the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Dec 2024
Long-term satellite trends of European lower-tropospheric ozone from 1996–2017
Abstract. Tropospheric ozone (O3) is a harmful secondary atmospheric pollutant and an important greenhouse gas. Satellite records have shown conflicting long-term tropospheric ozone trends over the globe, including Europe. Here, we present an in-depth analysis of lower-tropospheric sub-column O3 (LTCO3, surface – 450 hPa) records from three ultraviolet (UV) sounders produced by the Rutherford Appleton Laboratory (RAL): the Global Ozone Monitoring Experiment (GOME, 1996–2010), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY, 2003–2011) and Ozone Monitoring Instrument (OMI, 2005–2017). Overall, GOME and SCIAMACHY have negative trends of approximately -0.2 DU yr-1 across their respective full records, while OMI indicates a negligible trend. The TOMCAT 3-D chemical transport model was used to investigate processes driving simulated trends and try to identify possible reasons for discrepancies between the satellite records. However, the model trends generally showed negligible change in LTCO3, even when spatiotemporally co-located to the satellite level-2 swath data and convolved by averaging kernels. Model sensitivity experiments with the emissions or meteorology fixed to 2008 values aimed to isolate the impact of these processes on the simulated LTCO3 trend. Overall, the experiments highlighted a long-term steady balance in these processes with small positive trends (<0.1 DU yr-1) between 1996 and 2008 and then small negative trends (>-0.1 DU yr-1) between 2008 and 2017. As a result, it is difficult to detect a robust and consistent linear trend in European lower tropospheric O3 between 1996 and 2017, which is masked by large inter-annual variability in the model, ozonesonde and UV satellite instrument records.
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RC1: 'Comment on egusphere-2024-3717', Anonymous Referee #1, 30 Jan 2025
Pimlott et al. present an analysis of the trend of low altitude ozone (surface – 450 hPa) over Europe for the period 1996-2017. They compare three satellite datasets, GOME, SCIMACHY and OMI, and use a chemical transport model, TOMCAT, to assess the role of changing emissions and variable meteorology in driving the trend.
The paper is well written and presents a useful comparison of different satellite ozone products. Its content is suitable for ACP.
The relatively limited scope and clear description of the study means I have few comments. Overall, I recommend it for publication after the following issues have been dealt with.
Line 220: While averaging kernels are an important part of satellite-model comparison and known to the remote sensing field, there are many in the modelling field who know little of them. More detail should be given as to how they work and why they can alter the trend so substantially (e.g. GOME).
The change in emissions over the period of interest should be described in more detail and shown graphically to give the reader an idea of the (relative) magnitude of the changes in key species including NOx and CO. Spatially variation should also be considered as different parts of Europe are likely to have different temporal variations in emissions.
While I do not wish to create substantially more work for the authors, an interesting additional experiment might be to fixed say the emissions over the Po Valley and surrounding regions, where the strongest modelled reduction in O3 is simulated, and allow emissions in other regions to vary to determine the relative influence of local O3 production and longer range transport.
I notice that there are several missing references which are denoted with the text: “Error! Reference source not found.”
The complexity of the O3 satellite data for those outside the remote sensing community means I would recommend that the data used for this study are uploaded to the referenced Zenodo repository along with the model data.
Citation: https://doi.org/10.5194/egusphere-2024-3717-RC1 - CC1: 'Comment on egusphere-2024-3717', Owen Cooper, 03 Feb 2025
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RC2: 'Comment on egusphere-2024-3717', Anonymous Referee #2, 18 Mar 2025
Pimlott et al. investigated long-term trends (1996-2017) in tropospheric ozone over Europe using measurements from satellite instruments (GOME, SCIAMACHY, OMI) and ozonesondes, as well as simulations from a global chemical transport model (TOMCAT). The trend analysis is thorough and the information is presented very clearly. My comments mainly relate to the significance of the results and their interpretation within a broader context.
General comments:
1. Given that the major outcome of this work is a near-zero trend in tropospheric ozone across the period of interest, why is this outcome significant? Can we draw any major conclusions about the processes controlling ozone during this period? Any insights into a future outlook for tropospheric ozone? I understand that the authors have explored some of the underlying processes using sensitivity simulations with TOMCAT but the overall significance of the results found in this work could be addressed more directly.
2. More background information is needed in the introduction to put this work into a broader context and to assist in the interpretation of results. For example, the authors did mention that anthropogenic ozone precursor emissions declined over the period of interest, but this is only one piece of the puzzle - ozone chemistry and its dependence on precursor emissions is not linear (which in itself may offer a possible explanation for a near-zero trend in recent years) and this must be communicated in the manuscript. Precursor emissions are similarly complex and can be anthropogenic but have other sources too, including vegetation and biomass burning, and this should be discussed as well. I would also like to see some discussion of how meteorology affects tropospheric ozone as this is a major process investigated in the sensitivity simulations conducted by the authors towards the end of the manuscript.
Minor comments:
Line 128: Please provide more information here about the ozonesonde corrections: How are these corrections applied? How much do they impact the total reported values? Do the corrections differ between the three satellite products? Understood that references are provided but this seems worth addressing directly in the manuscript, especially if the corrections are sizeable or if there’s a chance that the corrections could contribute to differences between the three satellite products during the period of overlap.
Line 133: How are these error values calculated? Any idea how the RAL products compare to other retrievals that may exist for the same instruments?
Section 2.2: Where are the ozonesondes launched from? An additional figure might be useful here to place their locations within the European domain.
Line 225 and elsewhere: Why include TOMCAT results where the averaging kernels are not applied? My understanding is that AKs are applied to align the vertical sensitivity between the model and the satellite measurements, and that the two datasets are not truly comparable until this is done.
Section 3.3: Could a near-zero overall trend in tropospheric ozone be due to a cancelling of larger positive and negative trends in different locations across the domain? Precursor emissions may be declining in Europe but what trends are coming from Africa? What could be driving those trends? Overall, transport from Africa seems to be an important contributing factor and could be developed further in the interpretation of results.
Section 3.4: What is meant by “meteorology” here? Which variables specifically did you investigate?
Line 358: The authors state “Model sensitivity experiments also suggest that spatiotemporal variability in processes (i.e. precursor emissions, meteorology, and the stratosphere-tropospheric flux) controlling lower tropospheric ozone have remained stable” but this is not consistent with the previous assertion that precursor emissions have decreased over that time.
Table 3: Some of the entries in the first column appear to be mislabeled (TC-EMS (1996-2008) and TC-MET (1996-2008) appear twice)
Throughout: Seems to be some inconsistency in using 2017 vs 2018 to represent the final year of the long-term record
Throughout: Errors in some figure reference labels
Citation: https://doi.org/10.5194/egusphere-2024-3717-RC2
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