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One of the key questions in the air quality and climate sciences is how tropospheric ozone concentrations will change in the future. This will depend on two factors: changes in stratosphere-to-troposphere transport (STT) and changes in tropospheric chemistry. Here we aim to identify robust changes in STT using simulations from the Chemistry Climate Model Initiative (CCMI) under a common climate change scenario (RCP6.0). We use two idealized stratospheric tracers to isolate changes in transport: stratospheric ozone (O3S), which is exactly like ozone but has no chemical sources in the troposphere, and st80, a passive tracer with fixed volume mixing ratio in the stratosphere. We find a robust increase in the tropospheric columns of these two tracers across the models. In particular, stratospheric ozone in the troposphere is projected to increase 10 %–16 % by the end of the 21st century in the RCP6.0 scenario. Future STT is enhanced in the subtropics due to the strengthening of the shallow branch of the Brewer–Dobson circulation (BDC) in the lower stratosphere and of the upper part of the Hadley cell in the upper troposphere. The acceleration of the deep branch of the BDC in the Northern Hemisphere (NH) and changes in eddy transport contribute to increased STT at high latitudes. These STT trends are caused by greenhouse gas (GHG) increases, while phasing out of ozone-depleting substances (ODS) does not lead to robust transport changes. Nevertheless, the decline of ODS increases the reservoir of ozone in the lower stratosphere, which results in enhanced STT of O3S at middle and high latitudes. A higher emission scenario (RCP8.5) produces stronger STT trends, with increases in tropospheric column O3S more than 3 times larger than those in the RCP6.0 scenario by the end of the 21st century.

Chemistry–climate models are important tools for addressing interactions of composition and climate in the Earth system. In particular, they are used to assess the combined roles of greenhouse gases and ozone in Southern Hemisphere climate and weather. Here we present an evaluation of the Australian Community Climate and Earth System Simulator – chemistry–climate model (ACCESS-CCM), focusing on the Southern Hemisphere and the Australian region. This model is used for the Australian contribution to the international Chemistry–Climate Model Initiative, which is soliciting hindcast, future projection and sensitivity simulations. The model simulates global total column ozone (TCO) distributions accurately, with a slight delay in the onset and recovery of springtime Antarctic ozone depletion, and consistently higher ozone values. However, October-averaged Antarctic TCO from 1960 to 2010 shows a similar amount of depletion compared to observations. Comparison with model precursors shows large improvements in the representation of the Southern Hemisphere stratosphere, especially in TCO concentrations. A significant innovation is seen in the evaluation of simulated vertical profiles of ozone and temperature with ozonesonde data from Australia, New Zealand and Antarctica from 38 to 90° S. Excess ozone concentrations (greater than 26 % at Davis and the South Pole during winter) and stratospheric cold biases (up to 10 K at the South Pole during summer and autumn) outside the period of perturbed springtime ozone depletion are seen during all seasons compared to ozonesondes. A disparity in the vertical location of ozone depletion is seen: centred around 100 hPa in ozonesonde data compared to above 50 hPa in the model. Analysis of vertical chlorine monoxide profiles indicates that colder Antarctic stratospheric temperatures (possibly due to reduced mid-latitude heat flux) are artificially enhancing polar stratospheric cloud formation at high altitudes. The model's inability to explicitly simulate a supercooled ternary solution may also explain the lack of depletion at lower altitudes. Analysis of the simulated Southern Annular Mode (SAM) index compares well with ERA-Interim data, an important metric for correct representation of Australian climate. Accompanying these modulations of the SAM, 50 hPa zonal wind differences between 2001–2010 and 1979–1998 show increasing zonal wind strength southward of 60° S during December for both the model simulations and ERA-Interim data. These model diagnostics show that the model reasonably captures the stratospheric ozone-driven chemistry–climate interactions important for Australian climate and weather while highlighting areas for future model development.

The Antarctic ozone ‘hole’ was discovered in 1985 (ref.  1 ) and man-made ozone-depleting substances (ODSs) are its primary cause 2 . Following reductions of ODSs under the Montreal Protocol 3 , signs of ozone recovery have been reported, based largely on observations and broad yet compelling model–data comparisons 4 . Although such approaches are highly valuable, they do not provide rigorous statistical detection of the temporal and spatial structure of Antarctic ozone recovery in the presence of internal climate variability. Here we apply pattern-based detection and attribution methods as used in climate-change studies 5 , 6 , 7 , 8 , 9 , 10 – 11 to separate anthropogenically forced ozone responses from internal variability, relying on trend pattern information as a function of month and height. The analysis uses satellite observations together with single-model and multi-model ensemble simulations to identify and quantify the month–height Antarctic ozone recovery ‘fingerprint’ 12 . We demonstrate that the data and simulations show compelling agreement in the fingerprint pattern of the ozone response to decreasing ODSs since 2005. We also show that ODS forcing has enhanced ozone internal variability during the austral spring, influencing detection of forced responses and their time of emergence. Our results provide robust statistical and physical evidence that actions taken under the Montreal Protocol to reduce ODSs are indeed resulting in the beginning of Antarctic ozone recovery, defined as increases in ozone consistent with expected month–height patterns. Pattern-based detection and attribution methods that make use of trend pattern information as a function of month and height provide evidence that reduction of ozone-depleting substances has resulted in the beginning of Antarctic ozone recovery.

