Consistency Between Zonal Mean Stratospheric and Total Column Ozone Trends (2000&ndash;2024)

Auffarth, Brian; Weber, Mark; Rozanov, Alexei; Arosio, Carlo; Burrows, John P.; Coldewey-Egbers, Melanie; Davis, Sean M.; Degenstein, Doug; Dubé, Kimberlee; Frith, Stacey M.; Froidevaux, Lucien; Loyola, Diego; Fioletov, Vitali E.; Sofieva, Viktoria; van der A, Ronald; Wild, Jeannette D.

doi:10.5194/egusphere-2026-2576

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https://doi.org/10.5194/egusphere-2026-2576

Preprints

11 May 2026

| 11 May 2026

Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Consistency Between Zonal Mean Stratospheric and Total Column Ozone Trends (2000–2024)

Brian Auffarth, Mark Weber, Alexei Rozanov, Carlo Arosio, John P. Burrows, Melanie Coldewey-Egbers, Sean M. Davis, Doug Degenstein, Kimberlee Dubé, Stacey M. Frith, Lucien Froidevaux, Diego Loyola, Vitali E. Fioletov, Viktoria Sofieva, Ronald van der A, and Jeannette D. Wild

Abstract. This study presents an updated assessment of stratospheric and total column ozone trends over the 2000–2024 period using six merged limb-profile datasets and six merged total ozone datasets. Long-term changes were quantified using a multiple linear regression framework that accounts for dynamical and chemical variability. In addition to standard regressors (solar cycle, QBO, ENSO, stratospheric aerosol optical depth), we include Arctic and Antarctic Oscillation indices and the eddy heat flux in each hemisphere as proxies for dynamic variability. Volcanic (and wildfire) aerosol forcing is represented by separate proxies for three periods dominated by the major volcanic events of El Chichón, Pinatubo, and post-2000 volcanic eruptions, including Hunga-Tonga. These period-specific proxies are employed to better account for varying dynamical ozone responses that largely depend on the season and location of the eruptions. All profile datasets consistently show positive trends in the upper stratosphere, with the strongest ozone recovery in southern mid-latitudes, in agreement with other studies. In the lower stratosphere, trends remain weak, spatially heterogeneous, and predominantly negative. A comparison of stratospheric column trends derived from profile data with total ozone trends shows close agreement across latitude bands. Within the trend uncertainties, total column trends since 2000 are largely driven by stratospheric ozone changes, while tropospheric contributions to zonal-mean total ozone trends (the difference between total and stratospheric column trends) appear negligible. The extended regression framework improves the representation of recent dynamical variability and provides an updated perspective on stratospheric ozone recovery through 2024.

Received: 04 May 2026 – Discussion started: 11 May 2026

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RC1:
'Comment on egusphere-2026-2576', Anonymous Referee #1, 20 May 2026 reply
General Comments
This manuscript provides an updated assessment of ozone trends during the 2000–2024 period using several merged ozone profile and total column ozone datasets together with a multiple linear regression (MLR) technique. The results show that the MLR can better capture dynamical variability in ozone when additional dynamical regressors are included, especially for the SH polar region in September. The analyses with additional dynamical regressors also indicate more pronounced ozone recovery in the SH lower stratosphere, even though the positive trends remain within the uncertainty range (2σ) of the results obtained without the additional dynamical regressors.
The topic is relevant to the scientific questions within the scope of ACP. The approach and methodology are sound. There are, however, several minor issues and questions that should be addressed or clarified. After these issues are resolved, I strongly recommend publication.
Specific Comments
Page 4, Figure 1: The instrument datasets listed for creating GOZCARDS are SAGE-I, SAGE-II, HALOE, and Aura MLS. However, UARS MLS and ACE-FTS were also included in the GOZCARDS ozone database according to Lucien et al. (2015) (reference listed in Table 3). Please verify whether these two instruments were unintentionally omitted from Figure 1 or whether they are no longer included in the latest version of the dataset.

Page 5, Figure 2: OMPS-NP data have been used in several merged datasets, such as SBUV/NASA (MOD), SBUV/NOAA (COH), and MSR-2. For clarification, more detailed information should be provided to distinguish the different OMPS-NP satellites. For example, it would be better to replace “OMPS-NP” with “OMPS-NP (Suomi-NPP)” for the SBUV/NASA (MOD) dataset. More detailed information should also be provided for the “OMPS” instrument used in MSR-2.

