The Influence of Mixing on Stratospheric Age of Air Changes in the 21st Century

Climate models consistently predict an acceleration of the BrewerDobson 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 analyse 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 analyse the mixing efficiency, a measure of the relative strength of mixing for given residual mean transport, which was previously hypothesised 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

Analysis of recent lower-stratospheric ozone trends in chemistry climate models

Recent observations show a significant decrease in lower-stratospheric (LS) ozone concentrations in tropical and mid-latitude regions since 1998. By analysing 31 chemistry climate model (CCM) simulations performed for the Chemistry Climate Model Initiative (CCMI; Morgenstern et al., 2017), we find a large spread in the 1998 2018 trend patterns between different CCMs and between different realizations performed with the same CCM. The latter in particular indicates that natural variability strongly influences LS ozone trends. However none of the model simulations reproduce the observed ozone trend structure of coherent negative trends in the LS. In contrast to the observations, most models show an LS trend pattern with negative trends in the tropics (20 S 20 N) and positive trends in the northern mid-latitudes (30 50 N) or vice versa. To investigate the influence of natural variability on recent LS ozone trends, we analyse the sensitivity of observational trends and the models trend probability distributions for varying periods with start dates from 1995 to 2001 and end dates from 2013 to 2019. Generally, modelled and observed LS trends remain robust for these different periods; however observational data show a change towards weaker mid-latitude trends for certain periods, likely forced by natural variability. Moreover we show that in the tropics the observed trends agree well with the models trend distribution, whereas in the mid-latitudes the observational trend is typically an extreme value of the models distribution. We further investigate the LS ozone trends for extended periods reaching into the future and find that all models develop a positive ozone trend at mid-latitudes, and the trends converge to constant values by the period that spans 1998 2060. Inter-model correlations between ozone trends and transport-circulation trends confirm the dominant role of greenhouse gas (GHG)-driven tropical upwelling enhancement on the tropical LS ozone decrease. Mid-latitude ozone, on the other hand, appears to be influenced by multiple competing factors: an enhancement in the shallow branch decreases ozone, while an enhancement in the deep branch increases ozone, and, furthermore, mixing plays a role here too. Sensitivity simulations with fixed forcing of GHGs or ozonedepleting substances (ODSs) reveal that the GHG-driven increase in circulation strength does not lead to a net trend in LS mid-latitude column ozone. Rather, the positive ozone trends simulated consistently in the models in this region emerge from the decline in ODSs, i.e. the ozone recovery. Therefore, we hypothesize that next to the influence of natural variability, the disagreement of modelled and observed LS mid-latitude ozone trends could indicate a mismatch in the relative role of the response of ozone to ODS versus GHG forcing in the models.Atmospheric Remote Sensin