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The January 2022 eruption of Hunga Tonga‐Hunga Ha'apai (HTHH) injected a huge amount (∼150 Tg) of water vapor (H2O) into the stratosphere, along with small amount of SO2. An off‐line 3‐D chemical transport model (CTM) successfully reproduces the spread of the injected H2O through October 2023 as observed by the Microwave Limb Sounder. Dehydration in the 2023 Antarctic polar vortex caused the first substantial (∼20 Tg) removal of HTHH H2O from the stratosphere. The CTM indicates that this process will dominate removal of HTHH H2O for the coming years, giving an overall e‐folding timescale of 4 years; around 25 Tg of the injected H2O is predicted to still remain in the stratosphere by 2030. Following relatively low Antarctic column ozone in midwinter 2023 due to transport effects, additional springtime depletion due to H2O‐related chemistry was small and maximized at the vortex edge (10 DU in column). Plain Language Summary: Around 150 Tg (150 million tons) of water vapor was injected into the stratosphere during the eruption of Hunga Tonga‐Hunga Ha'apai. Water vapor is a greenhouse gas and this increase is expected to have a warming effect in the troposphere, as well causing perturbations in stratospheric chemistry and aerosols. We use an atmospheric model to study the residence time of this excess water vapor and its impact on the recent Antarctic ozone hole. The model performance is evaluated by comparison with satellite measurements. Wintertime dehydration in the Antarctic stratosphere in 2023 is found to be an important mechanism for removal of the volcanic water from the stratosphere. However, the overall removal rate is predicted to be slow; around 25 Tg (17%) is still present in 2030. The direct impact of the excess water vapor on ozone via chemical processes in the Antarctic ozone hole in 2023 is small. Key Points: Antarctic dehydration is a major removal pathway of stratospheric H2O injected from Hunga Tonga‐Hunga Ha'apai (HTHH) eruptionHTHH H2O caused small (up to 10 DU) additional chemical ozone depletion in 2023 Antarctic springModel indicates e‐folding timescale of 4 years for removal of HTHH H2O from stratosphere [ABSTRACT FROM AUTHOR]

Monitoring the atmospheric concentrations of greenhouse gases (GHGs) is crucial to improve our understanding of their climate impact. However, there are no long-term profile data sets of important GHGs that can be used to gain a better insight into the processes controlling their variations in the atmosphere. In this study, we apply corrections to chemical transport model (CTM) output based on profile measurements from two solar occultation instruments: the HALogen Occultation Experiment (HALOE) and the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS). The goal is to construct long-term (1991–2021), gap-free stratospheric profile data sets, hereafter referred to as TCOM, for two important GHGs. To estimate the corrections that need to be applied to the CTM profiles, we use the extreme gradient boosting (XGBoost) regression model. For methane (TCOM-CH4), we utilize both HALOE and ACE satellite profile measurements from 1992 to 2018 to train the XGBoost model, while profiles from 2019 to 2021 serve as an independent evaluation data set. As there are no nitrous oxide (N 2 O) profile measurements for earlier years, we derive XGBoost-derived correction terms to construct TCOM-N2O profiles using only ACE-FTS profiles from the 2004–2018 time period, with profiles from 2019–2021 used for the independent evaluation. Overall, both TCOM-CH4 and TCOM-N2O profiles exhibit excellent agreement with the available satellite-measurement-based data sets. We find that compared to evaluation profiles, biases in TCOM-CH4 and TCOM-N2O are generally less than 10 % and 50 %, respectively, throughout the stratosphere. The daily zonal mean profile data sets, covering altitude (15–60 km) and pressure (300–0.1 hPa) levels, are publicly available via the following links: 10.5281/zenodo.7293740 for TCOM-CH4 and 10.5281/zenodo.7386001 for TCOM-N2O. [ABSTRACT FROM AUTHOR]

