Preprints
https://doi.org/10.5194/egusphere-2026-532
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2026-532
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
26 Feb 2026
| 26 Feb 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Uncertainties in recent tropical stratospheric and tropospheric ozone changes restrict our understanding of future total column ozone change
Abstract. A variety of chemical and dynamical processes in the troposphere and stratosphere affect tropical total column ozone (TCO), the net effect of which may cause changes in surface UV radiation and impact human and ecosystem health. We use dynamical linear modeling to estimate tropical trends in TCO and partial column ozone (PCO) in the troposphere and three stratospheric layers to assess agreement between satellite observational composites and chemistry–climate model (CCM) simulations from two multi-model experiments (CCMI-1 and CCMI-2022). While both model experiments show tropical TCO increases over 2000–2021, CCMI–2022 trends (+2.5 DU) agree slightly better with observations than CCMI-1 (+1.6 DU). However, this overall agreement obscures multiple systematic differences in PCO trends between the models and observations across atmospheric layers. For example, since 2000 tropical tropospheric PCO increased significantly in CCMI-2022 (+1.5 DU) but not in CCMI–1 (+0.3 DU), largely explaining the difference in TCO trends. Also, despite nearly identical stratospheric PCO trends, CCMI-2022 trends are slightly more negative in the lower stratospheric (by ~0.5 DU), compensated by more positive middle/upper stratosphere trends compared to CCMI-1. Crucially, substantial differences exist across observational PCO trends, particularly in the troposphere and middle/upper stratosphere, and these disagreements limit the ability to evaluate CCM fidelity. Furthermore, while the inter-model correlation between late and early 21st century trends is suggestive of a potential emergent constraint on future ozone trends, the spread in observational trends precludes its observational implementation.
How to cite. Davis, S., Ball, W., Jia, Y., Chiodo, G., Alsing, J., Keeble, J., Akiyoshi, H., Arosio, C., Bednarz, E., Chrysanthou, A., Coldewey-Egbers, M., Damadeo, R., Dhomse, S., Diallo, M., Dietmuller, S., Eichinger, R., Frith, S., Hassler, B., Hegglin, M., Hubert, D., Jöckel, P., Josse, B., Kramarova, N., Loyola, D., Maillard Barras, E., Marchand, M., Morgenstern, O., Plummer, D., Portmann, R., Rosenlof, K., Rozanov, A., Sofieva, V., Staehelin, J., Sukhodolov, T., Tourpali, K., Van der A, R., Wang, H. J. R., Wargan, K., Watanabe, S., Weber, M., Wild, J., Yamashita, Y., and Ziemke, J.: Uncertainties in recent tropical stratospheric and tropospheric ozone changes restrict our understanding of future total column ozone change, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-532, 2026.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
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Status: open (until 05 Jun 2026)
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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- RC1: 'Nice summary of observed and simulated ozone trends, questionable extrapolation to the far future.', Anonymous Referee #1, 03 May 2026 reply
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Latest update: 17 May 2026
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
William Ball
Department of Geoscience and Remote Sensing, TU Delft, Delft, The Netherlands
Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
deceased
Univ. of Texas at Dallas, Dallas, TX, USA
Gabriel Chiodo
Instituto de Geociencias, Consejo Superior de Investigaciones Cientificas (IGEO-CSIC), Madrid, Spain
Justin Alsing
Oskar Klein Centre for Cosmoparticle Physics, Department of Physics, Stockholm University, Stockholm, Sweden
James Keeble
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Hideharu Akiyoshi
Earth System Division, National Institute for Environmental Studies, Ibaraki, Japan
Carlo Arosio
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Ewa Bednarz
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado at Boulder, Boulder, CO, USA
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Andreas Chrysanthou
