the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Examining ENSO related variability in tropical tropospheric ozone in the RAQMS-Aura chemical reanalysis
Abstract. The El Niño-Southern Oscillation (ENSO) is a major driver of interannual variability in both tropical and mid-latitudes and has been found to have a strong impact on the distribution of tropospheric ozone in the tropical Pacific in satellite observational datasets, chemical transport models, and chemistry-climate simulations. Here we analyze interannual variability in tropical tropospheric ozone by applying composite analysis, empirical orthogonal function (EOF) analysis and multiple linear regression to the Real-time Air Quality Modeling System (RAQMS) Aura chemical reanalysis. As shown in similar studies, the dominant mode of interannual variability in tropical tropospheric ozone is driven by ENSO. ENSO composites show that the ENSO signature in tropospheric ozone is strongest near the tropopause. We also show an enhancement in tropical ozone over the maritime continent below 700 hPa during El Niño that is dependent on the magnitude of the biomass burning emissions in the region. We reconstruct the ENSO variability in tropical tropospheric ozone through a multiple linear regression of principal components for precipitation and CO. The multiple linear regression quantifies that variability in biomass burning contributes to ENSO variability in tropical tropospheric ozone though the dominant driver is convection.
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Status: open (until 14 Jun 2024)
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RC1: 'Comment on egusphere-2024-1178', Anonymous Referee #1, 17 May 2024
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Bruckner et al use the RAQMS-Aura chemical reanalysis to explore the relationship between tropospheric O3 and ENSO. Using observations from the TRMM satellite, they demonstrate that their reanalysis captures the variability in tropical convection. Then, using composite analysis, EOFs, and a multiple linear regression they show that ENSO is the dominant driver of O3 variability in the tropics. The MLR analysis highlights that ENSO-related dynamical changes are the dominant driver of this ENSO-related variability, although biomass burning also has a meaningful contribution. This paper is suitable for publication in ACP after the following minor issues are addressed.
Line 95: What AIRS CO products are you using? The total column, which is not advised, or the layers product? If it is the layers product, please describe which layers are included.
Section 3.1: While you perform a thorough evaluation of the RAQMS-Aura precipitation, a discussion on the evaluation of the accuracy of the O3 and CO using independent data is also warranted. While the anomaly plots in Section 3.2 do suggest that the reanalysis captures the ENSO related variability of the column amounts of these species, a more thorough analysis akin to the TRMM analysis would be beneficial. If this has already been done in a separate paper, a simple reference would suffice. Also, how accurate is the vertical O3 in the reanalysis? This could be evaluated with something like SHADOZ ozonesondes.
Figures 4 -6: Why not combine these into a single figure?
Line 332: Show how you are defining ozone production. What reactions/species are included here?
Line 410: In your MLR analysis, you include both the PC1CO and PC1precip terms, which are somewhat related (r = -.435). How does this relationship affect the interpretability of the results of your MLR? How can you be sure that the impacts of one variable aren’t being convolved with the impacts of the other?
Section 3.3.2: Oman et al (2013) demonstrated an impact of the QBO on upper tropospheric O3. Can you separate the QBO and ENSO impacts on your results, since the Nino3.4 and QBO EOF1 indices are relatively strongly anti-correlated? How does omission of this term from your MLR affect the results? Some discussion of potential QBO impacts on your results is warranted.
Oman, L. D., Douglass, A. R., Ziemke, J. R., Rodriguez, J. M., Waugh, D. W., & Nielsen, J. E. (2013). The ozone response to ENSO in Aura satellite measurements and a chemistry-climate simulation. Journal of Geophysical Research-Atmospheres, 118(2), 965-976. https://doi.org/10.1029/2012jd018546
Citation: https://doi.org/10.5194/egusphere-2024-1178-RC1
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