Search

Dimethyl sulfide (DMS) is an important trace gas emitted from the ocean. The oxidation of DMS has long been recognised as being important for global climate through the role DMS plays in setting the sulfate aerosol background in the troposphere. However, the mechanisms in which DMS is oxidised are very complex and have proved elusive to accurately determine in spite of decades of research. As a result the representation of DMS oxidation in global chemistry-climate models is often greatly simplified. Recent field observations, laboratory and ab initio studies have prompted renewed efforts in understanding the DMS oxidation mechanism, with implications for constraining the uncertainty in the oxidation mechanism of DMS as incorporated in global chemistry-climate models. Here we build on recent evidence and develop a new DMS mechanism for inclusion in the UKCA chemistry-climate model. We compare our new mechanism (CS2-HPMTF) to a number of existing mechanisms used in UKCA (including the highly simplified 3 reactions, 2 species, ST mechanism used in CMIP6 studies) and to a range of recently developed mechanisms reported in the literature through a series of global and box model experiments. Global model runs with the new mechanism enable us to simulate the global distribution of hydroperoxyl methyl thioformate (HPMTF), which we calculate to have a burden of 2.6–26 Gg S (in good agreement with the literature range of 0.7–18 Gg S). We show that the sinks of HPMTF dominate uncertainty in the budget, not the rate of the isomerisation reaction forming it, and that based on the observed DMS/HPMTF ratio, rapid cloud uptake of HPMTF worsens the model-observation comparison. Our box model experiments highlight that there is significant variance in simulated secondary oxidation products from DMS across mechanisms used in the literature, with significant divergence in the sensitivity of these products to temperature exhibited; especially for methane sulfonic acid (MSA). Our global model studies show that our updated DMS scheme performs better than the current scheme used in UKCA when compared against a suite of surface and aircraft observations. However, sensitivity studies underscore the need for further laboratory and observational constraints.

Coupled surface-atmosphere high-resolution simulations were carried out to understand radiation fog development and persistence in a city surrounded by complex terrain. The controls of mesoscale meteorology and microscale soil moisture heterogeneity on fog were investigated using case studies for the city of Christchurch, New Zealand. Numerical model simulations from the synoptic to micro- scale were carried out using the Weather Research and Forecasting (WRF) model and the Parallelised Large-Eddy Simulation Model (PALM). Heterogeneous soil moisture, land use, and topography were included. The spatial heterogeneity of soil moisture was derived using Landsat 8 (https://www.usgs.gov/landsat-missions/landsat-8, last access: 10 October 2022) satellite imagery and ground-based meteorological observations. Eight simulations were carried out under identical meteorological conditions. One contained homogeneous soil moisture and one contained heterogeneous soil moisture derived from Landsat 8 imagery. For the other six simulations, the soil moisture heterogeneity magnitudes were amplified following the observed spatial distribution to aid our understanding of the impact of soil moisture heterogeneity. Our results showed that soil moisture heterogeneity did not significantly change the general spatial structure of near-surface fog occurrence, even when amplified. However, compared to homogeneous soil moisture, spatial heterogeneity in soil moisture leads to significant changes in radiation fog duration. The resulting changes in fog duration can be more than 50 minutes, although such changes are not directly correlated with spatial variations in soil moisture. The simulations showed that the mesoscale (104 to 2 × 105 m) meteorology controls the location of fog occurrence, while soil moisture heterogeneity alters fog duration at the microscale (10−2 to 103 m). Our results highlight the importance of including soil moisture heterogeneity for accurate spatiotemporal fog forecasting.

Microplastics are now recognized as widespread contaminants in the atmosphere, where, due to their small size and low density, they can be transported with winds around the Earth1–25. Atmospheric aerosols, such as mineral dust and other types of airborne particulate matter, influence Earth’s climate by absorbing and scattering radiation (direct radiative effects) and their impacts are commonly quantified with the effective radiative forcing (ERF) metric26. However, the radiative effects of airborne microplastics and associated implications for global climate are unknown. Here we present calculations of the optical properties and direct radiative effects of airborne microplastics (excluding aerosol–cloud interactions). The ERF of airborne microplastics is computed to be 0.044 ± 0.399 milliwatts per square metre in the present-day atmosphere assuming a uniform surface concentration of 1 microplastic particle per cubic metre and a vertical distribution up to 10 kilometres altitude. However, there are large uncertainties in the geographical and vertical distribution of microplastics. Assuming that they are confined to the boundary layer, shortwave effects dominate and the microplastic ERF is approximately −0.746 ± 0.553 milliwatts per square metre. Compared with the total ERF due to aerosol–radiation interactions27 (−0.71 to −0.14 watts per square metre), the microplastic ERF is small. However, plastic production has increased rapidly over the past 70 years28; without serious attempts to overhaul plastic production and waste-management practices, the abundance and ERF of airborne microplastics will continue to increase. Preliminary modelling of airborne microplastics suggests that they may be exerting a minor cooling influence on the present-day atmosphere, and continued production could have increasing effects on the climate system in future.

In recent years, airborne microplastics have been identified in a range of remote environments. However, data throughout the Southern Hemisphere, in particular Antarctica, are largely absent to date. We collected snow samples from 19 sites across the Ross Island region of Antarctica. Suspected microplastic particles were isolated and their composition confirmed using micro-Fourier transform infrared spectroscopy (µFTIR). We identified microplastics in all Antarctic snow samples at an average concentration of 29 particles L−1, with fibres the most common morphotype and polyethylene terephthalate (PET) the most common polymer. To investigate sources, backward air mass trajectories were run from the time of sampling. These indicate potential long-range transportation of up to 6000 km, assuming a residence time of 6.5 d. Local sources were also identified as potential inputs into the environment as the polymers identified were consistent with those used in clothing and equipment from nearby research stations. This study adds to the growing body of literature regarding microplastics as a ubiquitous airborne pollutant and establishes their presence in Antarctica.