School of Earth and Environment, University of Leeds, Leeds, UK
Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Greece
now at: Instituto de Geociencias, Consejo Superior de Investigaciones Cientificas (IGEO-CSIC), Madrid, Spain
Melanie Coldewey-Egbers
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut fur Methodik der Fernerkundung, Oberpfaffenhofen, Germany
Robert Damadeo
NASA Langley Research Center, Hampton, VA, USA
Sandip Dhomse
School of Earth and Environment, University of Leeds, Leeds, UK
National Centre for Earth Observation (NCEO), University of Leeds, Leeds, UK
Mohamadou Diallo
Institute of Climate and Energy Systems – Stratosphere (ICE-4), Forschungszentrum Jülich, Germany
Simone Dietmuller
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Roland Eichinger
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic
Stacey Frith
Adnet Systems, Inc., Lanham, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Birgit Hassler
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Michaela Hegglin
Institute of Climate and Energy Systems - Stratosphere, Forschungszentrum Jülich, Jülich, Germany
Institute for Atmospheric and Environmental Research, University of Wuppertal, Wuppertal, Germany
Department of Meteorology, University of Reading, Reading, United Kingdom
Daan Hubert
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Patrick Jöckel
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Béatrice Josse
CNRM, Université de Toulouse, Météo‐France, CNRS, Toulouse, France
Natalya Kramarova
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Diego Loyola
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut fur Methodik der Fernerkundung, Oberpfaffenhofen, Germany
Eliane Maillard Barras
Federal Office of Meteorology and Climatology, MeteoSwiss, Payerne, Switzerland
Marion Marchand
LATMOS, Institut Pierre‐Simon Laplace, Sorbonne Université/CNRS/UVSQ, Paris, France
Olaf Morgenstern
National Institute of Water and Atmospheric Research, Te Whanganui-a-Tara / Wellington, Aotearoa New Zealand
School of Physical and Chemical Sciences, Canterbury University, Ōtautahi / Christchurch, Aotearoa New Zealand
now at: Deutscher Wetterdienst, Offenbach, Germany
David Plummer
Climate Research Division, Environment and Climate Change Canada, Montreal, QC, Canada
Robert Portmann
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Karen Rosenlof
NOAA Chemical Sciences Laboratory, Boulder, CO, USA (now retired)
retired
Alexei Rozanov
Earth System Division, National Institute for Environmental Studies, Ibaraki, Japan
Viktoria Sofieva
Finnish Meteorological Institute, Helsinki, Finland
Johannes Staehelin
Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland
Timofei Sukhodolov
Physikalisch Meteorologisches Observatorium Davos/World Radiation Center, Davos, Switzerland
Kleareti Tourpali
Aristotle University of Thessaloniki, Thessaloniki, Greece
Ronald Van der A
Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
H. J. Ray Wang
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
Krzysztof Wargan
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications Inc., MD, USA
Shingo Watanabe
Japan Agency for Marine‐Earth Science and Technology (JAMSTEC), Yokohama, Japan
Advanced Institute for Marine Ecosystem Change (WPI-AIMEC), Tohoku University, Sendai, Japan
Mark Weber
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Jeannette Wild
ESSIC/UMD & NOAA/NESDIS/STAR, College Park, MD, USA (now retired)
retired
Yousuke Yamashita
Earth System Division, National Institute for Environmental Studies, Ibaraki, Japan
Jerry Ziemke
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Morgan State University, Baltimore, MD, USA
Short summary
This study investigates how tropical ozone levels have changed since 2000 in chemistry climate models and satellite observations to determine how well they agree with one another, and to see if current trends can help predict future levels. At some, satellite records disagree significantly on the magnitude of ozone changes. The study shows a connection between recent ozone trends and future ozone levels, suggesting that satellite measurements could help constrain future ozone changes.
This study investigates how tropical ozone levels have changed since 2000 in chemistry climate...
