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Very short-lived substances (VSLS), including dichloromethane (CH2Cl2), chloroform (CHCl3), perchloroethylene (C2Cl4), and 1,2-dichloroethane (C2H4Cl2), are a stratospheric chlorine source and therefore contribute to ozone depletion. We quantify stratospheric chlorine trends from these VSLS (VSLCltot) using a chemical transport model and atmospheric measurements, including novel high-altitude aircraft data from the NASA VIRGAS (2015) and POSIDON (2016) missions. We estimate VSLCltot increased from 69 (±14) parts per trillion (ppt) Cl in 2000 to 111 (±22) ppt Cl in 2017, with >80% delivered to the stratosphere through source gas injection, and the remainder from product gases. The modeled evolution of chlorine source gas injection agrees well with historical aircraft data, which corroborate reported surface CH2Cl2 increases since the mid-2000s. The relative contribution of VSLS to total stratospheric chlorine increased from ~2% in 2000 to ~3.4% in 2017, reflecting both VSLS growth and decreases in long-lived halocarbons. We derive a mean VSLCltot growth rate of 3.8 (±0.3) ppt Cl/year between 2004 and 2017, though year-to-year growth rates are variable and were small or negative in the period 2015-2017. Whether this is a transient effect, or longer-term stabilization, requires monitoring. In the upper stratosphere, the modeled rate of HCl decline (2004-2017) is -5.2% per decade with VSLS included, in good agreement to ACE satellite data (-4.8% per decade), and 15% slower than a model simulation without VSLS. Thus, VSLS have offset a portion of stratospheric chlorine reductions since the mid-2000s.

Using state-of-the-art satellite ozone profile products, and a chemical transport model, we provide an updated estimate of the tropospheric ozone radiative effect (TO 3 RE) and observational constraint on its variability over the decade 2008–2017. Previous studies have shown the short-term (i.e. a few years) globally weighted average TO 3 RE to be 1.17 ± 0.03 W m -2. However, from our analysis, using decadal (2008–2017) ozone profile datasets from the Infrared Atmospheric Sounding Interferometer, average TO 3 RE ranges between 1.21 and 1.26 W m -2. Over this decade, the modelled and observational TO 3 RE linear trends show a negligible change (e.g. ± 0.1 % yr -1). Two model sensitivity experiments fixing emissions and meteorology to 1 year (i.e. start year – 2008) show that temporal changes in ozone precursor emissions (increasing contribution) and meteorological factors (decreasing contribution) have counteracting tendencies, leading to a negligible globally weighted average TO 3 RE trend. [ABSTRACT FROM AUTHOR]

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

Ozone is a potent air pollutant in the lower troposphere and an important short-lived climate forcer (SLCF) in the upper troposphere. Studies using satellite data to investigate spatiotemporal variability of troposphere ozone (TO 3) have predominantly focussed on the tropospheric column metric. This is the first study to investigate long-term spatiotemporal variability in lower tropospheric column ozone (LTCO 3 , surface–450 hPa sub-column) by merging multiple European Space Agency–Climate Change Initiative (ESA-CCI) products produced by the Rutherford Appleton Laboratory (RAL) Space. We find that in the LTCO 3 , the degree of freedom of signal (DOFS) from these products varies with latitude range and season and is up to 0.8, indicating that the retrievals contain useful information on lower TO 3. The spatial and seasonal variation of the RAL Space products are in good agreement with each other, but there are systematic offsets of up to 3.0–5.0 DU between them. Comparison with ozonesondes shows that the Global Ozone Monitoring Experiment (GOME-1, 1996–2003), the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY, 2003–2010) and the Ozone Monitoring Instrument (OMI, 2005–2017) have stable LTCO 3 records over their respective periods, which can be merged together. However, GOME-2 (2008–2018) shows substantial drift in its bias with respect to ozonesondes. We have therefore constructed a robust merged data set of LTCO 3 from GOME-1, SCIAMACHY and OMI between 1996 and 2017. Comparing the LTCO 3 differences between the 1996–2000 and 2013–2017 5-year averages, we find sizeable positive increases (3.0–5.0 DU) in the tropics/sub-tropics, while in the northern mid-latitudes, we find small-scale differences in LTCO 3. Therefore, we conclude that there has been a substantial increase in tropical/sub-tropical LTCO 3 during the satellite era, which is consistent with tropospheric column ozone (TCO 3) records from overlapping time periods (e.g. 2005–2016). [ABSTRACT FROM AUTHOR]