The discovery of atmospheric micro(nano)plastic transport and ocean-atmosphere exchange points to a highly complex marine plastic cycle, with negative implications for human and ecosystem health. Yet, observations are currently limited. In this Perspective, we quantify the processes and fluxes of the marine-atmospheric micro(nano)plastic cycle, with the aim of highlighting the remaining unknowns in atmospheric micro(nano)plastic transport. Between 0.013 and 25 million metric tons per year of micro(nano)plastics are potentially being transported within the marine atmosphere and deposited in the oceans. However, the high uncertainty in these marine-atmospheric fluxes is related to data limitations and a lack of study intercomparability. To address the uncertainties and remaining knowledge gaps in the marine-atmospheric micro(nano)plastic cycle, we propose a future global marine-atmospheric micro(nano)plastic observation strategy, incorporating novel sampling methods and the creation of a comparable, harmonized and global data set. Together with long-term observations and intensive investigations, this strategy will help to define the trends in marine-atmospheric pollution and any responses to future policy and management actions. Atmospheric transport of microplastics could be a major source of plastic pollution to the ocean, yet observations currently remain limited. This Perspective quantifies the known budgets of the marine-atmospheric micro(nano)plastic cycle and proposes a future global observation strategy.

With low concentrations of tropospheric aerosol, the Southern Ocean offers a “natural laboratory” for studies of aerosol–cloud interactions. Aerosols over the Southern Ocean are produced from biogenic activity in the ocean, which generates sulfate aerosol via dimethylsulfide (DMS) oxidation, and from strong winds and waves that lead to bubble bursting and sea spray emission. Here, we evaluate the representation of Southern Ocean aerosols in the Hadley Centre Global Environmental Model version 3, Global Atmosphere 7.1 (HadGEM3-GA7.1) chemistry–climate model. Compared with aerosol optical depth (AOD) observations from two satellite instruments (the Moderate Resolution Imaging Spectroradiometer, MODIS-Aqua c6.1, and the Multi-angle Imaging Spectroradiometer, MISR), the model simulates too-high AOD during winter and too-low AOD during summer. By switching off DMS emission in the model, we show that sea spray aerosol is the dominant contributor to AOD during winter. In turn, the simulated sea spray aerosol flux depends on near-surface wind speed. By examining MODIS AOD as a function of wind speed from the ERA-Interim reanalysis and comparing it with the model, we show that the sea spray aerosol source function in HadGEM3-GA7.1 overestimates the wind speed dependency. We test a recently developed sea spray aerosol source function derived from measurements made on a Southern Ocean research voyage in 2018. In this source function, the wind speed dependency of the sea spray aerosol flux is less than in the formulation currently implemented in HadGEM3-GA7.1. The new source function leads to good agreement between simulated and observed wintertime AODs over the Southern Ocean; however, it reveals partially compensating errors in DMS-derived AOD. While previous work has tested assumptions regarding the seawater climatology or sea–air flux of DMS, we test the sensitivity of simulated AOD, cloud condensation nuclei and cloud droplet number concentration to three atmospheric sulfate chemistry schemes. The first scheme adds DMS oxidation by halogens and the other two test a recently developed sulfate chemistry scheme for the marine troposphere; one tests gas-phase chemistry only, while the second adds extra aqueous-phase sulfate reactions. We show how simulated sulfur dioxide and sulfuric acid profiles over the Southern Ocean change as a result and how the number concentration and particle size of the soluble Aitken, accumulation and coarse aerosol modes are affected. The new DMS chemistry scheme leads to a 20 % increase in the number concentration of cloud condensation nuclei and cloud droplets, which improves agreement with observations. Our results highlight the importance of atmospheric chemistry for simulating aerosols and clouds accurately over the Southern Ocean.

Studies have recently reported statistically significant relationships between observed year-to-year spring Antarctic ozone variability and the Southern Hemisphere annular mode and surface temperatures in spring–summer. This study investigates whether current chemistry–climate models (CCMs) can capture these relationships, in particular, the connection between November total column ozone (TCO) and Australian summer surface temperatures, where years with anomalously high TCO over the Antarctic polar cap tend to be followed by warmer summers. The interannual ozone–temperature teleconnection is examined over the historical period in the observations and simulations from the Whole Atmosphere Community Climate Model (WACCM) and nine other models participating in the Chemistry–Climate Model Initiative (CCMI). There is a systematic difference between the WACCM experiments forced with prescribed observed sea surface temperatures (SSTs) and those with an interactive ocean. Strong correlations between TCO and Australian temperatures are only obtained for the uncoupled experiment, suggesting that the SSTs could be important for driving both variations in Australian temperatures and the ozone hole, with no causal link between the two. Other CCMI models also tend to capture this relationship with more fidelity when driven by observed SSTs, although additional research and targeted modeling experiments are required to determine causality and further explore the role of model biases and observational uncertainty. The results indicate that CCMs can reproduce the relationship between spring ozone and summer Australian climate reported in observational studies, suggesting that incorporating ozone variability could improve seasonal predictions; however, more work is required to understand the difference between the coupled and uncoupled simulations.

Airborne microplastics have been identified throughout the Northern Hemisphere in several studies. Synthesising measurements from multiple studies to derive a global distribution of airborne microplastics is difficult because no standard sampling protocol currently exists. Furthermore, measurements from the Southern Hemisphere are largely absent. We undertook a pilot study to test four different deposition samplers and their efficacy in collecting microplastics: a bottle with a funnel attached, an open beaker, a petri dish covered in double-sided adhesive tape and an automatic wet deposition collector. The four samplers were deployed to a suburban site in Christchurch, New Zealand, for four 6-day sampling periods. It was originally hypothesised that the funnel would improve sample retention by limiting resuspension; however, the open beaker was found to be similarly effective. We were unable to assess the effectiveness of the automatic wet deposition collector robustly due to low rainfall during the sampling periods. The adhesive tape sampler proved impractical. Particles collected from all samplers were inspected and classified as microplastics according to a visual screening criteria. Fibres, films, fragments and beads were identified, with fibres being the dominant morphotype (90%); however, only 10% of suspected microplastics were confirmed as plastic following μFTIR spectroscopy. Overall, we recommend the use of a funnel sampler or open beaker for future deposition studies. This is the first study of airborne microplastics in New Zealand and adds to a growing body of evidence as to the widespread nature of microplastics in the atmosphere.

