 and N2O retrievals provided by MIPAS ESA. Nevertheless, this study also identifies two issues in these data sets. First, time series of the observations show unexpected discontinuities due to an abrupt change in the gain of MIPAS band B, generally occurring after the instrument decontamination. Since the calibration is performed weekly, the abrupt change in the gain affects the measurements until the subsequent calibration is performed. Second, the correlations between BASCOE analyses and independent observations are poor in the lower stratosphere, especially in the tropics, probably due to the presence of outliers in the assimilated data. In this region, we recommend using MIPAS CH4 and N2O retrievals with caution.

The stratospheric mean-meridional circulation (MMC) and eddy mixing are compared among six meteorological reanalysis data sets: NCEP-NCAR, NCEP-CFSR, ERA-40, ERA-Interim, JRA-25, and JRA-55 for the period 1979–2012. The reanalysis data sets produced using advanced systems (i.e., NCEP-CFSR, ERA-Interim, and JRA-55) generally reveal a weaker MMC in the Northern Hemisphere (NH) compared with those produced using older systems (i.e., NCEP/NCAR, ERA-40, and JRA-25). The mean mixing strength differs largely among the data products. In the NH lower stratosphere, the contribution of planetary-scale mixing is larger in the new data sets than in the old data sets, whereas that of small-scale mixing is weaker in the new data sets. Conventional data assimilation techniques introduce analysis increments without maintaining physical balance, which may have caused an overly strong MMC and spurious small-scale eddies in the old data sets. At the NH mid-latitudes, only ERA-Interim reveals a weakening MMC trend in the deep branch of the Brewer–Dobson circulation (BDC). The relative importance of the eddy mixing compared with the mean-meridional transport in the subtropical lower stratosphere shows increasing trends in ERA-Interim and JRA-55; this together with the weakened MMC in the deep branch may imply an increasing age-of-air (AoA) in the NH middle stratosphere in ERA-Interim. Overall, discrepancies between the different variables and trends therein as derived from the different reanalyses are still relatively large, suggesting that more investments in these products are needed in order to obtain a consolidated picture of observed changes in the BDC and the mechanisms that drive them.

A quality assessment of the CFC-11 (CCl3F), CFC-12 (CCl2F2), HF, and SF6 products from limb-viewing satellite instruments is provided by means of a detailed intercomparison. The climatologies in the form of monthly zonal mean time series are obtained from HALOE, MIPAS, ACE-FTS, and HIRDLS within the time period 1991–2010. The intercomparisons focus on the mean biases of the monthly and annual zonal mean fields and aim to identify their vertical, latitudinal and temporal structure. The CFC evaluations (based on MIPAS, ACE-FTS and HIRDLS) reveal that the uncertainty in our knowledge of the atmospheric CFC-11 and CFC-12 mean state, as given by satellite data sets, is smallest in the tropics and mid-latitudes at altitudes below 50 and 20 hPa, respectively, with a 1σ multi-instrument spread of up to ±5 %. For HF, the situation is reversed. The two available data sets (HALOE and ACE-FTS) agree well above 100 hPa, with a spread in this region of ±5 to ±10 %, while at altitudes below 100 hPa the HF annual mean state is less well known, with a spread ±30 % and larger. The atmospheric SF6 annual mean states derived from two satellite data sets (MIPAS and ACE-FTS) show only very small differences with a spread of less than ±5 % and often below ±2.5 %. While the overall agreement among the climatological data sets is very good for large parts of the upper troposphere and lower stratosphere (CFCs, SF6) or middle stratosphere (HF), individual discrepancies have been identified. Pronounced deviations between the instrument climatologies exist for particular atmospheric regions which differ from gas to gas. Notable features are differently shaped isopleths in the subtropics, deviations in the vertical gradients in the lower stratosphere and in the meridional gradients in the upper troposphere, and inconsistencies in the seasonal cycle. Additionally, long-term drifts between the instruments have been identified for the CFC-11 and CFC-12 time series. The evaluations as a whole provide guidance on what data sets are the most reliable for applications such as studies of atmospheric transport and variability, model–measurement comparisons and detection of long-term trends. The data sets will be publicly available from the SPARC Data Centre and through PANGAEA (doi:10.1594/PANGAEA.849223).

