Analysis and attribution of total column ozone changes over the Tibetan Plateau during 1979–2017

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

Fifteen Years of HFC-134a Satellite Observations: Comparisons With SLIMCAT Calculations

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

Exploring How Eruption Source Parameters Affect Volcanic Radiative Forcing Using Statistical Emulation

The radiative forcing caused by a volcanic eruption is dependent on several eruption source parameters such as the mass of sulfur dioxide (SO2) emitted, the eruption column height, and the eruption latitude. General circulation models with prognostic aerosol and chemistry schemes can be used to investigate how each parameter influences the volcanic forcing. However, the range of multidimensional parameter space that can be explored is restricted because such simulations are computationally expensive. Here we use statistical emulation to explore the radiative impact of eruptions over a wide covarying range of SO2 emission magnitudes, injection heights, and eruption latitudes based on only 30 simulations. We use the emulators to build response surfaces to visualize and predict the sulfate aerosol e-folding decay time, the stratospheric aerosol optical depth, and net radiative forcing of thousands of different eruptions. We find that the volcanic stratospheric aerosol optical depth and net radiative forcing are primarily determined by the mass of SO2 emitted, but eruption latitude is the most important parameter in determining the sulfate aerosol e-folding decay time. The response surfaces reveal joint effects of the eruption source parameters in influencing the net radiative forcing, such as a stronger influence of injection height for tropical eruptions than high-latitude eruptions. We also demonstrate how the emulated response surfaces can be used to find all combinations of eruption source parameters that produce a particular volcanic response, often revealing multiple solutions

Effects of reanalysis forcing fields on ozone trends and age of air from a chemical transport model

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

A single-peak-structured solar cycle signal in stratospheric ozone based on Microwave Limb Sounder observations and model simulations

Until now our understanding of the 11-year solar cycle signal (SCS) in stratospheric ozone has been largely based on high-quality but sparse ozone profiles from the Stratospheric Aerosol and Gas Experiment (SAGE) II or coarsely resolved ozone profiles from the nadir-viewing Solar Backscatter Ultraviolet Radiometer (SBUV) satellite instruments. Here, we analyse 16 years (2005–2020) of ozone profile measurements from the Microwave Limb Sounder (MLS) instrument on the Aura satellite to estimate the 11-year SCS in stratospheric ozone. Our analysis of Aura-MLS data suggests a single-peak-structured SCS profile (about 3 % near 4 hPa or 40 km) in tropical stratospheric ozone, which is significantly different to the SAGE II and SBUV-based double-peak-structured SCS. We also find that MLS-observed ozone variations are more consistent with ozone from our control model simulation that uses Naval Research Laboratory (NRL) v2 solar fluxes. However, in the lowermost stratosphere modelled ozone shows a negligible SCS compared to about 1 % in Aura-MLS data. An ensemble of ordinary least squares (OLS) and three regularised (lasso, ridge and elastic net) linear regression models confirms the robustness of the estimated SCS. In addition, our analysis of MLS and model simulations shows a large SCS in the Antarctic lower stratosphere that was not seen in earlier studies. We also analyse chemical transport model simulations with alternative solar flux data. We find that in the upper (and middle) stratosphere the model simulation with Solar Radiation and Climate Experiment (SORCE) satellite solar fluxes is also consistent with the MLS-derived SCS and agrees well with the control simulation and one which uses Spectral and Total Irradiance Reconstructions (SATIRE) solar fluxes. Hence, our model simulation suggests that with recent adjustments and corrections, SORCE data can be used to analyse effects of solar flux variations. Furthermore, analysis of a simulation with fixed solar fluxes and one with fixed (annually repeating) meteorology confirms that the implicit dynamical SCS in the (re)analysis data used to force the model is not enough to simulate the observed SCS in the middle and upper stratospheric ozone. Finally, we argue that the overall significantly different SCS compared to previous estimates might be due to a combination of different factors such as much denser MLS measurements, almost linear stratospheric chlorine loading changes over the analysis period, variations in the stratospheric dynamics as well as relatively unperturbed stratospheric aerosol layer that might have influenced earlier analyses