Using state-of-the-art satellite ozone profile products, and chemical transport model, we provide an updated estimate of the tropospheric ozone radiative effect (TO3RE) and observational constraint on its variability over the decade 2008–2017. Previous studies have shown the short-term (i.e. a few years) globally weighted average TO3RE to be 1.17±0.03 W/m2, while our analysis suggests that the long-term (2008–2017) average TO3RE to be 1.21–1.28 W/m2. Over this decade, the modelled/observational TO3RE linear trends show negligible change (i.e. ±0.1 %/year), so the tropospheric ozone radiative contribution to climate has remained stable with time. Two model sensitivity experiments fixing emissions and meteorology to one year (i.e. start year – 2008) show that ozone precursor emissions (meteorological factors) have had limited (substantial) impacts on the long-term tendency of globally weighted average TO3RE. Here, the meteorological variability in the tropical/sub-tropical upper troposphere is dampening any tendency in TO3RE from other factors (e.g. emissions, atmospheric chemistry). [ABSTRACT FROM AUTHOR]

Ozone is a potent air pollutant in the lower troposphere and an important short-lived climate forcer (SLCF) in the upper troposphere. Studies using satellite data to investigate spatiotemporal variability of troposphere ozone (TO3) have predominantly focussed on the tropospheric column metric. This is the first study to investigate long-term spatiotemporal variability in lower tropospheric column ozone (LTCO3, surface-450 hPa sub-column) by merging multiple European Space Agency – Climate Change Initiative (ESA-CCI) products produced by the Rutherford Appleton Laboratory (RAL) Space. We find that in the LTCO3, the degrees of freedom of signal (DOFS) from these products varies with latitude range and season and is up to 0.65, indicating that the retrievals contain useful information on lower TO3. The spatial and seasonal variation of the RAL Space products are in good agreement with each other but there are systematic offsets of up to 3.0–5.0 DU between them. Comparison with ozonesondes shows that the Global Ozone Monitoring Experiment (GOME-1, 1996–2003), the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY, 2003–2010) and the Ozone Monitoring Instrument (OMI, 2005–2017) have stable LTCO3 records over their respective periods, which can be merged together. While GOME-2 (2008–2018) shows substantial drift in its bias with respect to ozonesondes. We have therefore constructed a robust merged dataset of LTCO3 from GOME-1, SCIAMACHY and OMI between 1996 and 2017. Comparing the LTCO3 differences between the 1996–2000 and 2013–2017 5-year averages, we find significant positive increases (3.0–5.0 DU) in the tropics/sub-tropics, while in the northern mid-latitudes, we find small scale differences in LTCO3. Therefore, we conclude that there has been a substantial increase in tropical/sub-tropical LTCO3 during the satellite-era. [ABSTRACT FROM AUTHOR]

Figures 6(a) and 6(b) in the study by L2022 used total ozone data from different sources (Total Ozone Mapping Spectrometer, Ozone Monitoring Instrument, and Ozone Mapping and Profiler Suite) without removing potential biases and drifts between the datasets, a step that is essential for accurate diagnosis of trends. [37] (hereafter L2022) used the Trajectory-mapped Ozonesonde dataset for the Stratosphere and Troposphere (TOST) to argue that there has been very substantial ozone depletion (>80%) in the tropical (30°S-30°N) lower stratosphere (LS) since the 1960s. OZONE IN THE TROPICAL LOWER STRATOSPHERE A. TOST data used by L2022 The World Ozone and Ultraviolet Radiation Data Center (WOUDC) website (https://woudc.org/data.php) hosts the TOST data in two formats: (1) ozonesonde data at 1 km intervals in altitude expanded with 4-day forward and backward trajectories to increase spatial sampling (hereafter labeled TOST RAW) and (2) a smoothed, gap-filled version of TOST RAW using linear interpolation of maps (hereafter labeled TOST SM). The stronger decline reported by L2022 is caused by inappropriate use of the gap-filled version of the TOST ozone dataset, which is based on sparse tropical ozone sondes before the 1990s. [Extracted from the article]