The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty.

A method of classifying the upper tropospheric/lower stratospheric (UTLS) jets has been developed that allows satellite and aircraft trace gas data and meteorological fields to be efficiently mapped in a jet coordinate view. A detailed characterization of multiple tropopauses accompanies the jet characterization. Jet climatologies show the well-known high altitude subtropical and lower altitude polar jets in the upper troposphere, as well as a pattern of concentric polar and subtropical jets in the Southern Hemisphere, and shifts of the primary jet to high latitudes associated with blocking ridges in Northern Hemisphere winter. The jet-coordinate view segregates air masses differently than the commonly-used equivalent latitude (EqL) coordinate throughout the lowermost stratosphere and in the upper troposphere. Mapping O3 data from the Aura Microwave Limb Sounder (MLS) satellite and the Winter Storms aircraft datasets in jet coordinates thus emphasizes different aspects of the circulation compared to an EqL-coordinate framework: the jet coordinate reorders the data geometrically, thus highlighting the strong PV, tropopause height and trace gas gradients across the subtropical jet, whereas EqL is a dynamical coordinate that may blur these spatial relationships but provides information on irreversible transport. The jet coordinate view identifies the concentration of stratospheric ozone well below the tropopause in the region poleward of and below the jet core, as well as other transport features associated with the upper tropospheric jets. Using the jet information in EqL coordinates allows us to study trace gas distributions in regions of weak versus strong jets, and demonstrates weaker transport barriers in regions with less jet influence. MLS and Atmospheric Chemistry Experiment-Fourier Transform Spectrometer trace gas fields for spring 2008 in jet coordinates show very strong, closely correlated, PV, tropopause height and trace gas gradients across the jet, and evidence of intrusions of stratospheric air below the tropopause below and poleward of the subtropical jet; these features are consistent between instruments and among multiple trace gases. Our characterization of the jets is facilitating studies that will improve our understanding of upper tropospheric trace gas evolution.

A comprehensive evaluation of seasonal backward trajectories initialized in the northern hemisphere lowermost stratosphere (LMS) has been performed to investigate the factors that determine the temporal and spatial structure of troposphere-to-stratosphere-transport (TST) and it's impact on the LMS. In particular we explain the fundamental role of the transit time since last TST (tTST) for the chemical composition of the LMS. According to our results the structure of the LMS can be characterized by a layer with tTSTtTST indicating less frequent mixing and a smaller fraction of tropospheric air. Thus the LMS constitutes a region of two well defined regimes of tropospheric influence. These can be characterized mainly by different transport times from the troposphere and different fractions of tropospheric air. Carbon monoxide (CO) mirrors this structure of tTST due to it's finite lifetime on the order of three months. Water vapour isopleths, on the other hand, do not uniquely indicate TST and are independent of tTST, but are determined by the Lagrangian Cold Point (LCP) of air parcels. Most of the backward trajectories from the LMS experienced their LCP in the tropics and sub-tropics, and TST often occurs 20 days after trajectories have encountered their LCP. Therefore, ExTL properties deduced from CO and H2O provide totally different informations on transport and particular TST for the LMS.