Monitoring the atmospheric concentrations of greenhouse gases (GHGs) is crucial in order to improve our understanding of their climate impact. However, there are no long-term profile data sets of important GHGs that can be used to gain a better insight into the processes controlling their variations in the atmosphere. Here, we merge chemical transport model (CTM) output and profile measurements from two solar occultation instruments, the HALogen Occultation Experiment (HALOE) and the Atmospheric Chemistry Experiment - Fourier Transform Spectrometer (ACE-FTS), to construct long-term (1991-2021), gap-free stratospheric profile data sets (hereafter, TCOM) for two important GHGs. The Extreme Gradient Boosting (XGBoost) regression model is used to estimate the corrections needed to apply to the CTM profiles. For methane (TCOM-CH4), we use both HALOE and ACE satellite profile measurements (1992-2018) to train the XGBoost model while profiles from three later years (2019-2021) are used as an independent evaluation data set. As there are no nitrous oxide (N2O) profile mea10 surements for earlier years, XGBoost-derived correction terms to construct TCOM-N2O profiles are derived using only ACEFTS profiles for the 2004-2018 time period, with profiles from 2019-2021 again being used for the independent evaluation. Overall, both TCOM-CH4 and TCOM-N2O profiles show excellent agreement with the available satellite measurement-based data sets. We find that compared to evaluation profiles, biases in TCOM-CH4 and TCOM-N2O are generally less than 10% and 50%, respectively, throughout the stratosphere. Daily zonal mean profile data sets on altitude (15-60 km) and pressure (300-0.1 hPa) levels are publicly available via https://doi.org/10.5281/zenodo.7293740 for TCOM-CH4 (Dhomse, 2022a) and https://doi.org/10.5281/zenodo.7386001 for TCOM-N2O (Dhomse, 2022b). [ABSTRACT FROM AUTHOR]

Figure compares TOMCAT and ML-TOMCAT profiles with the three altitude-based ozone data sets with a focus on the Equator (0 HT ht latitude). The bottom panel shows the ozone sub-column over the Antarctic (poleward of 70 HT ht S latitude) integrated between 12 and 20 km for TOMCAT, ML-TOMCAT and MLS averaged over September-October months. We use ozone profile output from a CTM to create a machine-learning-based satellite-corrected long-term chemically (and dynamically) consistent ozone profile data set (hereafter, ML-TOMCAT) for the 1979-2020 time period. [Extracted from the article]

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]

We use a three‐dimensional chemical transport model and satellite observations to investigate Arctic ozone depletion in winter/spring 2019/20 and compare with earlier years. Persistently, low temperatures caused extensive chlorine activation through to March. March‐mean polar‐cap‐mean modeled chemical column ozone loss reached 78 DU (local maximum loss of ∼108 DU in the vortex), similar to that in 2011. However, weak dynamical replenishment of only 59 DU from December to March was key to producing very low (<220 DU) column ozone values. The only other winter to exhibit such weak transport in the past 20 years was 2010/11, so this process is fundamental to causing such low ozone values. A model simulation with peak observed stratospheric total chlorine and bromine loading (from the mid‐1990s) shows that gradual recovery of the ozone layer over the past 2 decades ameliorated the polar cap ozone depletion in March 2020 by ∼20 DU. Plain Language Summary: Ozone depletion in the polar stratosphere is caused by chlorine and bromine species which are activated by low temperatures. Chlorine and bromine are transported to the stratosphere following the surface emission of ozone‐depleting substances (ODSs). While springtime ozone depletion in the Antarctic is almost always large, it is much more variable in the Arctic due to warmer temperatures and more disturbed stratospheric dynamics. Using a three‐dimensional atmospheric chemical transport model and satellite observations, we show that the very low ozone columns observed in March 2020 were a consequence of large chemical destruction and weaker‐than‐normal replenishment by transport. These very low ozone levels are, by some measures, record values despite 2 decades of decreasing stratospheric chlorine and bromine through controls of the Montreal Protocol. Had the meteorology of 2019/20 occurred 2 decades ago, the ozone loss would have been notably larger. The Arctic stratospheric dynamics for 2019/20 are extreme relative to the past 2 decades but fit a compact relationship that links column ozone variations over Arctic and Antarctic winters. Key Points: Large mean Arctic (>63°N) chemical ozone destruction in 2019/20 of 78 DU, similar to other extreme cold winters in the past 2 decadesAnomalously weak wintertime dynamical replenishment of only ∼60 DU contributed strongly to the very low observed ozone column in MarchOzone recovery caused 20 DU less mean Arctic ozone loss in March 2020 than would have occurred with stratospheric halogens at 1995 levels [ABSTRACT FROM AUTHOR]