An updated version of a gap-free monthly mean zonal mean ozone database

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 70km), or 70 pressure levels that are approximately 1km apart (878.4 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 (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. However, compared to SWOOSH, BSVertOzone additionally covers the troposphere. Version 1.0 of BSVertOzone is publicly available at https://doi.org/http://doi.org/10.5281/zenodo.1217184

Evaluating the simulated radiative forcings, aerosol properties, and stratospheric warmings from the 1963 Mt Agung, 1982 El Chichón, and 1991 Mt Pinatubo volcanic aerosol clouds

Accurately quantifying volcanic impacts on climate is a key requirement for robust attribution of anthropogenic climate change. Here we use the Unified Model – United Kingdom Chemistry and Aerosol (UM-UKCA) composition–climate model to simulate the global dispersion of the volcanic aerosol clouds from the three largest eruptions of the 20th century: 1963 Mt Agung, 1982 El Chichón, and 1991 Mt Pinatubo. The model has interactive stratospheric chemistry and aerosol microphysics, with coupled aerosol–radiation interactions for realistic composition–dynamics feedbacks. Our simulations align with the design of the Interactive Stratospheric Aerosol Model Intercomparison (ISA-MIP) “Historical Eruption SO2 Emissions Assessment”. For each eruption, we perform three-member ensemble model experiments for upper, mid-point, and lower estimates of SO2 emission, each re-initialised from a control run to approximately match the observed transition in the phase of the quasi-biennial oscillation (QBO) in the 6 months after the eruptions. With this experimental design, we assess how each eruption's emitted SO2 translates into a tropical reservoir of volcanic aerosol and analyse the subsequent dispersion to mid-latitudes. We compare the simulations to the volcanic forcing datasets (e.g. Space-based Stratospheric Aerosol Climatology (GloSSAC); Sato et al., 1993, and Ammann et al., 2003) that are used in historical integrations for the two most recent Coupled Model Intercomparison Project (CMIP) assessments. For Pinatubo and El Chichón, we assess the vertical extent of the simulated volcanic clouds by comparing modelled extinction to the Stratospheric Aerosol and Gas Experiment (SAGE-II) v7.0 satellite measurements and to 1964–1965 Northern Hemisphere ground-based lidar measurements for Agung. As an independent test for the simulated volcanic forcing after Pinatubo, we also compare simulated shortwave (SW) and longwave (LW) top-of-the-atmosphere radiative forcings to the flux anomalies measured by the Earth Radiation Budget Experiment (ERBE) satellite instrument. For the Pinatubo simulations, an injection of 10 to 14 Tg SO2 gives the best match to the High Resolution Infrared Sounder (HIRS) satellite-derived global stratospheric sulfur burden, with good agreement also with SAGE-II mid-visible and near-infra-red extinction measurements. This 10–14 Tg range of emission also generates a heating of the tropical stratosphere that is consistent with the temperature anomaly present in the ERA-Interim reanalysis. For El Chichón, the simulations with 5 and 7 Tg SO2 emission give best agreement with the observations. However, these simulations predict a much deeper volcanic cloud than represented in the GloSSAC dataset, which is largely based on an interpolation between Stratospheric Aerosol Measurements (SAM-II) satellite and aircraft measurements. In contrast, these simulations show much better agreement during the SAGE-II period after October 1984. For 1963 Agung, the 9 Tg simulation compares best to the forcing datasets with the model capturing the lidar-observed signature of the altitude of peak extinction descending from 20 km in 1964 to 16 km in 1965. Overall, our results indicate that the downward adjustment to SO2 emission found to be required by several interactive modelling studies when simulating Pinatubo is also needed when simulating the Agung and El Chichón aerosol clouds. This strengthens the hypothesis that interactive stratospheric aerosol models may be missing an important removal or re-distribution process (e.g. effects of co-emitted ash) which changes how the tropical reservoir of volcanic aerosol evolves in the initial months after an eruption. Our model comparisons also identify potentially important inhomogeneities in the CMIP6 dataset for all three eruption periods that are hard to reconcile with variations predicted in the interactive stratospheric aerosol simulations. We also highlight large differences between the CMIP5 and CMIP6 volcanic aerosol datasets for the Agung and El Chichón periods. Future research should aim to reduce this uncertainty by reconciling the datasets with additional stratospheric aerosol observations