An unusually strong and prolonged stratospheric sudden warming (SSW) in January 2006 was the first major SSW for which globally distributed long-lived trace gas data are available covering the upper troposphere through the lower mesosphere. We use Aura Microwave Limb Sounder (MLS), Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) data, the SLIMCAT Chemistry Transport Model (CTM), and assimilated meteorological analyses to provide a comprehensive picture of transport during this event. The upper tropospheric ridge that triggered the SSW was associated with an elevated tropopause and layering in trace gas profiles in conjunction with stratospheric and tropospheric intrusions. Anomalous poleward transport (with corresponding quasi-isentropic troposphere-to-stratosphere exchange at the lowest levels studied) in the region over the ridge extended well into the lower stratosphere. In the middle and upper stratosphere, the breakdown of the polar vortex transport barrier was seen in a signature of rapid, widespread mixing in trace gases, including CO, H2O, CH4 and N2O. The vortex broke down slightly later and more slowly in the lower than in the middle stratosphere. In the middle and lower stratosphere, small remnants with trace gas values characteristic of the pre-SSW vortex lingered through the weak and slow recovery of the vortex. The upper stratospheric vortex quickly reformed, and, as enhanced diabatic descent set in, CO descended into this strong vortex, echoing the fall vortex development. Trace gas evolution in the SLIMCAT CTM agrees well with that in the satellite trace gas data from the upper troposphere through the middle stratosphere. In the upper stratosphere and lower mesosphere, the SLIMCAT simulation does not capture the strong descent of mesospheric CO and H2O values into the reformed vortex; this poor CTM performance in the upper stratosphere and lower mesosphere results primarily from biases in the diabatic descent in assimilated analyses.

CO, O3, and H2O data in the upper troposphere/lower stratosphere (UTLS) measured by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) on Canada's SCISAT-1 satellite are validated using aircraft and ozonesonde measurements. In the UTLS, validation of chemical trace gas measurements is a challenging task due to small-scale variability in the tracer fields, strong gradients of the tracers across the tropopause, and scarcity of measurements suitable for validation purposes. Validation based on coincidences therefore suffers from geophysical noise. Two alternative methods for the validation of satellite data are introduced, which avoid the usual need for coincident measurements: tracer-tracer correlations, and vertical tracer profiles relative to tropopause height. Both are increasingly being used for model validation as they strongly suppress geophysical variability and thereby provide an "instantaneous climatology". This allows comparison of measurements between non-coincident data sets which yields information about the precision and a statistically meaningful error-assessment of the ACE-FTS satellite data in the UTLS. By defining a trade-off factor, we show that the measurement errors can be reduced by including more measurements obtained over a wider longitude range into the comparison, despite the increased geophysical variability. Applying the methods then yields the following upper bounds to the relative differences in the mean found between the ACE-FTS and SPURT aircraft measurements in the upper troposphere (UT) and lower stratosphere (LS), respectively: for CO ±9% and ±12%, for H2O ±30% and ±18%, and for O3 ±25% and ±19%. The relative differences for O3 can be narrowed down by using a larger dataset obtained from ozonesondes, yielding a high bias in the ACE-FTS measurements of 18% in the UT and relative differences of ±8% for measurements in the LS. When taking into account the smearing effect of the vertically limited spacing between measurements of the ACE-FTS instrument, the relative differences decrease by 5–15% around the tropopause, suggesting a vertical resolution of the ACE-FTS in the UTLS of around 1 km. The ACE-FTS hence offers unprecedented precision and vertical resolution for a satellite instrument, which will allow a new global perspective on UTLS tracer distributions.

During a series of 8 measurement campaigns within the SPURT project (2001-2003), vertical profiles of CO and O3 have been obtained at subtropical, middle and high latitudes over western Europe, covering the troposphere and lowermost stratosphere up to ~14 km altitude during all seasons. The seasonal and latitudinal variation of the measured trace gas profiles are compared to simulations with the chemical transport model MATCH. In the troposphere reasonable agreement between observations and model predictions is achieved for CO and O3, in particular at subtropical and mid-latitudes, while the model overestimates (underestimates) CO (O3 in the lowermost stratosphere particularly at high latitudes, indicating too strong simulated bi-directional exchange across the tropopause. By the use of tagged tracers in the model, long-range transport of Asian air masses is identified as the dominant source of CO pollution over Europe in the free troposphere.

