TROPOMI aerosol products: evaluation and observations of synoptic-scale carbonaceous aerosol plumes during 2018–2020

Torres, Omar; Jethva, Hiren; Ahn, Changwoo; Jaross, Glen; Loyola, Diego G.

doi:https://doi.org/10.5194/amt-13-6789-2020

Articles | Volume 13, issue 12

https://doi.org/10.5194/amt-13-6789-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

TROPOMI on Sentinel-5 Precursor: first year in operation (AMT/ACP...

https://doi.org/10.5194/amt-13-6789-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 12

Research article

|

15 Dec 2020

Research article |

| 15 Dec 2020

TROPOMI aerosol products: evaluation and observations of synoptic-scale carbonaceous aerosol plumes during 2018–2020

Omar Torres, Hiren Jethva, Changwoo Ahn, Glen Jaross, and Diego G. Loyola

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Final revised paper (published on 15 Dec 2020)
Preprint (discussion started on 13 May 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review of TropOMI aerosol products manuscript', Anonymous Referee #1, 03 Jun 2020
- AC1: 'reply to reviewer 1', Omar Torres, 16 Aug 2020
RC2: 'Review of Torres TropOMI aerosol paper', Anonymous Referee #2, 10 Jun 2020
- AC2: 'reply to reviewer 2', Omar Torres, 16 Aug 2020
RC3: 'Review of the manuscript “TROPOMI Aerosol Products: …”', Anonymous Referee #3, 15 Jun 2020
- AC3: 'reply to reviewer 3', Omar Torres, 16 Aug 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Omar Torres on behalf of the Authors (29 Aug 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (10 Sep 2020) by Daniel Perez-Ramirez

RR by Anonymous Referee #2 (21 Sep 2020)

Suggestions for revision or reasons for rejection

I reviewed the previous version of this paper. My main concern then was that it did not provide enough technical detail on the TROPOMI product and its performance relative to OMI to inform a data user. I also thought the case studies of recent major aerosol events weren’t fleshed out enough for that to be the main focus. In this revision the authors have expanded the study significantly, especially in terms of TROPOMI-OMI comparability, which removes my main concern. This version has sufficient new content and aligns better with the scope of AMT; it is also clearer to read. In these respects it is a very good paper and will be of a lot of interest to the community.

Unfortunately the authors did not address a statistical problem (invalid use of linear least squares regression) I pointed out in my previous review. The data violate the assumptions made by this analysis technique. This concerns sections 3.1.2, Table 2, Figure 3, and some later discussion (including the Summary at the end of the paper). Here I will try to articulate more clearly why this is an issue. I therefore recommend further revisions to fix this.

The remedy is simple: just delete the lines, intercept, and slope, and the discussion. Removing it will not harm the paper. I appreciate the authors adding cautionary wording (page 7) not to over-interpret but it would still be better to delete these.

I don’t believe it is responsible to publish bad statistics, especially when authors and editor are aware of the fact; it does nothing except inform people they can get away with it. I am open to a valid counter-argument to this but am yet to hear one; “it is common” (as here) is not a scientific argument to me. I am not trying to shut down the paper, it is a good paper other than this.

As an alternative, the authors could overplot binned median and standard deviation of error (or similar) as a function of AOD on figure 3 instead of the regression. It will be more informative as to the actual distribution of retrieval errors. We can look at the data, at the correlation and RMSE (which are not ideal but are less problematic diagnostics for the present purpose), and see TropOMI is better.

The regression just muddles the issue as it invites the authors and readers to make an interpretation which is flawed because of the use of inappropriate statistics. As a case in point, Table 2 gives intercepts around +0.25 for Figures 3b and 3c. If you look at the data, it is clear that the point cloud of AOD up to about 0.5 is not pointing towards those being the actual intercepts if an AOD of 0 were measured. The true intercept looks smaller (but still positive). There are a small number of outliers pulling it up which are likely not reflective of the actual data. Regression amplifies these because the outliers are more extreme than the technique assumes. The position and torque of that cloud (AOD up to 0.5) may be different from that for higher AOD. So the relationship is not linear on aggregate. And as the authors note a relative uncertainty means those latter points shouldn’t be weighted as heavily anyway. All of which is why you get an artificial high intercept and low slope.