As the leading mode of Pacific variability, El Ni˜no–Southern Oscillation (ENSO) causes vast and wide-spread climatic impacts, including in the stratosphere. Following discovery of a stratospheric pathway of ENSO to the Northern Hemisphere surface, here we aim to investigate if there is a substantial Southern Hemisphere (SH) stratospheric pathway in relation to austral winter ENSO events. Large stratospheric anomalies connected to ENSO occur on average at high SH latitudes as early as August, peaking at around 10 hPa. An overall colder austral spring Antarctic stratosphere is generally associated with the warm phase of the ENSO cycle, and vice versa. This behavior is robust among reanalysis and six separate model ensembles encompassing two different model frameworks. A stratospheric pathway is identified by separating ENSO events that exhibit a stratospheric anomaly from those that do not and comparing to stratospheric extremes that occur during neutral ENSO years. The tropospheric eddy-driven jet response to the stratospheric ENSO pathway is the most robust in the spring following a La Ni˜na, but extends into summer, and is more zonally symmetric compared to the tropospheric ENSO teleconnection. The magnitude of the stratospheric pathway is weaker compared to the tropospheric pathway and therefore, when it is present, has a secondary role. For context, the magnitude is approximately half that of the eddy-driven jet modulation due to austral spring ozone depletion in the model simulations. This work establishes that the stratospheric circulation acts as an intermediary in coupling ENSO variability to variations in the austral spring and summer tropospheric circulation.

Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, 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, and a combination of carbon dioxide and other greenhouse gases. 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. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

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.

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI). Specifically, we find up to 40% differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

Measurements by the Dobson ozone spectrophotometer at the British Antarctic Survey's (BAS) Halley research station form a record of Antarctic total column ozone that dates back to 1956. Due to its location, length, and completeness, the record has been, and continues to be, uniquely important for studies of long-term changes in Antarctic ozone. However, a crack in the ice shelf on which it resides forced the station to abruptly close in February of 2017, leading to a gap of two ozone hole seasons in its historic record. We develop and test a method for filling in the record of Halley total ozone by combining and adjusting overpass data from a range of different satellite instruments. Comparisons to the Dobson suggest that our method reproduces monthly ground-based total ozone values with an average difference of 1.1 ± 6.2 DU for the satellites used to fill in the 2017–2018 gap. We show that our approach more closely reproduces the Dobson measurements than simply using the raw satellite average or data from a single satellite instrument. The method also provides a check on the consistency of the provisional data from the automated Dobson used at Halley after 2018 with earlier manual Dobson data and suggests that there were likely inconsistencies between the two. The filled Halley dataset provides further support that the Antarctic ozone hole is healing, not only during September but also in January.

Transport from the Northern Hemisphere (NH) midlatitudes to the Arctic plays a crucial role in determining the abundance of trace gases and aerosols that are important to Arctic climate via impacts on radiation and chemistry. Here we examine this transport using an idealized tracer with a fixed lifetime and predominantly midlatitude land-based sources in models participating in the Chemistry Climate Model Initiative (CCMI). We show that there is a 25%-45% difference in the Arctic concentrations of this tracer among the models. This spread is correlated with the spread in the location of the Pacific jet, as well as the spread in the location of the Hadley Cell (HC) edge, which varies consistently with jet latitude. Our results suggest that it is likely that the HC-related zonal-mean meridional transport rather than the jet-related eddy mixing is the major contributor to the inter-model spread in the transport of land-based tracers into the Arctic. Specifically, in models with a more northern jet, the HC generally extends further north and the tracer source region is mostly covered by surface southward flow associated with the lower branch of the HC, resulting in less efficient transport poleward to the Arctic. During boreal summer, there are poleward biases in jet location in free-running models, and these models likely underestimate the rate of transport into the Arctic. Models using specified dynamics do not have biases in the jet location, but do have biases in the surface meridional flow, which may result in differences in transport into the Arctic. In addition to the land-based tracer, the midlatitude-to-Arctic transport is further examined by another idealized tracer with zonally uniform sources. With equal sources from both land and ocean, the inter-model spread of this zonally uniform tracer is more related to variations in parameterized convection over oceans rather than variations in HC extent, particularly during boreal winter. This suggests that transport of land-based and oceanic tracers or aerosols towards the Arctic differs in pathways and therefore their corresponding inter-model variabilities result from different physical processes.

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.