We use TOMCAT, a 3-dimensional (3D) offline chemical transport model (CTM) forced by two different meteorological reanalysis data sets (ERA-Interim and ERA5) from the European Centre for Medium-Range weather Forecasts (ECMWF) to analyse seasonal behaviour and long-term trends in stratospheric ozone and mean age of air. The model-simulated ozone variations are evaluated against two observation-based data sets. For total column ozone (TCO) comparisons, we use the Copernicus Climate Change Service (C3S) data (1979–2019), while for ozone profiles we use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set (1984–2019). We find that the CTM simulations forced by ERA-Interim (A_ERAI) and ERA5 (B_ERA5) can both successfully reproduce the spatial and temporal variations in stratospheric ozone. Also, modelled TCO anomalies from B_ERA5 show better agreement with C3S than A_ERAI, especially in Northern Hemisphere (NH) mid latitudes, except that it gives somewhat larger positive biases (> 15 DU, Dobson units) during winter–spring seasons. Ozone profile comparisons against SWOOSH data show larger differences between the two simulations. In the lower stratosphere, ozone differences can be directly attributed to the representation of dynamical processes, whereas in the upper stratosphere they can be directly linked to the differences in temperatures between ERAI and ERA5 data sets. Although TCO anomalies from B_ERA5 show relatively better agreement with C3S compared to A_ERAI, a comparison with SWOOSH data does not confirm that B_ERA5 performs better at simulating the variations in the stratospheric ozone profiles. We employ a multivariate regression model to quantify the TCO and ozone profile trends before and after peak stratospheric halogen loading in 1997. Our results show that, compared to C3S, TCO recovery trends (since 1998) in simulation B_ERA5 are significantly overestimated in the Southern Hemisphere (SH) mid latitudes, while for A_ERAI in the NH mid latitudes, simulated ozone trends remain negative. Similarly, in the lower stratosphere, B_ERA5 shows positive ozone recovery trends for both NH and SH mid latitudes. In contrast, both SWOOSH and A_ERAI show opposite (negative) trends in the NH mid latitudes. Furthermore, we analyse age of air (AoA) trends to diagnose transport differences between the two reanalysis data sets. Simulation B_ERA5 shows a positive AoA trend after 1998 and somewhat older age in the NH lower stratosphere compared to A_ERAI, indicating that a slower Brewer–Dobson circulation does not translate into reduced wintertime ozone buildup in the NH extratropical lower stratosphere. Overall, our results show that models forced by the most recent ERA5 reanalyses may not yet be capable of reproducing observed changes in stratospheric ozone, particularly in the lower stratosphere. [ABSTRACT FROM AUTHOR]

High quality stratospheric ozone profile datasets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments obtain stratospheric ozone profile measurements over typical mission durations of 5-15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create longer term observation-based ozone profile datasets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different datasets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a Random-Forest (RF) ensemble learning method to create a merged 42-year (1979-2020) stratospheric ozone profile dataset (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gas, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) dataset over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991-1998) and Aura (2005-2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based datasets which use pressure as the vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the datasets which are height-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties in the observational datasets. The ML-TOMCAT dataset is thus ideally suited for the evaluation of model ozone profiles from the tropopause to 0.1 hPa. ML-TOMCAT data is freely available via https://zenodo.org/record/4997959#.YNzleUlKiUk (Dhomse et al., 2021). [ABSTRACT FROM AUTHOR]