Overall Assessment
The paper uses a dynamical linear model (DLM) to fit slowly varying smooth long-term trend lines to ozone time series from a number of sources: merged observed time series from satellites and simulated time series from two sets of multi-model simulation exercises. The obtained long-term trend lines are then used to derive ozone trends for several atmospheric layers and for different multi-decadal periods. The used data and the methodology are solid and consistent with many other publications. The derived trends are important and help to assess the expected recovery process of the ozone layer on the basis of both satellite observations and model simulations. Overall, I think this is a good and important paper and well suited for ACP.
Major Question
However, I do have a major problem with the extrapolations of trends from the 2000 to 2021 period to the end of the current century, which are presented in sections 7 and 8. To me there are so many uncertainties involved and the end results are, at best, very vague, uncertain and even doubtful. I think this entire part of the paper is unnecessary, weakens the main messages of the previous parts, and makes the paper longer and less clear. I strongly suggest to omit large parts of sections 7 and 8, especially Figs. 10 and 11 and their discussion. Ozone changes after 2030 or so depend a lot on future GHG emissions. CCMI-1 REF-C2 and CCMI-2022 REF-D2 use quite different GHG scenarios, have changes in the used models. Both model exercises make their own predictions, so there is not much point in repeating them here. Because the scenarios and models differ, and the real future emissions are likely to be different again, I don't see much point in using 2000 to 2021 changes to forecast anything in the far future. Matters get even worse when observed 2000 to 2021 changes that do not match the corresponding simulated changes are extrapolated to the end of the century using the poor correlations found for the model simulations. To me this seems a clear case of garbage in = garbage out, and an unnecessary, confusing and potentially misleading effort.
I do like Figure 8 and its discussion. Checking whether applying the DLM to the shorter (observational) period from 2000 to 2021 matches applying the DLM to the longer (simulated) period from 1960 to 2100 makes perfect sense.
I also like Figure 9 comparing the ozone trends during the period of decline with those during the recovery period. I would like to see the same Figure for the trends from the satellite observations. Or those observed trends should also be plotted in Figure 9 (might become too crowded).
Minor Comments
Line 65: are the DU numbers for trends - then they should be DU per decade, or are the for twenty year changes (not trends)? As is now, I found this misleading. Please clarify.
Line 72 to 74: This sentence does not make much sense to me, and captures the major problem I have indicated above. I strongly suggest to drop this sentence, and the corresponding parts of sections 7 and 8.
Line 114: I think you need to include a discussion of more recent tropospheric ozone trend updates from the TOAR II initiative. It would also be good to compare your tropospheric ozone trends to trends from TOAR II.
Line 181: one "a" too much in overlap
Line 193: I am not sure that Petropavlovskikh et al. 2025 is really a good reference for the SBUV-COH dataset. It would be better to also refer to the SBUV-COH Webpage / URL: https://www.star.nesdis.noaa.gov/data/smcd1/ozone/SBUV_OMPS_COH/
Line 238: Is that the MERRA2 zonal mean tropopause, since the satellite data sets all seem to be zonal means as well? Or are you using longitudinally resolved data. Please clarify.
Line 267: how similar are the WMO 2011 and WMO 2018 ODS scenarios (or their corresponding equivalent effective stratospheric chlorine). Can you make a statement on that?
Table 1: I think it would be helpful to have an additional comparable table that summarizes the different observational datasets. In all the following Figures I kept wondering which observational dataset is which.
Figure 2: It would be good to have a third panel that plots the CESM1-WACCM time series also just for the 1984 to 2021 period. Or plot the model results in the top panel along with the SWOOSH time series.
Figure 9: As mentioned above, it would be good to also compare the two trend periods for the satellite observations. Either also plotted in Figure 9 (might become too crowded), or in separate Figure.
Summary
Overall, I think this is a good and important paper that summarizes major ozone trend features of current observational and simulated records. The spread in the results is quite large and demonstrates substantial uncertainty in both observational records and model simulations. As indicated in my major comments, I feel that the paper would become shorter, clearer and more concise if the very speculative and uncertain extrapolations (Figs. 10 and 11 and their discussion) were omitted.