A set of Python-based tools, WRF4PALM, has been developed for offline-nesting of the PALM model system 6.0 into the Weather Research and Forecasting (WRF) modelling system. Time-dependent boundary conditions of the atmosphere are critical for accurate representation of microscale meteorological dynamics in high resolution real-data simulations. WRF4PALM generates initial and boundary conditions from WRF outputs to provide time-varying meteorological forcing for PALM. The WRF model has been used across the atmospheric science community for a broad range of multidisciplinary applications. The PALM model system 6.0 is a turbulence-resolving large-eddy simulation model with an additional Reynolds averaged Navier–Stokes (RANS) mode for atmospheric and oceanic boundary layer studies at microscale (Maronga et al., 2020). Currently PALM has the capability to ingest output from the regional scale Consortium for Small-scale Modelling (COSMO) atmospheric prediction model. However, COSMO is not an open source model which requires a licence agreement for operational use or academic research (). This paper describes and validates the new free and open-source WRF4PALM tools (available on ). Two case studies using WRF4PALM are presented for Christchurch, New Zealand, which demonstrate successful PALM simulations driven by meteorological forcing from WRF outputs. The WRF4PALM tools presented here can potentially be used for micro- and mesoscale studies worldwide, for example in boundary layer studies, air pollution dispersion modelling, wildfire emissions and spread, urban weather forecasting, and agricultural meteorology.

We studied sulfate aerosols over the Southern Ocean using the atmosphere-only climate model HadGEM3-GA7.1. The model contains biases in the aerosol seasonal variability over the Southern Ocean (40°S to 60°S), which cascade to uncertainties in aerosol-cloud interactions. Aerosols over the Southern Ocean are primarily natural in origin, such as sea spray aerosol and sulfate aerosol formed by phytoplankton-produced dimethyl sulfide (DMS).The current sulfate chemistry scheme implemented in the model simplifies the oxidation pathways for DMS, which has been identified as a major source of the seasonal bias present. The simulations performed here incorporate a comprehensive sulfate scheme in both the gas and aqueous-phase. An intermediate complexity biogeochemical dynamic model, MEDUSA, simulated a global climatology of seawater DMS, which is compared with a seawater DMS observational dataset from 2011. We compared the seasonality of sulfate aerosols over the Southern Ocean, and the global distribution using the two seawater DMS climatologies. Simulated aerosols over the Southern Ocean were evaluated against satellite and in-situ observations. The results show the impact of seawater DMS on sulfate aerosols and their influence on cloud formation.

With low concentrations of tropospheric aerosol, the Southern Ocean offers a "natural laboratory" for studies of aerosol–cloud interactions. Aerosols over the Southern Ocean are produced from biogenic activity in the ocean, which generates sulfate aerosol via dimethylsulfide (DMS) oxidation, and from strong winds and waves that lead to bubble bursting and sea spray emission. Here, we evaluate the representation of Southern Ocean aerosols in the Hadley Centre Global Environmental Model version 3, Global Atmosphere 7.1 (HadGEM3-GA7.1) chemistry–climate model. Compared with aerosol optical depth (AOD) observations from two satellite instruments (the Moderate Resolution Imaging Spectroradiometer, MODIS-Aqua c6.1, and the Multi-angle Imaging Spectroradiometer, MISR), the model simulates too-high AOD during winter and too-low AOD during summer. By switching off DMS emission in the model, we show that sea spray aerosol is the dominant contributor to AOD during winter. In turn, the simulated sea spray aerosol flux depends on near-surface wind speed. By examining MODIS AOD as a function of wind speed from the ERA-Interim reanalysis and comparing it with the model, we show that the sea spray aerosol source function in HadGEM3-GA7.1 overestimates the wind speed dependency. We test a recently developed sea spray aerosol source function derived from measurements made on a Southern Ocean research voyage in 2018. In this source function, the wind speed dependency of the sea spray aerosol flux is less than in the formulation currently implemented in HadGEM3-GA7.1. The new source function leads to good agreement between simulated and observed wintertime AODs over the Southern Ocean; however, it reveals partially compensating errors in DMS-derived AOD. While previous work has tested assumptions regarding the seawater climatology or sea–air flux of DMS, we test the sensitivity of simulated AOD, cloud condensation nuclei and cloud droplet number concentration to three atmospheric sulfate chemistry schemes. The first scheme adds DMS oxidation by halogens and the other two test a recently developed sulfate chemistry scheme for the marine troposphere; one tests gas-phase chemistry only, while the second adds extra aqueous-phase sulfate reactions. We show how simulated sulfur dioxide and sulfuric acid profiles over the Southern Ocean change as a result and how the number concentration and particle size of the soluble Aitken, accumulation and coarse aerosol modes are affected. The new DMS chemistry scheme leads to a 20% increase in the number concentration of cloud condensation nuclei and cloud droplets, which improves agreement with observations. Our results highlight the importance of atmospheric chemistry for simulating aerosols and clouds accurately over the Southern Ocean.

