the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A global ozone profile climatology for satellite retrieval algorithms based on Aura MLS measurements and the MERRA-2 GMI simulation
Jerald R. Ziemke
Gordon J. Labow
Natalya A. Kramarova
Richard D. McPeters
Pawan K. Bhartia
Luke D. Oman
Stacey M. Frith
David P. Haffner
Download
- Final revised paper (published on 05 Oct 2021)
- Supplement to the final revised paper
- Preprint (discussion started on 22 Jun 2021)
- Supplement to the preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on amt-2021-159', Anonymous Referee #1, 19 Jul 2021
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2021-159/amt-2021-159-RC1-supplement.pdf
-
AC1: 'Response to Reviewer #1', Jerry Ziemke, 19 Aug 2021
Response to Reviewer #1:
Short resume
This paper presents the development of a vertically resolved ozone climatology based on the merging of MLS measurements with model simulations. The presented data set is compared with a previously developed climatology and independent observations. In addition, the authors present an inter-annual ozone profile climatology, which is also compared with satellite observations. Improvements and advantages w.r.t. previous climatologies are well discussed. This paper fits the scope of AMT, it is well written and scientifically sound. From my side, I only have some minor comments on specific aspects and technical corrections.
Specific comments
- Introduction
I find that the introduction of the paper could be slightly expanded. The authors properly explain the improvements w.r.t. the ML climatology but I would expand if possible the part concerning the usage of this climatology and the issues it tackles, which are mostly already present in the paper but in different sections. Some paragraphs in the paper could better fit in my opinion to the introduction rather than in their current section. For example, the end of section 2.1 where you introduce the studies regarding diurnal ozone variations, with the justification of using only MLS daytime data, should rather be collocated in the introduction than in the data section. Also section 3, first paragraph, when the usage of climatological ozone variability is explained, could also go to the introduction.
Very good point – the Introduction was short, and we have now expanded it discussing applications using the climatologies. Sections 2.1 and 3 discuss some details such as relating to diurnal variability that we thought would be better to discuss in those sections rather than in the Introduction. The ML climatology was based on daytime/nighttime averages and an earlier version of MLS. Also, the ML climatology only went up to 65 km and used ozonesondes for troposphere.
- General idea/possible additional data set
You show in Fig.2 the zonal asymmetries in the ozone field at 5 km and explain the bias in the ML climatology at the end of Section 3.1. Since you have a high spatial resolution both with MLS and GMI, why not providing also a longitudinally resolved climatology, specially for tropospheric ozone or total column?
We decided to limit this paper to zonal-mean climatologies as in our previous ML climatology papers. Inclusion of longitudinal variability invokes additional uncertainties in mean profile numbers due to non-stationary inter-annual changes in the ozone fields. This especially applies to both the MLS/GMI seasonal climatology and REOF climatology due to large year-to-year regional changes in stratospheric ozone. The paper by Ziemke et al. (2011) produced a gridded tropospheric and stratospheric (and thus total) column ozone 12-month seasonal climatology based on combined Aura OMI and MLS satellite measurements. Once we do more validation of the GMI model in the lower troposphere, we will consider adding the longitudinal component to the profile climatology.
- Section 4
I found the description of this section (particularly until beginning of page 16) rather confused with some repetitions and lack of flow. For example, the third paragraph could go at the end as a conclusion of the work done (maybe starting with ’We demonstrated that’. The fourth paragraph could be incorporated into the fifth one, where the step-by-step procedure is introduced. The term ’REOF’ is introduced in the second paragraph as acronym but only explained in the fifth one.
Thanks – we have extensively re-written Section 4 under your suggestions. The Section 4 is a general overview with details remaining in the Supplementary Materials.
- Merging procedure
A simple remark: it is implicitly meant but, I think, never clearly stated that the merging of the profiles occurs on L3 data, i.e. monthly zonal mean MLS data are merged with monthly mean GMI data. I think this could be more clearly stated at the beginning of Section 3.2 or you can say in the MLS data section that you prepared MLS L3 data as you did for M2GMI.
Good point – we describe this now in section 3.2. Yes, merged after monthly means were created.
Technical corrections
P2, l52: I would insert the acronym: ’We have generated a new ozone profile seasonal climatology (MLS/GMI) based...’1
Done.