In the winter and spring of 2019/2020, the unusually cold, strong, and stable polar vortex created favorable conditions for ozone depletion in the Arctic. Chemical ozone loss started earlier than in any previous year in the satellite era and continued until late March, resulting in the unprecedented reduction of the ozone column. The vortex was located above the Polar Environment Atmospheric Research Laboratory in Eureka, Canada (80°N, 86°W) from late February to the end of April, presenting an excellent opportunity to examine ozone loss from a single ground station. Measurements from a suite of instruments show that total column ozone was at an all‐time low in the 20‐year data set, 22–102 DU below previous records set in 2011. Ozone minima (<200 DU), enhanced OClO and BrO slant columns, and unusually low‐HCl, ClONO2, and HNO3 columns were observed in March. Polar stratospheric clouds were present as late as 20 March, and ozonesondes show unprecedented depletion in the March and April profiles (to <0.2 ppmv). While both chemical and dynamical factors lead to reduced ozone when the vortex is cold, the contribution of chemical depletion (based on the variable correlation of ozone and temperature) was exceptional in spring 2020 when compared to typical Arctic winters. Mean chemical ozone loss over Eureka was estimated to be 111–126 DU (27%–31%) using April measurements and passive ozone from the SLIMCAT chemical transport model. While absolute ozone loss was generally smaller in 2020 than in 2011, percentage ozone loss was greater in 2020. Plain Language Summary: While an ozone hole forms over Antarctica every year, the Arctic typically does not experience such dramatic ozone loss. The chlorine and bromine (halogen) reactions that destroy ozone require very low temperatures that are rarely observed in the Arctic stratosphere. The winter and spring of 2019/2020, however, was unusually cold in the Arctic, and consequently, a large amount of ozone was destroyed by halogen chemistry. To understand the behavior of ozone in spring 2020, we use measurements from the Polar Environment Atmospheric Research Laboratory in Eureka, Canada. Eureka (at 80°N) is one of the northernmost research stations in the world, and thus an ideal location to observe ozone loss. Spring 2020 ozone minima were lower than any in the 20‐year data set, and ozone destruction was ongoing until the end of March, which is rare in the Arctic. While ozone concentrations are largely determined by circulation patterns in the Arctic stratosphere, chemistry in spring 2020 was a much larger factor than usual. Halogen chemistry destroyed 27%–31% of the total ozone, compared to about 10% in a typical winter. The only year on record with comparable ozone loss is 2011, and a larger percentage of the ozone column was lost in 2020. Key Points: Record low ozone columns (<200 DU) were observed over Eureka in spring 2020Limited dynamical resupply of ozone and chemical destruction both contributed to reduced ozone columnsMean chemical ozone loss of 111–126 DU (27%–31%) represents similar absolute loss and greater relative loss compared to that in spring 2011 [ABSTRACT FROM AUTHOR]

The phase out of anthropogenic ozone‐depleting substances such as chlorofluorocarbons under the terms of the Montreal Protocol led to the development and worldwide use of hydrofluorocarbons (HFCs) in refrigeration, air conditioning, and as blowing agents and propellants. Consequently, over recent years, the atmospheric abundances of HFCs have dramatically increased. HFCs are powerful greenhouse gases and are now controlled under the terms of the 2016 Kigali Amendment to the Montreal Protocol. HFC‐134a is currently the most abundant HFC in the atmosphere, breaking the 100 ppt barrier in 2018, and can be measured in the Earth's atmosphere by the satellite remote‐sensing instrument ACE‐FTS (Atmospheric Chemistry Experiment‐Fourier Transform Spectrometer), which has been measuring since 2004. This work uses the ACE‐FTS v4.0 data product to investigate global distributions and trends of HFC‐134a. These measurements are compared with a simulation of SLIMCAT, a state‐of‐the‐art three‐dimensional chemical transport model, which is constrained by global surface HFC‐134a measurements. The agreement between observation and model is good, although in the tropical troposphere ACE‐FTS measurements are biased low by up to 10–15 ppt. The overall ACE‐FTS global trend of HFC‐134a for the altitude range 5.5–24.5 km and 2004–2018 time period is approximately linear with a value of 4.49 ± 0.02 ppt/year, slightly lower than the corresponding SLIMCAT trend of 4.66 ppt/year. Using a simple box model, we also estimate the annual global emissions and burdens of HFC‐134a from the model data, indicating that emissions of HFC‐134a have increased almost linearly, reaching 236 Gg by 2018. Key Points: First comparison between long‐term satellite measurements (ACE‐FTS) of atmospheric HFC‐134a and a 3D chemical transport model (SLIMCAT)Observations agree well with SLIMCAT, although ACE‐FTS is biased low by up to 10–15 ppt in the troposphere between 30°S and 30°NGlobal trends are linear to a good approximation: 4.49 ppt/year for ACE‐FTS (2004–2018; 5.5–24.5 km) and 4.66 ppt/year for SLIMCAT [ABSTRACT FROM AUTHOR]