Our understanding of the processes that control the burden and budget of tropospheric ozone has changed dramatically over the last 60 years. Models are the key tools used to understand these changes, and these underscore that there are many processes important in controlling the tropospheric ozone budget. In this critical review, we assess our evolving understanding of these processes, both physical and chemical. We review model simulations from the International Global Atmospheric Chemistry Atmospheric Chemistry and Climate Model Intercomparison Project and Chemistry Climate Modelling Initiative to assess the changes in the tropospheric ozone burden and its budget from 1850 to 2010. Analysis of these data indicates that there has been significant growth in the ozone burden from 1850 to 2000 (approximately 43 ± 9%) but smaller growth between 1960 and 2000 (approximately 16 ± 10%) and that the models simulate burdens of ozone well within recent satellite estimates. The Chemistry Climate Modelling Initiative model ozone budgets indicate that the net chemical production of ozone in the troposphere plateaued in the 1990s and has not changed since then inspite of increases in the burden. There has been a shift in net ozone production in the troposphere being greatest in the northern mid and high latitudes to the northern tropics, driven by the regional evolution of precursor emissions. An analysis of the evolution of tropospheric ozone through the 21st century, as simulated by Climate Model Intercomparison Project Phase 5 models, reveals a large source of uncertainty associated with models themselves (i.e., in the way that they simulate the chemical and physical processes that control tropospheric ozone). This structural uncertainty is greatest in the near term (two to three decades), but emissions scenarios dominate uncertainty in the longer term (2050–2100) evolution of tropospheric ozone. This intrinsic model uncertainty prevents robust predictions of near-term changes in the tropospheric ozone burden, and we review how progress can be made to reduce this limitation.

The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6 µm ozone band is a fundamental quantity for understanding chemistry–climate coupling. However, observed TOA fluxes are hard to estimate as they exhibit considerable variability in space and time that depend on the distributions of clouds, ozone (O3), water vapor (H2O), air temperature (Ta), and surface temperature (Ts). Benchmarking present-day fluxes and quantifying the relative influence of their drivers is the first step for estimating climate feedbacks from ozone radiative forcing and predicting radiative forcing evolution. To that end, we constructed observational instantaneous radiative kernels (IRKs) under clear-sky conditions, representing the sensitivities of the TOA flux in the 9.6 µm ozone band to the vertical distribution of geophysical variables, including O3, H2O, Ta, and Ts based upon the Aura Tropospheric Emission Spectrometer (TES) measurements. Applying these kernels to present-day simulations from the Chemistry-Climate Model Initiative (CCMI) project as compared to a 2006 reanalysis assimilating satellite observations, we show that the models have large differences in TOA flux, attributable to different geophysical variables. In particular, model simulations continue to diverge from observations in the tropics, as reported in previous studies of the Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) simulations. The principal culprits are tropical middle and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mW m−2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mW m−2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mW m−2). We found that the atmospheric component (AM3) of the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model and Canadian Middle Atmosphere Model (CMAM) have the lowest TOA flux biases globally but are a result of cancellation of opposite biases due to different processes. Overall, the multi-model ensemble mean bias is −133±98 mW m−2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 and these competing effects add more uncertainties on the ozone radiative forcing. We find that the inter-model TOA outgoing longwave radiation (OLR) difference is well anti-correlated with their ozone band flux bias. This suggests that there is significant radiative compensation in the calculation of model outgoing longwave radiation., Atmospheric Chemistry and Physics, 20 (1), ISSN:1680-7375, ISSN:1680-7367

30 pags., 11 figs., 5 tabs., We quantify the stratospheric injection of brominated very short-lived substances (VSLS) based on aircraft observations acquired in winter 2014 above the Tropical Western Pacific during the CONvective TRansport of Active Species in the Tropics (CONTRAST) and the Airborne Tropical TRopopause EXperiment (ATTREX) campaigns. The overall contribution of VSLS to stratospheric bromine was determined to be 5.0 ± 2.1 ppt, in agreement with the 5 ± 3 ppt estimate provided in the 2014 World Meteorological Organization (WMO) Ozone Assessment report (WMO 2014), but with lower uncertainty. Measurements of organic bromine compounds, including VSLS, were analyzed using CFC-11 as a reference stratospheric tracer. From this analysis, 2.9 ± 0.6 ppt of bromine enters the stratosphere via organic source gas injection of VSLS. This value is two times the mean bromine content of VSLS measured at the tropical tropopause, for regions outside of the Tropical Western Pacific, summarized in WMO 2014. A photochemical box model, constrained to CONTRAST observations, was used to estimate inorganic bromine from measurements of BrO collected by two instruments. The analysis indicates that 2.1 ± 2.1 ppt of bromine enters the stratosphere via inorganic product gas injection. We also examine the representation of brominated VSLS within 14 global models that participated in the Chemistry-Climate Model Initiative. The representation of stratospheric bromine in these models generally lies within the range of our empirical estimate. Models that include explicit representations of VSLS compare better with bromine observations in the lower stratosphere than models that utilize longer-lived chemicals as a surrogate for VSLS., The CONTRAST field deployment was supported by the U.S. NSF, and the ATTREX field deployment was supported by the National Aeronautics and Space Administration (NASA). P. A. W., R. J. S., T. P. C., J. M. N., and D. C. A. received support from NSF, NASA Atmospheric Composition Modeling and Analysis Program (ACMAP), and the NASA Modeling, Analysis, and Prediction (MAP). D. C. A. also received support from the NASA Upper Atmospheric Research Program. J. M. N. was also supported by the NASA Postdoctoral Program at the NASA Goddard Space Flight Center, administered by Universities Space Research Association under contract with NASA. R. V. acknowledges funding from NSF awards AGS‐1261740 and AGS‐1620530. CONTRAST data are publicly available at “http://data.eol.ucar.edu/master_list/?project= CONTRAST.” ATTREX data are publicly available at “https://espoarchive.nasa.gov/archive/browse/attrex/id4/GHawk.” The National Center for Environmental Prediction (NCEP) meteorological data are available at “https://doi.org/10.5065/D6M043C6.” CCMI outputs from CESM1‐WACCM and CESM1‐CAM4Chem are archived by the National Center for Atmospheric Research (NCAR) at “www.earthsystemgrid.org,” and NCAR is sponsored by NSF. CCMI output from the EMAC‐L90MA‐SD simulation is available at “https://doi.org/10.5281/zenodo.1204495.” All other CCMI simulations are archived by the British Atmospheric Data Centre at “http://badc.nerc.ac.uk/”. Output from CAM‐chem‐SD is available as “NCAR/ACD CAMChem 1 Degree Forecast” at “http://catalog.eol.ucar.edu/contrast/model/CAMChem_NCAR_1deg/.” WACCM and CAM‐Chem are components of the Community Earth System Model (CESM), which is also supported by NSF. Computing resources were provided by NCAR's Climate Simulation Laboratory, sponsored by NSF and other agencies. This research was enabled by the computational and storage resources of NCAR's Computational and Information System Laboratory (CISL). R. S. and K. A. S., with ACCESS‐CCM, acknowledge support from Australian Research Council's Centre of Excellence for Climate System Science (CE110001028), the Australian Government's National Computational Merit Allocation Scheme (q90), and Australian Antarctic science grant program (FoRCES 4012). CCSRNIES research was supported by the Environment Research and Technology Development Fund (2‐1303 and 2‐1709) of the Ministry of the Environment, Japan, and computations were performed on NEC‐SX9/A(ECO) computers at the CGER, NIES. The EMAC simulations have been performed at the German Climate Computing Centre (DKRZ) through support from the Bundesministerium für Bildung und Forschung (BMBF). DKRZ and its scientific steering committee are gratefully acknowledged for providing the HPC and data archiving resources for the consortial project ESCiMo (Earth System Chemistry integrated Modelling). The TOMCAT modeling was supported by NERC NCAS and the SISLAC project (NE/R001782/1), and the simulations were performed on the Archer and Leeds HPC Systems.