The recovery and re-calibration of a dataset of vertical aerosol extinction profiles of the 1963/64 stratospheric aerosol layer measured by a searchlight at 32° N in New Mexico, US, is reported. The recovered dataset consists of 105 aerosol extinction profiles at 550 nm that cover the period from December 1963 to December 1964. It is a unique record of the portion of the aerosol cloud from the March 1963 Agung volcanic eruption that was transported into the Northern Hemisphere subtropics. The data-recovery methodology involved re-digitizing the 105 original aerosol extinction profiles from individual Figures within a research report, followed by the re-calibration. It involves inverting the original equation used to compute the aerosol extinction profile to retrieve the corresponding normalized detector response profile. The re-calibration of the original aerosol extinction profiles used Rayleigh extinction profiles calculated from local soundings. Rayleigh and aerosol slant transmission corrections are applied using the MODTRAN code in transmission mode. Also, a best-estimate aerosol phase function was calculated from observations and applied to the entire column. The tropospheric aerosol phase function from an AERONET station in the vicinity of the searchlight location was applied between 2.76 to 11.7 km. The stratospheric phase function, applied for a 12.2 to 35.2 km altitude range, is calculated from particle-size distributions measured by a high-altitude aircraft in the vicinity of the searchlight in early 1964. The original error estimate was updated considering unaccounted errors. Both the re-calibrated aerosol extinction profiles and the re-calibrated stratospheric aerosol optical depth magnitudes showed higher magnitudes than the original aerosol extinction profiles and the original stratospheric aerosol optical depth, respectively. However, the magnitudes of the re-calibrated variables show a reasonable agreement with other contemporary observations. The re-calibrated stratospheric aerosol optical depth demonstrated its consistency with the tropics-to-pole decreasing trend, associated with the major volcanic eruption stratospheric aerosol pattern when compared to the time-coincident stratospheric aerosol optical depth lidar observations at Lexington at 42° N. [ABSTRACT FROM AUTHOR]