Satellite observations of relevant trace gases and meteorological data from ERA5 were used to describe the dynamics and chemistry of the spectacular Arctic 2019/20 winter/spring season. Exceptionally low total ozone values of slightly less than 220 DU were observed in mid‐March within an unusually large stratospheric polar vortex. Very high OClO and very low NO2 column amounts observed by GOME‐2A were indicative of unusually large active chlorine levels and significant denitrification, which likely contributed to large chemical ozone loss. Using results from the TOMCAT chemical transport model (CTM) and ozone observations from S5P/TROPOMI, GOME‐2 (total column), SCIAMACHY, and OMPS‐LP (vertical profiles), chemical ozone loss was evaluated and compared with the previous record Arctic winter 2010/11. The polar‐vortex‐averaged total column ozone loss in 2019/20 reached 88 DU (23%) and 106 DU (28%) based upon observations and model, respectively, by the end of March, which was similar to that derived for 2010/11. The maximum ozone loss (∼80%) observed by OMPS‐LP was near the 450 K potential temperature level (∼18 km altitude). Because of the larger polar vortex area in March 2020 compared to March 2011 (about 25% at 450 K), ozone mass loss was larger in Arctic winter 2019/20. It is shown that Arctic cap temperatures were at a record 40‐year low in winter, suggesting that Arctic cold winters are getting colder. Tropical UTLS temperatures show an apparent upward trend during the last two decades that may indicate a weakening of the Brewer‐Dobson circulation and strengthening of the polar vortex. Key Points: Very large OClO and very low NO2 slant columns were observed by GOME‐2A during Arctic winter 2019/20Chemical total column ozone loss of 88 DU and 106 DU was derived from TROPOMI satellite observations and the chemical transport modelChemical ozone loss derived from OMPS‐LP satellite data reached 2.1 ppmv (80%) near the 450 K potential temperature level (∼18 km) [ABSTRACT FROM AUTHOR]

Various observation-based datasets have confirmed positive zonal mean column ozone trends at midlatitudes as a result of the successful implementation of the Montreal Protocol. However, there is still uncertainty about the longitudinal variation of these trends and the direction and magnitude of ozone changes at low latitudes. Here, we use the extended Copernicus Climate Change Service (C3S) dataset (1979–2017) to investigate the long-term variations in total column ozone (TCO) over the Tibetan Plateau (TP) for different seasons. We use piecewise linear trend (PWLT) and equivalent effective stratospheric chlorine loading (EESC)-based multivariate regression models with various proxies to attribute the influence of dynamical and chemical processes on the TCO variability. We also compare the seasonal behaviour of the relative total ozone low (TOL) over the TP with the zonal mean at the same latitude. Both regression models show that the TP column ozone trends change from negative trends from 1979 to 1996 to small positive trends from 1997 to 2017, although the later positive trend based on PWLT is not statistically significant. The wintertime positive trend starting from 1997 is larger than that in summer, but both seasonal TP recovery rates are smaller than the zonal means over the same latitude band. For TP column ozone, both regression models suggest that the geopotential height at 150 hPa (GH150) is a more suitable and realistic dynamical proxy compared to a surface temperature proxy used in some previous studies. Our analysis also shows that the wintertime GH150 plays an important role in determining summertime TCO over the TP through persistence of the ozone signal. For the zonal mean column ozone at this latitude, the quasi-biennial oscillation (QBO) is nonetheless the dominant dynamical proxy. We also use a 3-D chemical transport model to diagnose the contributions of different proxies for the TP region. The role of GH150 variability is illustrated by using two sensitivity experiments with repeating dynamics of 2004 and 2008. The simulated ozone profiles clearly show that wintertime TP ozone concentrations are largely controlled by tropics to midlatitude pathways, whereas in summer variations associated with tropical processes play an important role. These model results confirm that the long-term trends of TCO over the TP are dominated by different processes in winter and summer. The different TP recovery rates relative to the zonal means at the same latitude band are largely determined by wintertime dynamical processes. [ABSTRACT FROM AUTHOR]

Here we present a description of the UKCA StratTrop chemical mechanism, which is used in the UKESM1 Earth system model for CMIP6. The StratTrop chemical mechanism is a merger of previously well-evaluated tropospheric and stratospheric mechanisms, and we provide results from a series of bespoke integrations to assess the overall performance of the model. We find that the StratTrop scheme performs well when compared to a wide array of observations. The analysis we present here focuses on key components of atmospheric composition, namely the performance of the model to simulate ozone in the stratosphere and troposphere and constituents that are important for ozone in these regions. We find that the results obtained for tropospheric ozone and its budget terms from the use of the StratTrop mechanism are sensitive to the host model; simulations with the same chemical mechanism run in an earlier version of the MetUM host model show a range of sensitivity to emissions that the current model does not fall within. Whilst the general model performance is suitable for use in the UKESM1 CMIP6 integrations, we note some shortcomings in the scheme that future targeted studies will address. [ABSTRACT FROM AUTHOR]