Formaldehyde (HCHO) directly affects the atmospheric oxidative capacity through its effects on HOx. In remote marine environments, such as the Tropical Western Pacific (TWP), it is particularly important to understand the processes controlling the abundance of HCHO because model output from these regions is used to correct satellite retrievals of HCHO. Here, we have used observations from the CONTRAST field campaign, conducted during January and February 2014, to evaluate our understanding of the processes controlling the distribution of HCHO in the TWP as well as its representation in chemical transport/climate models. Observed HCHO mixing ratios varied from ~500 pptv near the surface to ~75 pptv in the upper troposphere. Recent convective transport of near surface HCHO and its precursors, acetaldehyde and possibly methyl hydroperoxide, increased upper tropospheric HCHO mixing ratios by ~33% (22 pptv); this air contained roughly 60% less NO than more aged air. Output from the CAM-Chem chemistry transport model (2014 meteorology) as well as nine chemistry climate models from the Chemistry-Climate Model Initiative (free-running meteorology) are found to uniformly underestimate HCHO columns derived from in situ observations by between 4 and 50%. This underestimate of HCHO likely results from a near factor of two underestimate of NO in most models, which strongly suggests errors in NOx emissions inventories and/or in the model chemical mechanisms. Likewise, the lack of oceanic acetaldehyde emissions and potential errors in the model acetaldehyde chemistry lead to additional underestimates in modeled HCHO of up to 75 pptv (~15%) in the lower troposphere.

Climate models consistently predict an acceleration of the Brewer-Dobson circulation (BDC) due to climate change in the 21st century. However, the strength of this acceleration varies considerably among individual models, which constitutes a notable source of uncertainty for future climate projections. To shed more light upon the magnitude of this uncertainty and on its causes, we analyze the stratospheric mean age of air (AoA) of 10 climate projection simulations from the Chemistry Climate Model Initiative phase 1 (CCMI-I), covering the period between 1960 and 2100. In agreement with previous multi-model studies, we find a large model spread in the magnitude of the AoA trend over the simulation period. Differences between future and past AoA are found to be predominantly due to differences in mixing (reduced aging by mixing and recirculation) rather than differences in residual mean transport. We furthermore analyze the mixing efficiency, a measure of the relative strength of mixing for given residual mean transport, which was previously hypothesized to be a model constant. Here, the mixing efficiency is found to vary not only across models, but also over time in all models. Changes in mixing efficiency are shown to be closely related to changes in AoA and quantified to roughly contribute 10 % to the long-term AoA decrease over the 21st century. Additionally, mixing efficiency variations are shown to considerably enhance model spread in AoA changes. To understand these mixing efficiency variations, we also present a consistent dynamical framework based on diffusive closure, which highlights the role of basic state potential vorticity gradients in controlling mixing efficiency and therefore aging by mixing.

Simulated stratospheric temperatures over the period 1979–2016 in models from the Chemistry-Climate Model Initiative are compared with recently updated and extended satellite data sets. The multimodel mean global temperature trends over 1979–2005 are -0.88 ± 0.23, -0.70 ± 0.16, and -0.50 ± 0.12 K/decade for the Stratospheric Sounding Unit (SSU) channels 3 (~40–50 km), 2 (~35–45 km), and 1 (~25–35 km), respectively (with 95% confidence intervals). These are within the uncertainty bounds of the observed temperature trends from two reprocessed SSU data sets. In the lower stratosphere, the multimodel mean trend in global temperature for the Microwave Sounding Unit channel 4 (~13–22 km) is -0.25 ± 0.12 K/decade over 1979–2005, consistent with observed estimates from three versions of this satellite record. The models and an extended satellite data set comprised of SSU with the Advanced Microwave Sounding Unit-A show weaker global stratospheric cooling over 1998–2016 compared to the period of intensive ozone depletion (1979–1997). This is due to the reduction in ozone-induced cooling from the slowdown of ozone trends and the onset of ozone recovery since the late 1990s. In summary, the results show much better consistency between simulated and satellite-observed stratospheric temperature trends than was reported by Thompson et al. (2012, https://doi.org/10.1038/nature11579) for the previous versions of the SSU record and chemistry-climate models. The improved agreement mainly comes from updates to the satellite records; the range of stratospheric temperature trends over 1979–2005 simulated in Chemistry-Climate Model Initiative models is comparable to the previous generation of chemistry-climate models.

