the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Mar 2025
Tropospheric ozone responses to the El Niño-Southern Oscillation (ENSO): quantification of individual processes and future projections from multiple chemical models
Abstract. The El Niño-Southern Oscillation (ENSO) modulates tropospheric ozone variability, yet quantitative contributions from individual processes and future responses remain unclear. Here, we evaluate GEOS-Chem chemical transport model and ten climate-chemistry models (CCMs) in Coupled Model Intercomparison Project Phase 6 (CMIP6) in capturing ozone-ENSO responses, quantify the roles of transport, chemistry, and biomass burning, and examine the future evolution of these responses. GEOS-Chem simulation over 2005–2020 well reproduces satellite-observed ozone-ENSO responses, including the instantaneous decrease (increase) in tropospheric column ozone (TCO) over tropical eastern (western) Pacific in El Niño, and the delayed responses in subtropics and mid-latitudes. The combined effects of transport, chemistry, and biomass burning emissions explain over 90 % of the simulated TCO variability in tropical Pacific during ENSO. Changes in transport patterns show the dominant role by explaining 53 % (+0.8 DU) and 92 % (-2.2 DU) of the variability in TCO respectively in the western and eastern Pacific during El Niño relative to normal periods. Chemical depletion reduces ozone by 0.2 (0.7) DU in the western (eastern) Pacific, which is offset by enhanced biomass burning emissions of 0.4 (0.1) DU. Only five of ten CMIP6 CCMs, with interactive tropospheric chemistry and accurate representation of anomalous circulation with ENSO, reproduce the tropical ozone-ENSO response. These models consistently indicate that tropical ozone-ENSO response will increase by 15–40 % in 2100 under the SSP3-7.0 scenario, associated with strengthening anomalous circulation and increasing water vapor with global warming. These results are critical for understanding climate-chemistry interactions and for future ozone projection.
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Status: open (until 22 May 2025)
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RC1: 'Comment on egusphere-2025-782', Anonymous Referee #1, 23 Apr 2025
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Review of “Tropospheric ozone responses to the El Niño-Southern Oscillation (ENSO): quantification of individual processes and future projections from multiple chemical models” by Li et al.
Manuscript summary
This study investigates the response of tropospheric ozone to ENSO using a combination of satellite data, the GEOS-Chem chemical transport model, and CMIP6 chemistry-climate models (CCMs). The authors evaluate GEOS-Chem against OMI/MLS satellite observations, conduct sensitivity experiments to disentangle the roles of transport, chemistry, and biomass burning, and assess how well CMIP6 models capture the observed ozone-ENSO relationship. Finally, the study examines projections under the SSP3-7.0 scenario using selected CMIP6 models.The key conclusions are:
- GEOS-Chem reproduces observed ozone-ENSO variability very well.
- ENSO-driven changes in transport (via the Walker Circulation) explain most of the ozone variability, though chemistry and biomass burning also contribute.
- CMIP6 models with interactive chemistry capture the ozone-ENSO response more realistically than those with prescribed chemistry.
This is an interesting and timely study that falls well within the scope of ACP. I recommend publication after the following concerns are addressed.
Major Comments
- The manuscript would benefit from a deeper discussion of the limitations of the sensitivity experiment design. The assumption of linear additivity may not fully capture the interactions between transport, chemistry, and emissions. For example, transport changes also affect precursor distributions, which in turn influence ozone chemistry. Can the authors quantify how much of the total ozone response is not explained by the sum of the isolated processes (e.g., residuals)? This would help assess the robustness of the attribution.
- The discussion of chemical contributions to the ozone-ENSO response is somewhat limited. It would be helpful if the authors could provide quantitative changes in lightning NOx and BVOC emissions under ENSO conditions from their simulations. Can these changes be linked to the observed or modelled ozone responses, particularly in the eastern Pacific?
- While spatial correlation is an informative metric, the authors do not assess how well the models capture the magnitude of interannual variability in TCO. A model may simulate the correct spatial pattern but still underestimate variability. Consider including an evaluation of the standard deviation or amplitude of the TCO–ENSO relationship (e.g., variance in the regression residuals) for each model.
- The manuscript lacks a clear explanation of how ENSO events are identified in the CMIP6 models under the SSP3-7.0 scenario. Since these models are free-running, ENSO phasing and intensity are not aligned with observations and may differ significantly between models.
Minor Comments- The frequent use of opposing effects in parentheses (e.g., “increase (decrease)”) in the abstract and main text is hard to read. Consider rephrasing for clarity.
- The introduction would benefit from additional references, especially in lines 32, 33, 44, and 46. In particular, the discussion of BVOC and lightning NOx responses to ENSO could be expanded. Suggested references:
- https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/jgrd.50857
- https://bg.copernicus.org/articles/20/4391/2023/
- https://www.frontiersin.org/articles/10.3389/ffgc.2018.00012/full
- Lines 136–137 suggest that GEOS-Chem runs freely, but the model is in fact driven by nudged reanalysis meteorology. Please clarify this to avoid contradiction.
- The SST values used in the sensitivity simulations should be described more clearly.
- Line 205 – consider rephrasing to improve clarity.
- More explanation is needed on how r_TCO–Niño3.4 is calculated. Are the Niño3.4 index values spatially uniform?
- While the manuscript avoids using a p-value threshold, some discussion of statistical confidence is warranted. How confident are the authors that the reported correlations and sensitivities exceed internal variability?
- Line 274 – citation needed.
- Line 364 – “nudging” is more accurate than “imposing.”
- Line 375 – are these effects statistically significant?
- Line 399 – citation needed.
- Use the more established term Chemistry-Climate Models (CCMs) instead of “climate-chemistry models.”
- The manuscript would benefit from a brief overview of the SST and ocean components in the CMIP6 models.
- Line 374 – contains a typo.
- Lines 510–517: The explanation of future projections is unclear. How are you comparing responses under “the same SST anomalies” when SSTs are not synchronised across free-running models? Please clarify or rephrase.
Citation: https://doi.org/10.5194/egusphere-2025-782-RC1 - GEOS-Chem reproduces observed ozone-ENSO variability very well.
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