P4, l105: section→Section
Done.
P4, l109: Now→currently or presently
Done.
P5, l134: I would write ’...for both sonde measurements and GMI TCO was...’
Done.
P5, l136: Most all of the→Most
Done.
P5, l136-138: please move the last sentence of this paragraph to line 131, before explaining the post-processing of the ozonesondes.
Done.
P5, l141: I would remove ’in its construction’ at the end of the sentence.
Done.
P6, l163: provides→provide
Done.
P6, l177:
I find the term ’difference standard deviations’ not so clear, maybe better ’standard deviation of the differences’ of ’RMS of differences’.
Done.
P7, l193: The section in the supplementary material is S3, not S1.
Done.
P9, l245: ’similar to the satellite TCO patterns during May’→’similar to the TCO May pat-tern from satellite records.’
Done.
P12, l299: ’MLS/GMI minus ML’ is opposite to what the title in Fig.4 says. I would also rephrase as ’Figure 4 shows the difference between ML and MLS/GMI zonal-mean column ozone...’.
Done.
P12, l311: I would change to ’the model in this region over-determines the ozone column in DJF by about 2 DU.’
Done.
P13, l317: I would delete the explanation ’with blue/dashed contours meaning negative, and pink to red solid etc..’
We rephrased this sentence for the color scheme.
P15, l354: ’. The time period for this climatology is 1970-2018...’→’, and it corresponds to1970-2018...’
This has been rewritten in the revision.
P15, l369: ’The EOF analysis was applied to monthly zonal mean anomalies derived by removing seasonal cycles in MLS...’→’In detail, we removed the seasonal cycle from MLS...’
This has been rewritten in the revision.
P16, l408: delete ’based on’
Done.
P17, l424: ’Figure 7b is the same as Fig.7a but for the lower altitude range’.
Done.
Supplementary Material
P13: The comparison with Lidar is in Fig.S11 not S12.
Done.
-
AC1: 'Response to Reviewer #1', Jerry Ziemke, 19 Aug 2021
-
RC2: 'Review of the manuscript “A Global Ozone Profile Climatology for Satellite Retrieval Algorithms Based on Aura MLS Measurements and the MERRA-2 GMI Simulation“ by J.R. Ziemke', Anonymous Referee #2, 20 Jul 2021
The manuscript “A Global Ozone Profile Climatology for Satellite Retrieval Algorithms Based on Aura MLS Measurements and the MERRA-2 GMI Simulation“ by J.R. Ziemke describes a new atmospheric ozone profile climatology built from Aura MLS data in the stratosphere and MERRA-2 Global Modeling Initiative (GMI) simulation data in the troposphere. It replaces a climatology that was based on MLS observations and ozone soundings. The new climatology (12 months, based on the period 2004-2016) is available in 5-degree latitude bands from 90S-90N, and covers the altitudes from the Earth’s surface to 80km in about 1km increments. Additionally, a time-dependent climatology of monthly zonal-mean profile ozone anomalies was developed, based on a rotational EOF analysis of Aura MLS observations. These are very useful climatologies and therefore the manuscript provides scientifically interesting analyses and results. The manuscript is very well written, mostly well structured, and the topic lays within the scope of the AMT journal. However, there are a few things that I think would help to improve the manuscript, and that I would suggest the author to consider while revising the manuscript. These comments are outlined below.
I recommend the publication of the manuscript after minor revisions.
General comments:
- Abstract: It is mentioned that the MLS measurements were filtered so only the daytime measurements of MLS were used for the climatology which is beneficial because of the diurnal cycle in ozone in the upper stratosphere and mesosphere. However, that fact is mentioned again in the description of the used MLS observations, but not the results section. Is it then necessary to be mentioned so prominently in the abstract?
- In Section 2.1 the time period of the used MLS data is given as August 2004-December 2016. Does that mean that the climatology is not based on full years only? If so, is the difference in number of data points for calculating the climatology reflected in the climatology somehow?
- In Section 2.2 the abbreviation “MOD” is given as “merged ozone dataset”. However, when it is mentioned in the section there are normally additional identifiers given when “MOD” is mentioned, e.g. line 105 “MOD total ozone dataset”. I recommend checking the instances where “MOD” is used to make sure that the abbreviation is correctly used.