The impact of changes in incoming solar irradiance on stratospheric ozone abundances should be included in climate simulations to aid in capturing the atmospheric response to solar cycle variability. This study presents the first systematic comparison of the representation of the 11-year solar cycle ozone response (SOR) in chemistry–climate models (CCMs) and in pre-calculated ozone databases specified in climate models that do not include chemistry, with a special focus on comparing the recommended protocols for the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5 and CMIP6). We analyse the SOR in eight CCMs from the Chemistry–Climate Model Initiative (CCMI-1) and compare these with results from three ozone databases for climate models: the Bodeker Scientific ozone database, the SPARC/Atmospheric Chemistry and Climate (AC&C) ozone database for CMIP5 and the SPARC/CCMI ozone database for CMIP6. The peak amplitude of the annual mean SOR in the tropical upper stratosphere (1–5hPa) decreases by more than a factor of 2, from around 5 to 2%, between the CMIP5 and CMIP6 ozone databases. This substantial decrease can be traced to the CMIP5 ozone database being constructed from a regression model fit to satellite and ozonesonde measurements, while the CMIP6 database is constructed from CCM simulations. The SOR in the CMIP6 ozone database therefore implicitly resembles the SOR in the CCMI-1 models. The structure in latitude of the SOR in the CMIP6 ozone database and CCMI-1 models is considerably smoother than in the CMIP5 database, which shows unrealistic sharp gradients in the SOR across the middle latitudes owing to the paucity of long-term ozone measurements in polar regions. The SORs in the CMIP6 ozone database and the CCMI-1 models show a seasonal dependence with enhanced meridional gradients at mid- to high latitudes in the winter hemisphere. The CMIP5 ozone database does not account for seasonal variations in the SOR, which is unrealistic. Sensitivity experiments with a global atmospheric model without chemistry (ECHAM6.3) are performed to assess the atmospheric impacts of changes in the representation of the SOR and solar spectral irradiance (SSI) forcing between CMIP5 and CMIP6. The larger amplitude of the SOR in the CMIP5 ozone database compared to CMIP6 causes a likely overestimation of the modelled tropical stratospheric temperature response between 11-year solar cycle minimum and maximum by up to 0.55K, or around 80% of the total amplitude. This effect is substantially larger than the change in temperature response due to differences in SSI forcing between CMIP5 and CMIP6. The results emphasize the importance of adequately representing the SOR in global models to capture the impact of the 11-year solar cycle on the atmosphere. Since a number of limitations in the representation of the SOR in the CMIP5 ozone database have been identified, we recommend that CMIP6 models without chemistry use the CMIP6 ozone database and the CMIP6 SSI dataset to better capture the climate impacts of solar variability. The SOR coefficients from the CMIP6 ozone database are published with this paper.

Previous multi-model intercomparisons have shown that chemistry-climate models exhibit significant biases in tropospheric ozone compared with observations. We investigate annual-mean tropospheric column ozone in 15 models participating in the SPARC/IGAC (Stratosphere-troposphere Processes and their Role in Climate/International Global Atmospheric Chemistry) Chemistry-Climate Model Initiative (CCMI). These models exhibit a positive bias, on average, of up to 40–50 % in the Northern Hemisphere compared with observations derived from the Ozone Monitoring Instrument and Microwave Limb Sounder (OMI/MLS), and a negative bias of up to ~ 30 % in the Southern Hemisphere. SOCOLv3.0 (version 3 of the Solar-Climate Ozone Links CCM), which participated in CCMI, simulates global-mean tropospheric ozone columns of 40.2 DU – approximately 33 % larger than the CCMI multi-model mean. Here we introduce an updated version of SOCOLv3.0, SOCOLv3.1, which includes an improved treatment of ozone sink processes, and results in a reduction in the tropospheric column ozone bias of up to 8 DU, mostly due to the inclusion of N2O5 hydrolysis on tropospheric aerosols. As a result of these developments, tropospheric column ozone amounts simulated by SOCOLv3.1 are comparable with several other CCMI models. We apply Gaussian process emulation and sensitivity analysis to understand the remaining ozone bias in SOCOLv3.1. This shows that ozone precursors (nitrogen oxides (NOx, carbon monoxide, methane and other volatile organic compounds) are responsible for more than 90 % of the variance in tropospheric ozone. However, it may not be the emissions inventories themselves that result in the bias, but how the emissions are handled in SOCOLv3.1, and we discuss this in the wider context of the other CCMI models. Given that the emissions data set to be used for phase 6 of the Coupled Model Intercomparison Project includes approximately 20 % more NOx than the data set used for CCMI, further work is urgently needed to address the challenges of simulating sub-grid processes of importance to tropospheric ozone in the current generation of chemistry-climate models.

The Montreal Protocol has succeeded in limiting major ozone-depleting substance emissions, and consequently stratospheric ozone concentrations are expected to recover this century. However, there is a large uncertainty in the rate of regional ozone recovery in the Northern Hemisphere. Here we identify a Eurasia-North America dipole mode in the total column ozone over the Northern Hemisphere, showing negative and positive total column ozone anomaly centres over Eurasia and North America, respectively. The positive trend of this mode explains an enhanced total column ozone decline over the Eurasian continent in the past three decades, which is closely related to the polar vortex shift towards Eurasia. Multiple chemistry-climate-model simulations indicate that the positive Eurasia-North America dipole trend in late winter is likely to continue in the near future. Our findings suggest that the anticipated ozone recovery in late winter will be sensitive not only to the ozone-depleting substance decline but also to the polar vortex changes, and could be substantially delayed in some regions of the Northern Hemisphere extratropics., Climate change can exert a significant effect on the ozone recovery. Here, the authors show that the Arctic polar vortex shift associated with Arctic sea-ice loss could slow down ozone recovery over the Eurasian continent.