Substantial and prolonged enhancements in stratospheric water vapor (SWV) have occurred after large‐magnitude explosive tropical volcanic eruptions, with modified tropopause entry caused by aerosol‐absorptive heating. Here, we analyze the timing and longevity of heating‐driven post‐eruption SWV changes within CMIP6‐VolMIP short‐term climate‐response experiments with the UK Earth System Model (UKESM1). We find aerosol‐absorptive heating causes peak SWV increases of 17% (∼1 ppmv) and 10% (0.5 ppmv) at 100 and 50 hPa, at ∼18 and ∼23 months after a Pinatubo‐like eruption, respectively. We track the temperature response in the tropical lower stratosphere and identify the main SWV increase occurs only after the descending aerosol heating reaches the tropopause, suggesting a key role for aerosol microphysical processes (sedimentation rate). We explore how El Niño–Southern Oscillation variability modulates this effect. Post‐eruption SWV increases are ∼80% stronger for the La Nina phase compared to the ensemble mean. Tropical upwelling strongly mediates this effect. Plain Language Summary: Strong volcanic eruptions, such as the 1991 eruption of Mt Pinatubo, inject a large amount of SO2 directly into the stratosphere, thereby enhancing the stratospheric aerosol layer and causing a short‐term climatic perturbation. Another substantial part of the climatic influence is the change in stratospheric water vapor (SWV), which affects the chemical processes and the radiative budget of the atmosphere. Along with near‐instantaneous injection of water vapor into the stratosphere, volcanic eruptions can indirectly enhance the entry of water vapor into the stratosphere through aerosol‐induced tropopause heating. This work analyses Earth system model experiments designed to explore how volcanic impacts combine with internal climate variability. We find that peak SWV entry mixing ratios occur only within the second post‐eruption year, consistent with the substantially lagged timing of SWV increase seen in post‐Pinatubo satellite measurements. This analysis provides a new perspective on the temporal evolution of the observed post‐Pinatubo SWV increase and an improved quantification of its impacts. Key Points: Aerosol‐induced absorptive‐heating increases stratospheric water vapor (SWV) by up to 17% at 18 months post‐eruption in a Pinatubo‐like experimentAnalyzing simulations by El Niño–Southern Oscillation (ENSO) variability show an 80% larger peak SWV increase occurs if an eruption is followed by a La Niña phaseThe timing of peak SWV increase occurs when volcanic‐aerosol‐induced heating reaches the tropopause, with ENSO modulation of tropical upwelling [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 report the recovery and re-calibration of an extensive dataset of vertical profile measurements of the 1963/64 stratospheric aerosol layer measured from a two-site searchlight measurement facility at White Sands missile base and Sacramento Peak observatory, in New Mexico, US. The recovered dataset comprises 105 profiles of 550nm aerosol extinction (βp(z)) and is part of a longer program of measurements with the US Air Force Cambridge Research Laboratories (AFCRL) searchlight facility that began in February 1963. The recovered series of βp(z) profiles span the 13-month period December 1963 to December 1964 and provide a unique record of the altitude and vertical extent of the Northern Hemisphere dispersed portion of the aerosol cloud from the March 1963 Agung volcanic eruption. The data recovery methodology involved first re-digitizing the 105 original βp(z) profiles (βp(z)) from individual Figures within an AFCRL research report (Elterman, 1966a). The re-calibration involves inverting the original equation used to compute βp(z) in Elterman (1966a; 1966b) to retrieve a normalized detector response (Er(z) Er(35)) profile for each of the 105 re-digitized βp 0(z) profiles. An iterative procedure was then used to compute the re-calibration βp(z) profiles (βp Ra(z)), with the molecular extinction profile calculated with the corresponding daily molecular extinction profile calculated from local soundings, rather than the US Standard Atmosphere 1962 in the original dataset. Two-way molecular and aerosol transmittance corrections are applied using the MODTRAN (MODerate resolution atmospheric TRANsmission) code in transmission mode, applying a best-estimate aerosol phase function calculated from measurements, applied for the entire 2.76 to 35.2 km column. For the tropospheric aerosol transmittance, the AERONET aerosol phase function from White Sands High Energy Laser Systems Test Facility (HELSTF) was applied (2.76 to 10.7 km), a separate stratospheric phase function applied between 11.2 and 35.2 km, calculated from a set of particle size distributions measured by the U-2 high-altitude aircraft over a US region in the vicinity of White Sands in early 1964. Errors were estimated taking as a reference the errors determined in the computation of βp 0(z). Using available tabulated data from the original procedure the errors in the re-digitalization of βp 0(z) and in the retrieval of the Er(z) Er(35) procedures were calculated and later added to the original estimates. Both the βp R(z) and the stratospheric aerosol optical depth magnitudes showed higher magnitudes than βp 0(z) and the original stratospheric aerosol optical depth, however their magnitudes show a reasonable agreement with other contemporary observations. Both the original and recalibration datasets are being submitted to PANGAEA data repository for its storage and public access. [ABSTRACT FROM AUTHOR]

