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

Abstract

Abstract. 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 ozone-depleting 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.

The historical ozone trends simulated with the SOCOLv4 and their comparison with observations and reanalysis

“…Recently, the ozone simulated by 31 CCMs participating in the Chemistry-Climate Model Initiative Phase-1 (CCMI-1) has been analyzed, and it was shown that the pattern of the signal in LSO varies greatly even between different realizations of the experiment performed with the same CCM (Dietmüller et al, 2021). The question is why models cannot reproduce the persistent and statistically robust declining trends in near-global LSO.…”

“…These results suggest that to study long-term ozone trends in dynamically controlled regions, it is desirable to analyze different ensemble members of the experiment separately because ensemble-averaging suppresses the variability. In contrast, Dietmüller et al (2021) suspect that the models have difficulties reproducing the observed LSO trend because of extreme natural variability at the beginning or end of the observed period , or because natural variability in QBO and BDC is not adequately simulated. Thus, small inadequacies in atmospheric dynamics might be the reason why models do not demonstrate robust LSO negative tendencies, amplified by the strong internal ozone variability (Shangguan et al, 2019).…”

On the impact of Himalaya-induced gravity waves on the polar vortex, Rossby wave activity and ozone

“…Our results also prove the potential of GWs to alter the ozone variability and its trends via mixing in the surf zone or advection from lower latitudes. The evidence for a link between polar vortex dynamics and the parameterized OGWD via PWs stipulates further research of the uncertainty in polar vortex projections (Manzini et al, 2014;Ayarzagüena et al, 2020) or ozone variability (Dietmüller et al, 2021). Given all the assumptions and tuning employed in the OGW parameterization scheme, this indication of surprisingly wide ranging effects of parameterized OGWD in the model prompts validation in GW resolving datasets and makes an additional case for improving of the parameterizations in CCMs.…”

“…In future work a standalone metric could be developed with even lower false alarm rate. Dietmüller et al (2021) discussed in detail the model spread in ozone variability and trends in the lower stratospheric mid latitudes, however, they could not identify a clear cause for this spread. Our results now show that also the representation of GWs have the potential to alter ozone variability and trends in the lower stratospheric mid latitudes in chemistry climate models and hence can play a role for the inter-model spread.…”

Optimized Umkehr profile algorithm for ozone trend analyses

“…At the same time, in the lower stratosphere, atmospheric composition and ozone levels are driven by the climate-impacted changes in the Brewer-Dobson circulation and by seasonal-to-decadal variability in stratospheretroposphere exchange. These processes are difficult to discern and predict based solely on ozone or other atmospheric composition observations (Ball et al, 2019(Ball et al, , 2020Abalos et al, 2019;Orbe et al, 2017;Strahan et al, 2020;Dietmüller et al, 2021). Analyses of the processes that are responsible for ozone changes through atmospheric chemistry and dy-namical transport rely on the development of climate chemistry models (CCMs, Morgenstein et al, 2017).…”