Page 6, Table 1: Similar to comment #2, more detailed information is needed for “OMPS” in the instrument column for MSR-2. In addition, for NOAA/SBUV (COH), the OMPS-NP instrument from NOAA-20 is missing in Table 1, although it appears in Figure 2.

Page 8, Figure 8: It is not clear from either the figure caption or the text in Section 3.1 what “reference” value was used to define the differences before calculating the trends in those differences. In other words, was the reference based on MLS Level-3 or Level-2 data (e.g., by first converting individual profiles)? This information would help readers better interpret the sign of the trends in the differences and the impact of coordinate conversion on the derived ozone trends.

Lines 153-154, “It ranges from 0.5 to 0.75%/decade between 60⁰S and 60⁰N and above 20km”. This statement is applicable for 2000 to 2024 period, but not for 1985 to 1995 period (Figure 4a). The sentence should be revised for clarity.

Lines 156-157, “and the results are shown for the period after 1996 (ODS peak) and 2000 in Figure 5.” This sentence implies that the total ozone data periods shown in Figure 5 are 1996–2024 and 2000–2024 (red and blue lines). However, the Figure 5 caption indicates “until 1995 and since 2000” (i.e., 1985–1995 and 2000–2024). Please clarify the wording for consistency.

Page 10, Equation (2), there are typos in the “inflection time” corresponding to the linear trend coefficients, β13(z,t)(t-t1), and β16(z,t)(t-t2). The terms t1, and t2 should be corrected to t0, and t1, respectively.

Lines 174-175, A special term, L_Gap(t), is used for the 1996-1999 period due to “the sparse sampling of the merged ozone profile datasets”. During this period, the main contributing satellite measurements came from SAGE II and HALOE (see Figure 1). Since there were no major volcanic eruptions (Figure A1) or extended periods of instrument problems during that time, could the authors elaborate further on the cause of sparse sampling, and did the sparse measurements mainly occur in specific latitude or altitude regions?

Page 14, Figure 6. The regression coefficients of the proxy terms are shown as functions of latitude and altitude, but there is no information regarding the statistical significance of those coefficients. It would be helpful to use hatching to indicate insignificant coefficients (similar to Figure 3). This would provide additional insight into the remarkably different impacts of the three volcanic aerosol proxies (Figure 6i, j, k). A related question concerns Figure 6k, the El Chichon aerosol proxy appears to result in ozone increases in the mid-latitude lower stratosphere (below 20km). Is this feature an artifact of MLR fit or has it been reported in previous studies?

Line 285, “SH trends are lower and remain at about +0.5DU/decade”. The trend value appears to be a typo. It should be approximately 1 to 1.5 DU/decade (or ~0.5 %/decade).

Line 354, “in % per decade Fig. A7) can can be compared”. Please correct the typos, for example, “in % per decade (Fig. A7) can be compared”.

Lines 359-360, “The larger variations in SH trend profiles, ….. is due to the smaller positive trends seen in GOZCADRS compared to all other merged datasets.” The smaller positive GOZCARDS trends mainly occur above 25 km. Below 20 km the larger variations in trend profiles are mainly associated with SAGE-SCIA-OMPS and SAGE-OSIRIS-OMPS. For clarification, I recommend revising the sentence to specify the altitude range, for example, “The larger variations in SH trend profiles for altitudes above 25 km, …, is due to the smaller positive trends seen in GOZCARDS….”.

Lines 417-418, “For the stratospheric column calculations, data were screened out if more than three of the five layers above the tropopause had missed data”. Conventionally there should be no missing data above the tropopause when calculating stratospheric column ozone. Which five layers were used for screening criteria, and how were the missing data treated (e.g. interpolation) before calculating the stratospheric column ozone?

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Citation: https://doi.org/10.5194/egusphere-2026-2576-RC1

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Short summary

This study examines the trends of stratospheric and total ozone between 2000 and 2024, using long-term satellite datasets. Our results show positive trends in the upper stratosphere and a strong ozone recovery in the Southern Hemisphere, while changes in lower altitudes remain mostly small. The total and stratospheric trends show very similar results, indicating that tropospheric ozone contributes little to total column changes, while the stratospheric column is the dominant driver.


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