We present measurements of NO, NOy, O3, and N2O within the lowermost stratosphere (LMS) over Europe obtained during the SPURT project. The measurements cover all seasons between November 2001 and July 2003. They span a broad band of latitudes from 30° N to 75° N and a potential temperature range from 290 to 380 K. The measurements represent a comprehensive data set of these tracers and reveal atmospheric transport processes that influence tracer distributions in the LMS. Median mixing ratios of stratospheric tracers in equivalent latitude-potential temperature coordinates show a clear seasonal cycle related to the Brewer-Dobson circulation, with highest values in spring and lowest values in autumn. Vertical tracer profiles show strong gradients at the extratropical tropopause, suggesting that vertical (cross-isentropic) mixing is reduced above the tropopause. Pronounced meridional gradients in the tracer mixing ratios are found on potential temperature surfaces in the LMS. This suggests strongly reduced mixing along isentropes. Concurrent large gradients in static stability in the vertical direction, and of PV in the meridional direction, suggest the presence of a mixing barrier. Seasonal cycles were found in the correlation slopes ΔO3/ΔN2O and ΔNOy/ΔN2O well above the tropopause. Absolute slope values are smallest in spring indicating chemically aged stratospheric air originating from high altitudes and latitudes. Larger values were measured in summer and autumn suggesting that a substantial fraction of air takes a 'short-cut' from the tropical tropopause region into the extratropical LMS. The seasonal change in the composition of the LMS has direct implications for the ozone chemistry in this region. Comparisons of measured NO with the critical NO value at which net ozone production changes from negative to positive, imply ozone production up to 20 K above the local tropopause in spring, up to 30 K in summer, and up to 40 K in autumn. Above these heights, and in winter, net ozone production is negative.

Two aircraft instruments for the measurement of total odd nitrogen (NOy) were compared side by side aboard a Learjet A35 in April 2003 during a campaign of the AFO2000 project SPURT (Spurengastransport in der Tropopausenregion). The instruments albeit employing the same measurement principle (gold converter and chemiluminescence) had different inlet configurations. The ECO-Physics instrument operated by ETH-Zürich in SPURT had the gold converter mounted outside the aircraft, whereas the instrument operated by FZ-Jülich in the European project MOZAIC III (Measurements of ozone, water vapour, carbon monoxide and nitrogen oxides aboard Airbus A340 in-service aircraft) employed a Rosemount probe with 80 cm of FEP-tubing connecting the inlet to the gold converter. The NOy concentrations during the flight ranged between 0.3 and 3 ppb. The two data sets were compared in a blind fashion and each team followed its normal operating procedures. On average, the measurements agreed within 7%, i.e. within the combined uncertainty of the two instruments. This puts an upper limit on potential losses of HNO3 in the Rosemount inlet of the MOZAIC instrument. Larger transient deviations were observed during periods after calibrations and when the aircraft entered the stratosphere. The time lag of the MOZAIC instrument observed in these instances is in accordance with the time constant of the MOZAIC inlet line determined in the laboratory for HNO3.

Airborne high resolution in situ measurements of a large set of trace gases including ozone (O3) and total water (H2O) in the upper troposphere and the lowermost stratosphere (UT/LMS) have been performed above Europe within the SPURT project. SPURT provides an extensive data coverage of the UT/LMS in each season within the time period between November 2001 and July 2003. In the LMS a distinct spring maximum and autumn minimum is observed in O3, whereas its annual cycle in the UT is shifted by 2–3 months later towards the end of the year. The more variable H2O measurements reveal a maximum during summer and a minimum during autumn/winter with no phase shift between the two atmospheric compartments. For a comprehensive insight into trace gas composition and variability in the UT/LMS several statistical methods are applied using chemical, thermal and dynamical vertical coordinates. In particular, 2-dimensional probability distribution functions serve as a tool to transform localised aircraft data to a more comprehensive view of the probed atmospheric region. It appears that both trace gases, O3 and H2O, reveal the most compact arrangement and are best correlated in the view of potential vorticity (PV) and distance to the local tropopause, indicating an advanced mixing state on these surfaces. Thus, strong gradients of PV seem to act as a transport barrier both in the vertical and the horizontal direction. The alignment of trace gas isopleths reflects the existence of a year-round extra-tropical tropopause transition layer. The SPURT measurements reveal that this layer is mainly affected by stratospheric air during winter/spring and by tropospheric air during autumn/summer. Normalised mixing entropy values for O3 and H2O in the LMS appear to be maximal during spring and summer, respectively, indicating highest variability of these trace gases during the respective seasons.