Sure, TROPOMI calibration issues likely are real and cause a bias but it seems a stretch to imply this is causing an offset of +0.25 in low AOD. Figure 3a (for OMI) has a similar issue: regression intercept is +0.1 with again a small number of extreme outliers pulling it up. If you look at the OMI AOD, when AERONET AOD is low most of the time it OMI is in fact around or below the 1:1 line. So what is this intercept telling us that is useful? Nothing, it is misleading us compared to if we look at the data. Yet these are the numbers highlighted in the paper’s Conclusion. The regression adds nothing of value and hides information in a biased way. Just take a close look at Figure 3.

I am not trying to be negative. I respect the authors’ work a lot and they (here and elsewhere) do a very nice job getting the most out of spaceborne UV measurements. They continue to make improvements which enable people to do new and exciting science unavailable from other platforms. I just want bad statistics to stop being published when there is no need to.

I had a couple of other small comments:

Figures 5, 6: How are standard deviations here calculated? I am not sure if this the standard deviation of all retrievals in the month, or between days from a daily average, or spatially from a monthly average, for example. This should be stated in text or caption. I ask as some of these (e.g. eastern US, Jan 2020 AOD) have a very high standard deviation and I am not sure if this is attributed to spatial variability across the region or an event causing temporal variability within that month, or something else.

Page 11 lines 9-10: “where TROPOMI measured monthly average AOD in the vicinity of 1.0 0.9 are reported. downwind over the southeast” It looks like some text got cut off here as “1.0 0.9” does not make sense and then there is a loose sentence fragment.

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RR by Anonymous Referee #1 (21 Sep 2020)

Suggestions for revision or reasons for rejection

Summary
This revised manuscript now reads like an AMT paper. I congratulate the authors for digging in to produce a much more informative paper. I believe now the manuscript is ready for publication with just a list of mostly technical corrections to make to the text. I also make comments, but these should not be taken as requirements to be rectified, but more as suggestions for the authors to consider in either revising this paper or proceeding to the next one.