We report the recovery and processing methodology of the first ever multi-year lidar dataset of the stratospheric aerosol layer. A Q-switched ruby lidar measured 66 vertical profiles of 694 nm attenuated backscatter at Lexington, Massachusetts, between January 1964 and August 1965, with an additional nine profile measurements conducted from College, Alaska, during July and August 1964. We describe the processing of the recovered lidar backscattering ratio profiles to produce mid-visible (532 nm) stratospheric aerosol extinction profiles (sAEP 532) and stratospheric aerosol optical depth (sAOD 532) measurements, utilizing a number of contemporary measurements of several different atmospheric variables. Stratospheric soundings of temperature and pressure generate an accurate local molecular backscattering profile, with nearby ozone soundings determining the ozone absorption, which are used to correct for two-way ozone transmittance. Two-way aerosol transmittance corrections are also applied based on nearby observations of total aerosol optical depth (across the troposphere and stratosphere) from sun photometer measurements. We show that accounting for these two-way transmittance effects substantially increases the magnitude of the 1964/1965 stratospheric aerosol layer's optical thickness in the Northern Hemisphere mid-latitudes, then ∼ 50 % larger than represented in the Coupled Model Intercomparison Project 6 (CMIP6) volcanic forcing dataset. Compared to the uncorrected dataset, the combined transmittance correction increases the sAOD 532 by up to 66 % for Lexington and up to 27 % for Fairbanks, as well as individual sAEP 532 adjustments of similar magnitude. Comparisons with the few contemporary measurements available show better agreement with the corrected two-way transmittance values. Within the January 1964 to August 1965 measurement time span, the corrected Lexington sAOD 532 time series is substantially above 0.05 in three distinct periods, October 1964, March 1965, and May–June 1965, whereas the 6 nights the lidar measured in December 1964 and January 1965 had sAOD values of at most ∼ 0.03. The comparison with interactive stratospheric aerosol model simulations of the Agung aerosol cloud shows that, although substantial variation in mid-latitude sAOD 532 are expected from the seasonal cycle in the stratospheric circulation, the Agung cloud's dispersion from the tropics would have been at its strongest in winter and weakest in summer. The increasing trend in sAOD from January to July 1965, also considering the large variability, suggests that the observed variations are from a different source than Agung, possibly from one or both of the two eruptions that occurred in 1964/1965 with a Volcanic Explosivity Index (VEI) of 3: Trident, Alaska, and Vestmannaeyjar, Heimaey, south of Iceland. A detailed error analysis of the uncertainties in each of the variables involved in the processing chain was conducted. Relative errors for the uncorrected sAEP 532 were 54 % for Fairbanks and 44 % Lexington. For the corrected sAEP 532 the errors were 61 % and 64 %, respectively. The analysis of the uncertainties identified variables that with additional data recovery and reprocessing could reduce these relative error levels. Data described in this work are available at 10.1594/PANGAEA.922105 (Antuña-Marrero et al., 2020a). [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]

The Stratospheric Sulfur and its Role in Climate (SSiRC) Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP) explores uncertainties in the processes that connect volcanic emission of sulfur gas species and the radiative forcing associated with the resulting enhancement of the stratospheric aerosol layer. The central aim of ISA-MIP is to constrain and improve interactive stratospheric aerosol models and reduce uncertainties in the stratospheric aerosol forcing by comparing results of standardized model experiments with a range of observations. In this paper we present four co-ordinated inter-model experiments designed to investigate key processes which influence the formation and temporal development of stratospheric aerosol in different time periods of the observational record. The Background (BG) experiment will focus on microphysics and transport processes under volcanically quiescent conditions, when the stratospheric aerosol is controlled by the transport of aerosols and their precursors from the troposphere to the stratosphere. The Transient Aerosol Record (TAR) experiment will explore the role of small- to moderate-magnitude volcanic eruptions, anthropogenic sulfur emissions, and transport processes over the period 1998-2012 and their role in the warming hiatus. Two further experiments will investigate the stratospheric sulfate aerosol evolution after major volcanic eruptions. The Historical Eruptions SO2 Emission Assessment (HErSEA) experiment will focus on the uncertainty in the initial emission of recent large-magnitude volcanic eruptions, while the Pinatubo Emulation in Multiple models (PoEMS) experiment will provide a comprehensive uncertainty analysis of the radiative forcing from the 1991 Mt Pinatubo eruption. [ABSTRACT FROM AUTHOR]