We present airborne in-situ trace gas measurements which were performed on eight campaigns between November 2001 and July 2003 during the SPURT-project (SPURenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region). The measurements on a quasi regular basis allowed an overview of the seasonal variations of the trace gas distribution in the tropopause region over Europe from 35°-75°N to investigate the influence of transport and mixing across the extratropical tropopause on the lowermost stratosphere. From the correlation of CO and O3 irreversible mixing of tropospheric air into the lowermost stratosphere is identified. The CO distribution indicates that transport and subsequent mixing of tropospheric air across the extratropical tropopause predominantly affects a layer, which closely follows the shape of the local tropopause. In addition, the seasonal cycle of CO2 illustrates the strong coupling of that layer to the extratropical troposphere. Both, horizontal gradients of CO on isentropes as well as the CO-O3-distribution in the lowermost stratosphere reveal that the influence of quasi-horizontal transport and subsequent mixing weakens with distance from the local tropopause. The mixing layer extends to about 25 K in potential temperature above the local tropopause exhibiting only a weak seasonality. However, at large distances from the tropopause a significant influence of tropospheric air is still evident. The relation between N2O and CO2 indicates that a significant contribution of air originating from the tropical tropopause contributes to the background air in the extratropical lowermost stratosphere.

Within the project SPURT (trace gas measurements in the tropopause region) a variety of trace gases have been measured in situ in order to investigate the role of dynamical and chemical processes in the extra-tropical tropopause region. In this paper we report on a flight on 10 November 2001 leading from Hohn, Germany (52ºN) to Faro, Portugal (37ºN) through a strongly developed deep stratospheric intrusion. This streamer was associated with a large convective system over the western Mediterranean with potentially significant troposphere-to-stratosphere transport. Along major parts of the flight we measured unexpectedly high NOy mixing ratios. Also H2O mixing ratios were significantly higher than stratospheric background levels confirming the extraordinary chemical signature of the probed air masses in the interior of the streamer. Backward trajectories encompassing the streamer enable to analyze the origin and physical characteristics of the air masses and to trace troposphere-to-stratosphere transport. Near the western flank of the intrusion features caused by long range transport, such as tropospheric filaments characterized by sudden drops in the O3 and NOy mixing ratios and enhanced CO and H2O can be reconstructed in great detail using the reverse domain filling technique. These filaments indicate a high potential for subsequent mixing with the stratospheric air. At the south-western edge of the streamer a strong gradient in the NOy and the O3 mixing ratios coincides very well with a sharp gradient in potential vorticity in the ECMWF fields. In contrast, in the interior of the streamer the observed highly elevated NOy and H2O mixing ratios up to a potential temperature level of 365 K and potential vorticity values of maximum 10 PVU cannot be explained in terms of resolved troposphere-to-stratosphere transport along the backward trajectories. Also mesoscale simulations with a High Resolution Model reveal no direct evidence for convective H2O injection up to this level. Elevated H2O mixing ratios in the ECMWF and HRM model are seen only up to about tropopause height at 340 hPa and 270hPa, respectively, well below flight altitude of about 200 hPa. However, forward tracing of the convective influence as identified by satellite brightness temperature measurements and counts of lightning strokes shows that during this part of the flight the aircraft was closely following the border of an air mass which was heavily impacted by convective activity over Spain and Algeria. This is evidence that deep convection at mid-latitudes may have a large impact on the tracer distribution of the lowermost stratosphere reaching well above the thunderstorms anvils as claimed by recent studies using cloud-resolving models.