- In Section 2.3 there is, in my opinion, not enough information given about the ozone sounding database that is used. How many stations are included? How many stations are there per latitude band? And how many soundings per month per latitude band are available? I understand that the ozone soundings are only used for validation purposes in this analysis, but some more information about the number of stations and soundings would be very helpful.
- The structure of Section 4 made it hard to understand the content of the section. The first paragraphs feel almost like an introduction to the section without any specific content which raise all kinds of questions that are answered only a few paragraphs further along. I think it would really help this section to be better understandable if it would be restructured and if in some cases paragraphs would be merged/rephrased/reorganized.
More specific comments:
- Page 5, line 126: It might be good to be more specific about the ozone database, e.g. rephrase to “The used ozone database…”
- Page 5, line 130/131: I think the term “The ozonesondes provide daily ozone profile concentrations…” is misleading. Ozone soundings are on most stations not performed on a daily basis, but only a few times a week. I suggest rephrasing this.
- Page 7, line 187: What does the phrase “have been space-time co-located at the sonde station sites” mean with respect to comparison to M2GMI tropospheric column ozone? Were the M2GMI data used directly for the coordinates of the different sounding stations or the soundings used in latitude bands? Were the M2GMI data used for the specific days when the soundings happened or were monthly means calculated from the soundings and then compared to the M2GMI? Please rephrase and be more specific.
- Page 10, line 236: there are two “.” at the end of the sentence.
- Page 11, line 284/285: Maybe it would be worth also to mention what the reasons for the lowest ozone amounts in the different seasons around 20km are?
- Page 12, line 301/302: Should the phrase “Year-round negative differences in the tropics in Fig. 4…” rather be “Year-round positive differences in the tropics in Fig. 4…”? The tropical signal in Figure 4 in the lower and middle troposphere is positive.
- Page 14, line 329: What would be other reasons for the seasonal biases? The text says “Part of the reason…”.
- Page 17, line 423: “The bottom panel in Fig. 7b…” should be “The bottom panel in Fig. 7a…”, I guess.
- Page 19, line 454-456: I find this sentence a little misleading. You mention in the very last sentence of the summary that long-term trends are not included in the REOF climatology. But how would you use the climatology then as baseline for model and observation comparisons without considering this long-term evolution?
- Page 19, line 469: Here the time period of MLS data used for the REOF analysis is given as “August 2004 – December 2016”, however, on page 17, line 371 it is given as “between January 2005 and December 2016”. Which one is correct?
-
AC2: 'Response to Reviewer #2', Jerry Ziemke, 19 Aug 2021
Response to Reviewer #2:
The manuscript “A Global Ozone Profile Climatology for Satellite Retrieval Algorithms Based on Aura MLS Measurements and the MERRA-2 GMI Simulation“ by J.R. Ziemke describes a new atmospheric ozone profile climatology built from Aura MLS data in the stratosphere and MERRA-2 Global Modeling Initiative (GMI) simulation data in the troposphere. It replaces a climatology that was based on MLS observations and ozone soundings. The new climatology (12 months, based on the period 2004-2016) is available in 5-degree latitude bands from 90S-90N, and covers the altitudes from the Earth’s surface to 80km in about 1km increments. Additionally, a time-dependent climatology of monthly zonal-mean profile ozone anomalies was developed, based on a rotational EOF analysis of Aura MLS observations. These are very useful climatologies and therefore the manuscript provides scientifically interesting analyses and results. The manuscript is very well written, mostly well structured, and the topic lays within the scope of the AMT journal. However, there are a few things that I think would help to improve the manuscript, and that I would suggest the author to consider while revising the manuscript. These comments are outlined below.
I recommend the publication of the manuscript after minor revisions.
General comments:
- Abstract: It is mentioned that the MLS measurements were filtered so only the daytime measurements of MLS were used for the climatology which is beneficial because of the diurnal cycle in ozone in the upper stratosphere and mesosphere. However, that fact is mentioned again in the description of the used MLS observations, but not the results section. Is it then necessary to be mentioned so prominently in the abstract?
Good point – the diurnal cycle is a detail that should be discussed in the MLS data section and should not be included in the Abstract which is to convey a generalization of the paper. We deleted these sentences in the Abstract referring to the diurnal variability.
