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. 2019 Aug 16;124(15):8837-8850.
doi: 10.1029/2019jd030996.

Why Do Antarctic Ozone Recovery Trends Vary?

Susan E Strahan  1   2 , Anne R Douglass  1 , Megan R Damon  1   3
Affiliations

Why Do Antarctic Ozone Recovery Trends Vary?

Susan E Strahan et al. J Geophys Res Atmos. .

Abstract

We use satellite ozone records and Global Modeling Initiative chemistry transport model simulations integrated with Modern Era Retrospective for Research and Analysis 2 meteorology to identify a metric that accurately captures the trend in Antarctic ozone attributable to the decline in ozone depleting substances (ODSs). The GMI CTM Baseline simulation with realistically varying ODS levels closely matches observed interannual to decadal scale variations in Antarctic September ozone over the past four decades. The expected increase or recovery trend is obtained from the differences between the Baseline simulation and one with identical meteorology and fixed 1995 ODS levels. The differences show that vortex-averaged column O3 has the greatest sensitivity to ODS change from 1 to 20 September. The observed vortex-averaged column O3 during this period produces a trend consistent with the expected recovery attributable to ODS decline. Trends from dates after 20 September have smaller sensitivity to ODS decline and are more uncertain due to transport variability. Simulations show that the greatest decrease in O3 loss (i.e., recovery) occurs inside the vortex near the edge. The polar cap metrics have vortex size-dependent bias and do not consistently sample this region. Because the 60-90°S 220 Dobson unit O3 mass deficit metric does not sample the edge region, its trend is lower than the expected trend; this is improved by area weighting. The 250-Dobson unit O3 mass deficit metric samples more of the edge region, which increases its trend. Approximately 25% of the September Antarctic O3 increase is due to higher O3 levels in June prior to winter depletion.

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Figures

Figure 1.
Figure 1.
Observed and simulated Antarctic vortex-averaged column O3 (a) averaged over 1–20 September 1980–2018 and (b) averaged over 1–30 June 2005–2018. (c) Vortex column O3 change 2005–2018 between June and 1–20 September, for MLS and GMI with 14-year mean removed. The dashed lines are linear fits to MLS and GMI points. The slopes of the lines, which are the same for the simulation and observations, indicate an ~20 DU reduction in winter O3 loss from 2005 to 2018. TOMS = Total Ozone Mapping Spectrometers; OMI = Ozone Measuring Instrument; OMPS = Ozone Measurements Profiler Suite; MLS = Microwave Limb Sounder.
Figure 2.
Figure 2.
(a) The difference between vortex-averaged column O3 in the High ODS and Baseline simulations as a function of day of the year since 1995. The period of greatest ODS sensitivity is highlighted by the dashed lines. (b) Vortex-averaged column O3 in the Baseline and High ODS simulations in 2018. Their difference (blue) shows that O3 loss sensitivity to ODS decline peaks around 10 September. Before mid-September, the High ODS O3 loss is faster so the differences increase, but after mid-September loss continues at a greater rate in Baseline because O3 levels are higher causing the differences to decrease. (c) O3 differences from (a) averaged over 1–20 September (black) and 1–30 June (red) and EESC change (Baseline-High ODS, blue). ODS = ozone depleting substance; EESC = Equivalent Effective Stratospheric Chlorine.
Figure 3.
Figure 3.
The 1–20 September Antarctic vortex-averaged column O3 and their trends with 95% confidence intervals in parentheses, 2000–2018, for (a) Total Ozone Mapping Spectrometers/Ozone Measuring Instrument/Ozone Measurements Profiler Suite (blue) and Baseline (red) and (b) the Baseline (red) and High ODS simulations (black). ODS = ozone depleting substance.
Figure 4.
Figure 4.
(a) Baseline column O3 and (b) O3 Loss (No Het-Baseline) in Dobson units averaged over 8–14 September in 2017, a warmer than average year. (c, d) The same as in (a) and (b) except for 8–14 September 2018, a colder than average year. The vortex edge (red), 220 DU contour (white), 63°S boundary (yellow dashed), and 60°S boundary (orange dashed) identify the boundaries of the metrics discussed.
Figure 5.
Figure 5.
(a) Observed polar cap and vortex-averaged O3 metrics and their trends with 95% CIs. (b) Differences between the polar cap and vortex-averaged metrics, 2000–2018, from (a).
Figure 6.
Figure 6.
(a) Time series, trends, and CIs for area with <220 DU O3. The areas in black are calculated using daily areas that are averaged over 1–20 September; the areas in blue are the daily High ODS-Baseline area differences averaged over 1–20 September and offset by 24 × 106 km2 (blue), and the areas in red calculate the area <220 DU O3 after averaging all September O3 observations together. (b) OMD metrics, trends, and CIs using 220 DU (black) and 250 DU (red) boundaries, each weighted by the area they cover and the unweighted 220 DU OMD for 60–90°S (blue). ODS = ozone depleting substance; OMD = O3 mass deficit.
Figure 7.
Figure 7.
The reduction in O3 loss (i.e., recovery) due to declining ozone depleting substances from Baseline-High ODS column O3 on 15 September 2018. The regions with the greatest recovery, 25–35 DU, fall outside of the observed 220 DU contour (red) but inside the vortex edge (white). The 220 DU O3 mass deficit metric excludes the region of largest recovery, which biases its trend low. The 220 DU observed O3 contour (red) comes from 24 hr of satellite observations. There is a 23-hr lag between observations at 180°E (bottom of figure) that causes a discontinuity in the contour.
Figure 8.
Figure 8.
The 1995–2018 vortex-averaged (a) O3 Depletion (DU; No Het-Baseline) and (b) O3 transport since June (No Het) as a function of date. (c) The vortex-averaged change in depletion (black) and transport (red) between 1–20 September and 25 September to 14 October. These dates are shown by the red and white dashed lines in (a) and (b). The date ranges are the periods of maximum sensitivity of O3 loss to ODSs (September, red) and maximum seasonal O3 loss (October, white).
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