Interactive stratospheric aerosol models' response to different amounts and altitudes of SO2 injection during the 1991 Pinatubo eruption

A previous model intercomparison of the Tambora aerosol cloud has highlighted substantial differences among simulated volcanic aerosol properties in the pre-industrial stratosphere and has led to questions about the applicability of global aerosol models for large-magnitude explosive eruptions prior to the observational period. Here, we compare the evolution of the stratospheric aerosol cloud following the well-observed June 1991 Mt. Pinatubo eruption simulated with six interactive stratospheric aerosol microphysics models to a range of observational data sets. Our primary focus is on the uncertainties regarding initial SO2 emission following the Pinatubo eruption, as prescribed in the Historical Eruptions SO2 Emission Assessment experiments (HErSEA), in the framework of the Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP). Six global models with interactive aerosol microphysics took part in this study: ECHAM6-SALSA, EMAC, ECHAM5-HAM, SOCOL-AERv2, ULAQ-CCM, and UM-UKCA. Model simulations are performed by varying the SO2 injection amount (ranging between 5 and 10TgS) and the altitude of injection (between 18-25km). The comparisons show that all models consistently demonstrate faster reduction from the peak in sulfate mass burden in the tropical stratosphere. Most models also show a stronger transport towards the extratropics in the Northern Hemisphere, at the expense of the observed tropical confinement, suggesting a much weaker subtropical barrier in all the models, which results in a shorter e-folding time compared to the observations. Furthermore, simulations in which more than 5TgS in the form of SO2 is injected show an initial overestimation of the sulfate burden in the tropics and, in some models, in the Northern Hemisphere and a large surface area density a few months after the eruption compared to the values measured in the tropics and the in situ measurements over Laramie. This draws attention to the importance of including processes such as the ash injection for the removal of the initial SO2 and aerosol lofting through local heating

Large Impacts, Past and Future, of Ozone-Depleting Substances on Brewer-Dobson Circulation Trends: A Multimodel Assessment

Substantial increases in the atmospheric concentration of well‐mixed greenhouse gases (notably CO2), such as those projected to occur by the end of the 21st century under large radiative forcing scenarios, have long been known to cause an acceleration of the Brewer‐Dobson circulation (BDC) in climate models. More recently, however, several single‐model studies have proposed that ozone‐depleting substances might also be important drivers of BDC trends. As these studies were conducted with different forcings over different periods, it is difficult to combine them to obtain a robust quantitative picture of the relative importance of ozone‐depleting substances as drivers of BDC trends. To this end, we here analyze—over identical past and future periods—the output from 20 similarly forced models, gathered from two recent chemistry‐climate modeling intercomparison projects. Our multimodel analysis reveals that ozone‐depleting substances are responsible for more than half of the modeled BDC trends in the two decades 1980–2000. We also find that, as a consequence of the Montreal Protocol, decreasing concentrations of ozone‐depleting substances in coming decades will strongly decelerate the BDC until the year 2080, reducing the age‐of‐air trends by more than half, and will thus substantially mitigate the impact of increasing CO2. As ozone‐depleting substances impact BDC trends, primarily, via the depletion/recovery of stratospheric ozone over the South Pole, they impart seasonal and hemispheric asymmetries to the trends which may offer opportunities for detection in coming decades