- In Section 2.1 the time period of the used MLS data is given as August 2004-December 2016. Does that mean that the climatology is not based on full years only? If so, is the difference in number of data points for calculating the climatology reflected in the climatology somehow?
Adding or subtracting perhaps a few years for this record will change the derived EOF structures and coefficient time series, but our results including comparisons with SAGE II (1984-2005) indicate that we get a good representative long-term REOF climatology using the current MLS record. For the EOF analysis of the deseasonalized MLS ozone, the beginning and ending months need not end with similar months (i.e., with exact integer number of years).
- In Section 2.2 the abbreviation “MOD” is given as “merged ozone dataset”. However, when it is mentioned in the section there are normally additional identifiers given when “MOD” is mentioned, e.g. line 105 “MOD total ozone dataset”. I recommend checking the instances where “MOD” is used to make sure that the abbreviation is correctly used.
Thanks – this is indeed a confusing acronym issue. For MOD there is also a profile ozone dataset along with the MOD total ozone. We have gone through the manuscript and made appropriate changes consistent with the acronym and its use in previous papers involving the MOD dataset.
- In Section 2.3 there is, in my opinion, not enough information given about the ozone sounding database that is used. How many stations are included? How many stations are there per latitude band? And how many soundings per month per latitude band are available? I understand that the ozone soundings are only used for validation purposes in this analysis, but some more information about the number of stations and soundings would be very helpful.
We have now created a new table for the sondes involving station sites and statistics and placed it in the Supplementary Materials with discussion.
- The structure of Section 4 made it hard to understand the content of the section. The first paragraphs feel almost like an introduction to the section without any specific content which raise all kinds of questions that are answered only a few paragraphs further along. I think it would really help this section to be better understandable if it would be restructured and if in some cases paragraphs would be merged/rephrased/reorganized.
This section has been rewritten in the revision since the previous version was confusing and somewhat disorganized with redundancies. Reviewer #1 had a similar comment about Section 4.
More specific comments:
- Page 5, line 126: It might be good to be more specific about the ozone database, e.g. rephrase to “The used ozone database…”
Done.
- Page 5, line 130/131: I think the term “The ozonesondes provide daily ozone profile concentrations…” is misleading. Ozone soundings are on most stations not performed on a daily basis, but only a few times a week. I suggest rephrasing this.
Done.
- Page 7, line 187: What does the phrase “have been space-time co-located at the sonde station sites” mean with respect to comparison to M2GMI tropospheric column ozone? Were the M2GMI data used directly for the coordinates of the different sounding stations or the soundings used in latitude bands? Were the M2GMI data used for the specific days when the soundings happened or were monthly means calculated from the soundings and then compared to the M2GMI? Please rephrase and be more specific.
This has been rewritten for clarity.
- Page 10, line 236: there are two “.” at the end of the sentence.
Corrected. (line 263)
- Page 11, line 284/285: Maybe it would be worth also to mention what the reasons for the lowest ozone amounts in the different seasons around 20km are?
Lowest ozone is in the tropical troposphere in all seasons.
- Page 12, line 301/302: Should the phrase “Year-round negative differences in the tropics in Fig. 4…” rather be “Year-round positive differences in the tropics in Fig. 4…”? The tropical signal in Figure 4 in the lower and middle troposphere is positive.
This paragraph has now been re-written.
- Page 14, line 329: What would be other reasons for the seasonal biases? The text says “Part of the reason…”.
This has now been re-written.
- Page 17, line 423: “The bottom panel in Fig. 7b…” should be “The bottom panel in Fig. 7a…”, I guess.
Thanks – typo has been corrected.
- Page 19, line 454-456: I find this sentence a little misleading. You mention in the very last sentence of the summary that long-term trends are not included in the REOF climatology. But how would you use the climatology then as baseline for model and observation comparisons without considering this long-term evolution?
Sentence has been re-worded.
- Page 19, line 469: Here the time period of MLS data used for the REOF analysis is given as “August 2004 – December 2016”, however, on page 17, line 371 it is given as “between January 2005 and December 2016”. Which one is correct?
Should be August-2004 – December 2016 and has been corrected.