We evaluate how the coupled aerosol-chemistry-climate model SOCOL-AER represents the influence of the 1991 eruption of Mt. Pinatubo on stratospheric aerosol loading, aerosol microphysical processes, radiative effects, and atmospheric chemistry. The aerosol module includes comprehensive sulfur chemistry and microphysics, in which the particle size distribution is represented by 40 size bins spanning radii from 0.39 nm to 3.2 μm. Radiative forcing is computed online using aerosol optical properties calculated according to Mie theory. SOCOL-AER simulations are compared with satellite and in situ measurements of aerosol parameters, temperature reanalyses, and ozone observations. In addition to the reference model configuration, we performed a series of sensitivity experiments looking at different processes affecting the aerosol layer. An accurate sedimentation scheme is found to be essential to prevent particles diffusing too rapidly to high and low altitudes. The aerosol radiative feedback and the use of a nudged quasi-biennial oscillation help to keep aerosol in the tropics and significantly affect the evolution of the stratospheric aerosol burden, which improves the agreement with observed aerosol mass distributions. Changes in the aerosol distribution affected by an inclusion of Van der Waals forces to the particle coagulation scheme suggest improvements in particle effective radius, although other parameters (such as aerosol longevity) deteriorate. Modification of the Pinatubo emission rate also improves some aerosol parameters, while worsens others compared to observations. Observations themselves are highly uncertain and render it difficult to conclusively judge the necessity of further model reconfiguration. In conclusion, our results show that SOCOL-AER is capable of predicting the most important global-scale atmospheric and climate effects following volcanic eruptions, which is also a prerequisite for improved understanding of anthropogenic effects from sulfur emissions.

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

Because tropospheric ozone is both a greenhouse gas and harmful air pollutant, it is important to understand how anthropogenic activities may influence its abundance and distribution through the 21st century. Here, we present model simulations performed with the chemistry–climate model SOCOL, in which spatially disaggregated chemistry and transport tracers have been implemented in order to better understand the distribution and projected changes in tropospheric ozone. We examine the influences of ozone precursor emissions (nitrogen oxides (NOx), carbon monoxide (CO) and volatile organic compounds (VOCs)), climate change (including methane effects) and stratospheric ozone recovery on the tropospheric ozone budget, in a simulation following the climate scenario Representative Concentration Pathway (RCP) 6.0 (a medium-high, and reasonably realistic climate scenario). Changes in ozone precursor emissions have the largest effect, leading to a global-mean increase in tropospheric ozone which maximizes in the early 21st century at 23% compared to 1960. The increase is most pronounced at northern midlatitudes, due to regional emission patterns: between 1990 and 2060, northern midlatitude tropospheric ozone remains at constantly large abundances: 31% larger than in 1960. Over this 70-year period, attempts to reduce emissions in Europe and North America do not have an effect on zonally averaged northern midlatitude ozone because of increasing emissions from Asia, together with the long lifetime of ozone in the troposphere. A simulation with fixed anthropogenic ozone precursor emissions of NOx, CO and non-methane VOCs at 1960 conditions shows a 6% increase in global-mean tropospheric ozone by the end of the 21st century, with an 11 % increase at northern midlatitudes. This increase maximizes in the 2080s and is mostly caused by methane, which maximizes in the 2080s following RCP 6.0, and plays an important role in controlling ozone directly, and indirectly through its influence on other VOCs and CO. Enhanced flux of ozone from the stratosphere to the troposphere as well as climate change-induced enhancements in lightning NOx emissions also increase the tropospheric ozone burden, although their impacts are relatively small. Overall, the results show that under this climate scenario, ozone in the future is governed largely by changes in methane and NOx; methane induces an increase in tropospheric ozone that is approximately one-third of that caused by NOx. Climate impacts on ozone through changes in tropospheric temperature, humidity and lightning NOx remain secondary compared with emission strategies relating to anthropogenic emissions of NOx, such as fossil fuel burning. Therefore, emission policies globally have a critical role to play in determining tropospheric ozone evolution through the 21st century.

The double-peaked response of the tropical stratospheric temperature profile to the 11-year solar cycle (SC) has been well documented. However, there are concerns about the origin of the lower peak due to potential aliasing with volcanic eruptions or the El Nino Southern Oscillation (ENSO) detected using multiple linear regression (MLR) analysis. We confirm the aliasing using the results of the chemistry-climate model (CCM) SOCOLv3 obtained in the framework of the IGAC/SPAR Chemistry-Climate Model Initiative phase 1 (CCMI-1). We further show that, even without major volcanic eruptions included in transient simulations, the lower stratospheric response exhibits a residual peak when historical sea surface temperatures (SST)/sea ice coverage (SIC) are used. Only the use of climatological SSTs/SICs in addition to background stratospheric aerosols removes volcanic and ENSO signals and results in an almost complete disappearance of the modeled solar signal in the lower stratospheric temperature. We demonstrate that the choice of temporal sub-period considered for the regression analysis has a large impact on the estimated profile signal in the lower stratosphere: at least 45 consecutive years are needed to avoid the large aliasing effect of SC maxima with volcanic eruptions in 1982 and 1991 in historical simulations, reanalyses and observations. The application of volcanic forcing compiled for phase 6 of the Coupled Model Intercomparison Project (CMIP6) in the CCM SOCOLv3 reduces the warming overestimation in the tropical lower stratosphere and the volcanic aliasing of the temperature response to the SC, although it does not eliminate it completely.