The Stratospheric Sulfur and its Role in Climate (SSiRC) interactive stratospheric aerosol model intercomparison project (ISA-MIP) explores uncertainties in the processes that connect volcanic emission of sulphur gas species and the radiative forcing associated with the resulting enhancement of the stratospheric aerosol layer. The central aim of ISA-MIP is to constrain and improve interactive stratospheric aerosol models and reduce uncertainties in the stratospheric aerosol forcing by comparing results of standardized model experiments with a range of observations. In this paper we present 4 co-ordinated inter-model experiments designed to investigate key processes which influence the formation and temporal development of stratospheric aerosol in different time periods of the observational record. The Background (BG) experiment will focus on microphysics and transport processes under volcanically quiescent conditions, when the stratospheric aerosol is controlled by the transport of aerosols and their precursors from the troposphere to the stratosphere. The Transient Aerosol Record (TAR) experiment will explore the role of small- to moderate-magnitude volcanic eruptions, anthropogenic sulphur emissions and transport processes over the period 1998-2012 and their role in the warming hiatus. Two further experiments will investigate the stratospheric sulphate aerosol evolution after major volcanic eruptions. The Historical Eruptions SO2 Emission Assessment (HErSEA) experiment will focus on the uncertainty in the initial emission of recent large-magnitude volcanic eruptions, while the Pinatubo Emulation in Multiple models (PoEMS) experiment will provide a comprehensive uncertainty analysis of the radiative forcing from the 1991 Mt. Pinatubo eruption. [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 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 70km), or 70 pressure levels that are approximately 1km apart (878.4hPa to 0.046hPa). 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 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 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: (i) Adjustments of measurements to account for biases and drifts between different data sources (using a chemistry-transport model 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. However, compared to SWOOSH, BSVertOzone additionally covers the troposphere. [ABSTRACT FROM AUTHOR]

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 intermodel 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. [ABSTRACT FROM AUTHOR]

The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol data set for each experiment to minimize differences in the applied volcanic forcing. It defines a set of initial conditions to assess how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input data sets to be used. [ABSTRACT FROM AUTHOR]

We present an overview of state-of-the-art chemistry-climate and -transport models that are used within the Chemistry-Climate Model Initiative (CCMI). 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, 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 recommendations for simulations have been followed is necessary to understand model response 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 simulations with the aim to inform CCMI data users. [ABSTRACT FROM AUTHOR]

The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Climate Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the model intercomparison project on the climate response to volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol dataset for each experiment to eliminate differences in the applied volcanic forcing, and defines a set of initial conditions to determine how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically-forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input datasets to be used. [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]

The Stratospheric Sulfur and its Role in Climate (SSiRC) interactive stratospheric aerosol model intercomparison project (ISA-MIP) explores uncertainties in the processes that connect volcanic emission of sulphur gas species and the radiative forcing associated with the resulting enhancement of the stratospheric aerosol layer. The central aim of ISA-MIP is to constrain and improve interactive stratospheric aerosol models and reduce uncertainties in the stratospheric aerosol forcing by comparing results of standardized model experiments with a range of observations. In this paper we present 4 co-ordinated inter-model experiments designed to investigate key processes which influence the formation and temporal development of stratospheric aerosol in different time periods of the observational record. The "Background" (BG) experiment will focus on microphysics and transport processes under volcanically quiescent conditions, when the stratospheric aerosol is controlled by the transport of aerosols and their precursors from the troposphere to the stratosphere. The "Transient Aerosol Record" (TAR) experiment will explore the role of small- to moderate-magnitude volcanic eruptions, anthropogenic sulphur emissions and transport processes over the period 1998-2012 and their role in the warming hiatus. Two further experiments will investigate the stratospheric sulphate aerosol evolution after major volcanic eruptions. The "Historical Eruptions SO2 Emission Assessment" (HErSEA) experiment will focus on the uncertainty in the initial emission of recent large-magnitude volcanic eruptions, while the "Pinatubo Emulation in Multiple models" (PoEMS) experiment will provide a comprehensive uncertainty analysis of the radiative forcing from the 1991 Mt. Pinatubo eruption. [ABSTRACT FROM AUTHOR]