Corrections and comments.
p. 2 Line 12. Insert “an” to read “Per an established”
p. 2 Line 24. Insert a space between “section” and “3”
p. 3 Line 31. Insert a hyphen to read “TROPOMI-measured radiances”
p. 3 Line 31. Change “to” to “into” to read “input into a two-channel”
p. 7 Lines 35-37. It may not be calibration. Could it be something particular to the 331 new points that TropOMI picks up that OMI misses?
p. 8 Line 16. Re-write to read “Because AERONET SSA derived from almucantar scans is considered unreliable near noon (Dubovik et al., 2002) when satellite overpass occurs, “
p. 8 Line 21. Insert “the” to read “Although the Version 3”
p. 8 Line 22. Delete “over” and insert “a” to read “covering a wider range”
p. 8 Line 23. Replace “is” with “are” to read “sensors are capable”
p. 8 Line 30. Replace “Table 2” with “Table 3”
p. 9 Lines 22 – 24. I wouldn’t be so sure that there is a cancellation of error or even that AAOD shows a closer agreement than AOD. Did you expect that AAOD would have a difference of 0.2 when the magnitude of AAOD is only 0.10? Differences would have to be smaller than AOD because magnitudes of AAOD are smaller than AOD. The relative difference in the AAOD is basically the same percentage as the relative difference in AOD.
p. 9 Line 31. Should read “northwest India”
p. 10 Line 6. Insert “the” to read “improved the near UV”
p. 10 Line 22. Insert “the” to read “to the California”
p. 10 Section 4.1. What wavelength is this AOD? Also both sensors miss retrieving AOD in the core of the plume. Out of range of the retrieval? Masked for cloud?
p. 11 Line 9. Rewrite to read “where TROPOMI-measured monthly average AOD in the range of 0.9 to 1.0 are reported.”
p. 11 Section 4.2. Do you want to give a reference for the media attention? Do you want to say something about TROPOMI continuing the OMI time series? Because if not, why is this in this paper? Also, I notice that there are differences in the time series between the two sensors. These differences are not large enough to question the ability to recognize big years from small years, but they are differences with respect to quantifying amounts.
p. 11 Line 22. Make “region” plural to read “over regions up north”
p. 11 Line 28. Change to read “including species that were near extinction before the fire”
p. 11 Line 30. Change to read “aerosols into the Southern Hemisphere”
p. 12 Line 8. Add a comma (this one is important) to read “provided ALH information, and assumed AAE value”
p. 12 paragraph from Line 25 to p. 13 Line 2. Some things are unclear to me. In equation A-1, the sum is over “the total area covered by the aerosol plume” meanwhile there is a parameter “A” in equation A-1. The “A” is the effective geographical area with retrieved stratospheric AOD. Are these the same thing? Or is “A” the area covered by a single pixel of the retrieval? Is the total area of the plume some sort of latitude longitude box, or the total area defined by whether or not there are aerosols determined to be above 12 km within some sort of latitude longitude box?
p. 12, more on the same paragraph. The statement about dilution is confusing. “spreads the aerosol layer horizontally and thins it out”. Does this mean that the aerosol passes out of the area in the horizontal? If it were only a matter of spreading out horizontally but staying within the same domain, the total mass in the domain would be the same. Concentration would decrease but total mass is the same. It seems to me that what is happening is that the aerosol is falling below 12 km and thinning out because of deposition of some kind. I see it as a vertical issue not a horizontal one.
p. 13 Lines 35-36. I did not understand this sentence. Is “exacerbated” the correct word here?
p. 14 Line 5. All through the paper there is an assumption that we know what wavelength is being discussed. It would be helpful occasionally, including here in the Summary, to say “AOD at XXXX” and give the wavelength.
p. 14 Line 20. Remove “presence” to read “levels of carbonaceous aerosol were detected in 2019”
p. 14 Line 26. Replace “in” with “into” to read “carbonaceous aerosols into the Southern”
p. 14 Line 28. Make “layers” singular to read “a distinct high-altitude aerosol layer near 12 km”
p. 14 Line 29. Add hyphen to read “TROPOMI-retrieved”
p. 14 Line 31. Replace “in” with “into” to read “injected into the stratosphere”
p. 23 Figure 2 caption. Please state the wavelength
p. 24 Figure 3 caption. Add at the end “See text for details and Table 2 for linear regression statistics.” Also please state the wavelength.
p. 25 Figure 4. With TropOMI you start to see a real separation in SSA by aerosol type that you don't see in OMI. Calibration is the easy explanation for the biases, but for the separation by type? Is it the additional data points? I wonder about the models used to move the SSA to 440 nm from 388 nm.
p. 26 Figure 5 caption. Put spaces between “in” and “red; “in” and “blue”
p. 26 Figure 5 caption. Please state the wavelength
p. 30 Figure 9 caption. Please state the wavelength
p. 31 Figure 10 caption. Please state the wavelength
p. 32 Figure 11 caption. Please state the wavelength
p. 34 Figure 13 caption. Please state the wavelength

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ED: Publish subject to minor revisions (review by editor) (21 Sep 2020) by Daniel Perez-Ramirez

AR by Omar Torres on behalf of the Authors (10 Oct 2020) Author's response Manuscript

ED: Publish as is (10 Oct 2020) by Daniel Perez-Ramirez

AR by Omar Torres on behalf of the Authors (20 Oct 2020)

Short summary

TROPOMI measures the quantity of small suspended particles (aerosols). We describe initial results of aerosol measurements using a NASA algorithm that retrieves the UV aerosol index, aerosol optical depth, and single-scattering albedo. An evaluation of derived products using sun-photometer observations shows close agreement. We also use these results to discuss important biomass burning and wildfire events around the world that got the attention of scientists and news media alike.