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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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1178', Anonymous Referee #1, 17 May 2024
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 -
RC2: 'Comment on egusphere-2024-1178', Anonymous Referee #2, 27 May 2024
This study takes a closer look at ENSO related variability in tropical tropospheric ozone from the RAQMS-Aura chemical reanalysis. Using multiple linear regression analysis and compositing techniques to show the dominant drivers causing this ozone change depending on region. While the calculated response is similar to what has been shown in some past studies, the use of RAQMS-Aura appears novel including ozone production and loss terms, convective mass flux, and diabatic heating and should be of interest of ACP readership. I would recommend publication pending the authors consideration of a few mostly minor suggestions below.
I think it would be particularly helpful if the authors consider especially for figures 8-14, and 20 to show some indication of significance in the response plots to put the changes in context and help draw the readers eyes to the key areas.
Some of the ozone response to ENSO in the subtropics is related to stratosphere-troposphere exchange, are there any concerns about representing that properly with a model having 35 model levels. Does the use of assimilated data help with any model deficiencies related to resolving those processes?
I don’t believe you cite Oman et al. 2013, please have a look and note some of the discussion related to Quasi-biennial Oscillation (QBO) and its influence that can extend into the troposphere and consider checking and possibly adding terms to your regression analysis to account for its influence.
Oman, L. D., A. R. Douglass, J. R. Ziemke, J. M. Rodriguez, D. W. Waugh, and J. E. Nielsen (2013), The ozone response to ENSO in Aura satellite measurements and a chemistry-climate simulation, J. Geophys. Res., 118, 965–976, doi:10.1029/2012JD018546.
Any concerns about the shift in bias noted in precipitation fields between 2009-2011, compared to observations, impacting ozone response, are there corresponding shifts in any of the ozone response terms.
Lines 404-405 and comment in general: Shifts in precipitation also impact clouds, would this impact be reflected in your net ozone production related to changes in photolysis rates. Or stated more generally on the net ozone productions term can you differentiate that caused by biomass burning emission changes with clouds and photolysis changes.
Lines 51-53 while La Niña responds in a generally opposite manner it is not quite symmetrical
Line 130 al missing period al.
Line 339 need to subscript 3 in O3
Citation: https://doi.org/10.5194/egusphere-2024-1178-RC2 -
AC1: 'Comment on egusphere-2024-1178', Maggie Bruckner, 08 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1178/egusphere-2024-1178-AC1-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1178', Anonymous Referee #1, 17 May 2024
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 -
RC2: 'Comment on egusphere-2024-1178', Anonymous Referee #2, 27 May 2024
This study takes a closer look at ENSO related variability in tropical tropospheric ozone from the RAQMS-Aura chemical reanalysis. Using multiple linear regression analysis and compositing techniques to show the dominant drivers causing this ozone change depending on region. While the calculated response is similar to what has been shown in some past studies, the use of RAQMS-Aura appears novel including ozone production and loss terms, convective mass flux, and diabatic heating and should be of interest of ACP readership. I would recommend publication pending the authors consideration of a few mostly minor suggestions below.
I think it would be particularly helpful if the authors consider especially for figures 8-14, and 20 to show some indication of significance in the response plots to put the changes in context and help draw the readers eyes to the key areas.
Some of the ozone response to ENSO in the subtropics is related to stratosphere-troposphere exchange, are there any concerns about representing that properly with a model having 35 model levels. Does the use of assimilated data help with any model deficiencies related to resolving those processes?
I don’t believe you cite Oman et al. 2013, please have a look and note some of the discussion related to Quasi-biennial Oscillation (QBO) and its influence that can extend into the troposphere and consider checking and possibly adding terms to your regression analysis to account for its influence.
Oman, L. D., A. R. Douglass, J. R. Ziemke, J. M. Rodriguez, D. W. Waugh, and J. E. Nielsen (2013), The ozone response to ENSO in Aura satellite measurements and a chemistry-climate simulation, J. Geophys. Res., 118, 965–976, doi:10.1029/2012JD018546.
Any concerns about the shift in bias noted in precipitation fields between 2009-2011, compared to observations, impacting ozone response, are there corresponding shifts in any of the ozone response terms.
Lines 404-405 and comment in general: Shifts in precipitation also impact clouds, would this impact be reflected in your net ozone production related to changes in photolysis rates. Or stated more generally on the net ozone productions term can you differentiate that caused by biomass burning emission changes with clouds and photolysis changes.
Lines 51-53 while La Niña responds in a generally opposite manner it is not quite symmetrical
Line 130 al missing period al.
Line 339 need to subscript 3 in O3
Citation: https://doi.org/10.5194/egusphere-2024-1178-RC2 -
AC1: 'Comment on egusphere-2024-1178', Maggie Bruckner, 08 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1178/egusphere-2024-1178-AC1-supplement.pdf
Peer review completion
Journal article(s) based on this preprint
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R. Bradley Pierce
Allen Lenzen
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(3520 KB) - Metadata XML