To simulate the impacts of volcanic eruptions on the stratosphere, chemistry-climate models that do not include an online aerosol module require temporally and spatially resolved aerosol size parameters for heterogeneous chemistry and aerosol radiative properties as a function of wavelength. For phase 1 of the Chemistry-Climate Model Initiative (CCMI-1) and, later, for phase 6 of the Coupled Model Intercomparison Project (CMIP6) two such stratospheric aerosol data sets were compiled, whose functional capability and representativeness are compared here. For CCMI-1, the SAGE-4λ data set was compiled, which hinges on the measurements at four wavelengths of the SAGE (Stratospheric Aerosol and Gas Experiment) II satellite instrument and uses ground-based Lidar measurements for gap-filling immediately after the Mt. Pinatubo eruption, when the stratosphere was optically opaque for SAGE II. For CMIP6, the new SAGE-3λ data set was compiled, which excludes the least reliable SAGE II wavelength and uses CLAES (Cryogenic Limb Array Etalon Spectrometer) measurements on UARS, the Upper Atmosphere Research Satellite, for gap-filling following the Mt. Pinatubo eruption instead of ground-based Lidars. Here, we performed SOCOLv3 (Solar Climate Ozone Links version 3) chemistry-climate model simulations of the recent past (1986–2005) to investigate the impact of the Mt. Pinatubo eruption in 1991 on stratospheric temperature and ozone and how this response differs depending on which aerosol data set is applied. The use of SAGE-4λ results in heating and ozone loss being overestimated in the lower stratosphere compared to observations in the post-eruption period by approximately 3 K and 0.2 ppmv, respectively. However, less heating occurs in the model simulations based on SAGE-3λ, because the improved gap-filling procedures after the eruption lead to less aerosol loading in the tropical lower stratosphere. As a result, simulated temperature anomalies in the model simulations based on SAGE-3λ for CMIP6 are in excellent agreement with MERRA and ERA-Interim reanalyses in the post-eruption period. Less heating in the simulations with SAGE-3λ means that the rate of tropical upwelling does not strengthen as much as it does in the simulations with SAGE-4λ, which limits dynamical uplift of ozone and therefore provides more time for ozone to accumulate in tropical mid-stratospheric air. Ozone loss following the Mt. Pinatubo eruption is overestimated by 0.1 ppmv in the model simulations based on SAGE-3λ, which is a better agreement with observations than in the simulations based on SAGE-4λ. Overall, the CMIP6 stratospheric aerosol data set, SAGE-3λ, allows SOCOLv3 to more accurately simulate the post-Pinatubo eruption period.

Ozone fields simulated for the Chemistry-Climate Model Initiative (CCMI) will be used as forcing data in the 6th Coupled Model Intercomparison Project (CMIP6). Here we assess, using reference and sensitivity simulations produced for phase 1 of CCMI, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances (ODSs), and a combination of carbon dioxide and other greenhouse gases (GHGs). We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. The likely cause of this is lower-stratospheric transport and dynamical responses exhibiting substantial inter-model differences. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings.

We present an overview of state-of-the-art chemistry–climate and chemistry transport models that are used within phase 1 of the Chemistry–Climate Model Initiative (CCMI-1). The CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models' projections of the stratospheric ozone layer, tropospheric composition, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to which CCMI-1 recommendations for simulations have been followed is necessary to understand model responses to anthropogenic and natural forcing and also to explain inter-model differences. This becomes even more important given the ongoing development and the ever-growing complexity of these models. This paper also provides an overview of the available CCMI-1 simulations with the aim of informing CCMI data users.

It is well understood by most chemistry students at advanced undergraduate levels that chemical reactions generally follow the Arrhenius law of temperature dependence with positive activation energies, proceeding faster at elevated temperatures. It is much less widely known that the rates of some Arrhenius-compliant reactions are retarded by increasing the temperature and are therefore associated with negative activation energies. The few readily accessible explanations of this phenomenon are rather cursory and limited to enthalpic considerations relating to the relative activation energies and thermicities of the component elementary steps of the process. However, these explanations are incomplete and consequently counterintuitive. Here we provide the required augmentation via entropic considerations.

Through the 21st century, anthropogenic emissions of the greenhouse gases N2O and CH4 are projected to increase, thus increasing their atmospheric concentrations. Consequently, reactive nitrogen species produced from N2O and reactive hydrogen species produced from CH4 are expected to play an increasingly important role in determining stratospheric ozone concentrations. Eight chemistry-climate model simulations were performed to assess the sensitivity of stratospheric ozone to different emissions scenarios for N2O and CH4. Global-mean total column ozone increases through the 21st century in all eight simulations as a result of CO2-induced stratospheric cooling and decreasing stratospheric halogen concentrations. Larger N2O concentrations were associated with smaller ozone increases, due to reactive nitrogen-mediated ozone destruction. In the simulation with the largest N2O increase, global-mean total column ozone increased by 4.3 DU through the 21st century, compared with 10.0 DU in the simulation with the smallest N2O increase. In contrast, larger CH4 concentrations were associated with larger ozone increases; global-mean total column ozone increased by 16.7 DU through the 21st century in the simulation with the largest CH4 concentrations and by 4.4 DU in the simulation with the lowest CH4 concentrations. CH4 leads to ozone loss in the upper and lower stratosphere by increasing the rate of reactive hydrogen-mediated ozone loss cycles, however in the lower stratosphere and troposphere, CH4 leads to ozone increases due to photochemical smog-type chemistry. In addition to this mechanism, total column ozone increases due to H2O-induced cooling of the stratosphere, and slowing of the chlorine-catalyzed ozone loss cycles due to an increased rate of the CH4 + Cl reaction. Stratospheric column ozone through the 21st century exhibits a near-linear response to changes in N2O and CH4 surface concentrations, which provides a simple parameterization for the ozone response to changes in these gases.

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.

We find that wintertime temperature anomalies near 4 hPa and 50° N/S are related, through dynamics, to anomalies in ozone and temperature, particularly in the tropical stratosphere, but also throughout the upper stratosphere and mesosphere. These mid-latitude anomalies occur on timescales of up to a month, and are related to changes in wave-forcing. A change in the meridional circulation extends from the middle stratosphere into the mesosphere and forms a temperature-change quadrupole from equator to pole. We develop a dynamical index based on detrended, deseasonalised mid-latitude temperature. When employed in multiple linear regression, this index can account for up to 40 % of the total variability of temperature and ozone and a doubling of the total coefficient of determination in the equatorial stratosphere above 20 hPa. Further, the uncertainty on all multiple-linear regression coefficients can be reduced by up to 45 % and 25 % in temperature and ozone, respectively, and so this index is an important tool for quantifying current and future ozone recovery.