Here we present a description of the UKCA StratTrop chemical mechanism which is used in the UKESM1 Earth System Model for CMIP6. The StratTrop chemical mechanism is a merger of previously well evaluated tropospheric and stratospheric mechanisms and we provide results from a series of bespoke integrations to assess the overall performance of the model. We find that the StratTrop scheme performs well when compared to a wide array of observations. The analysis we present here focuses on key components of atmospheric composition, namely the performance of the model to simulate ozone in the stratosphere and troposphere and constituents that are important for ozone in these regions. We find that the results obtained from the use of the StratTrop mechanism are sensitive to the host model; simulations with the same chemical mechanism run in an earlier version of the MetUM host model show a range of sensitivity to emissions that the current model does not fall within. Whilst the general model performance is suitable for use in the UKESM1 CMIP6 integrations, we note some shortcomings in the scheme that future targeted studies will address. [ABSTRACT FROM AUTHOR]

An updated and improved version of a global, vertically resolved, monthly mean zonal mean ozone database has been calculated - hereafter referred to as the BSVertOzone (Bodeker Scientific Vertical Ozone) database. Like its predecessor, it combines measurements from several satellite-based instruments and ozone profile measurements from the global ozonesonde network. Monthly mean zonal mean ozone concentrations in mixing ratio and number density are provided in 5° latitude bins, spanning 70 altitude levels (1 to 70 km), or 70 pressure levels that are approximately 1 km apart (878.4 to 0.046 hPa). Different data sets or "tiers" are provided: Tier 0 is based only on the available measurements and therefore does not completely cover the whole globe or the full vertical range uniformly; the Tier 0.5 monthly mean zonal means are calculated as a filled version of the Tier 0 database where missing monthly mean zonal mean values are estimated from correlations against a total column ozone (TCO) database. The Tier 0.5 data set includes the full range of measurement variability and is created as an intermediate step for the calculation of the Tier 1 data where a least squares regression model is used to attribute variability to various known forcing factors for ozone. Regression model fit coefficients are expanded in Fourier series and Legendre polynomials (to account for seasonality and latitudinal structure, respectively). Four different combinations of contributions from selected regression model basis functions result in four different Tier 1 data sets that can be used for comparisons with chemistry-climate model (CCM) simulations that do not exhibit the same unforced variability as reality (unless they are nudged towards reanalyses). Compared to previous versions of the database, this update includes additional satellite data sources and ozonesonde measurements to extend the database period to 2016. Additional improvements over the previous version of the database include the following: (i) adjustments of measurements to account for biases and drifts between different data sources (using a chemistry-transport model, CTM, simulation as a transfer standard), (ii) a more objective way to determine the optimum number of Fourier and Legendre expansions for the basis function fit coefficients, and (iii) the derivation of methodological and measurement uncertainties on each database value are traced through all data modification steps. Comparisons with the ozone database from SWOOSH (Stratospheric Water and OzOne Satellite Homogenized data set) show good agreement in many regions of the globe. Minor differences are caused by different bias adjustment procedures for the two databases. [ABSTRACT FROM AUTHOR]

Stratospheric ozone, O3, in the tropical middle stratosphere is controlled by a balance between photochemical production and loss. These processes are strongly influenced by atmospheric dynamics, which is dominated by the Brewer-Dobson Circulation (BDC). Seasonal variations of the strength of BDC in the tropical mid-stratosphere, which are commonly described by the mean age-of-air parameter, have been identified to impact the annual mean trends of nitrous oxide (N2O), nitrogen dioxide (NO2), and therefore O3. However, the reasons for the changes in seasonal transport in this region are not yet clear. This has implications for the detection and attribution of stratospheric ozone recovery in this region. This study investigates and identifies possible reasons for the seasonal variability in the speed of vertical transport in the tropical mid-stratosphere. In particular, we investigate whether the observed behaviour is caused by (a) shift of subtropical transport barriers, (b) different behaviour of BDC branches, (c) cooling of the eastern Pacific, which leads to changes in upwelling, or (d) the changing contributions from the wave forcing. In our analysis, we use observational data for O3 profiles retrieved at the University of Bremen from limb-scanning instruments SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) and the Ozone Mapping and Profiler Suite (OMPS). We also use time series of gravity wave (GW) potential energy retrieved at the Finnish Meteorological Institute from high-resolution temperature profiles (HRTP) measured by the GOMOS satellite instrument and output from the TOMCAT global offline 3-D chemistry-transport model (CTM). The model contains a detailed description of stratospheric chemistry and it is driven by ERA-Interim reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). We performed TOMCAT simulations with different chemical and dynamical forcings for the period 2003-2018 to interpret their possible changes and impact on stratospheric ozone. [ABSTRACT FROM AUTHOR]