Biomass burning events measured by lidars in EARLINET –  Part 1: Data analysis methodology

Adam, Mariana; Nicolae, Doina; Stachlewska, Iwona S.; Papayannis, Alexandros; Balis, Dimitris

doi:https://doi.org/10.5194/acp-20-13905-2020

Articles | Volume 20, issue 22

https://doi.org/10.5194/acp-20-13905-2020

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

Special issue:

EARLINET aerosol profiling: contributions to atmospheric and...

https://doi.org/10.5194/acp-20-13905-2020

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

Articles | Volume 20, issue 22

Research article

|

18 Nov 2020

Research article |

| 18 Nov 2020

Biomass burning events measured by lidars in EARLINET – Part 1: Data analysis methodology

Mariana Adam, Doina Nicolae, Iwona S. Stachlewska, Alexandros Papayannis, and Dimitris Balis

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Interactive discussion

Status: closed

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

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RC1: 'Review', Anonymous Referee #2, 06 Jun 2020
- AC1: 'Answers reviewer 2', Mariana Adam, 28 Aug 2020
RC2: 'Review', Anonymous Referee #3, 22 Jul 2020
- AC2: 'Answers reviewer 3', Mariana Adam, 28 Aug 2020

Peer-review completion

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

AR by Mariana Adam on behalf of the Authors (31 Aug 2020) Manuscript

ED: Referee Nomination & Report Request started (14 Sep 2020) by Eduardo Landulfo

RR by Anonymous Referee #3 (23 Sep 2020)

Suggestions for revision or reasons for rejection

I acknowledge that the authors answered most of the questions raised in the review process.
As you can see, most of the remainig issues are "minor". However, I really doubt your error spans on the intensive properties, see my remark below. Please come up with realistic values!

P 12, L 32: is it higher altitude or higher value?
P 15, L11 “h” in Athens missing
P 16, L 14 ff: I still think that the error of the IP are unrealistically small. For example, the authors state BEA(355 / 532) = 1.82+-0.0001
Let us assume that beta_aer at 532nm had zero error and beta_aer at 355nm had only 1% of error (and I think the authors agree that this is an absolute unrealistic low error estimation) this would translate into values of BAE between 1.7955 and 1.8445
As this is mainly a paper on the method the authors really should come up with a realistic error estimation.
P16, L 17 ff: you are using E NE etc for East, North East which is fine for me. But as you changed it elsewhere in the manuscript you may change it here
P16, L 22 please change: [the smallest particles] “are the most … backscattering” into “show the highest backscatter coefficient”
P19 L3-4: again SE Europe and NE Europe (which is fine for me but not consistent)
P21, L27 LRT event “mixed cases” (and the discussion before). Strictly speaking you had to show somehow that you really compare in your layers the mixture of 2 different BB events (but no additional source of aerosol!) As this is probably difficult to prove I recommend to be more cautious in your wording.
P22 L1 CE Europe is “Central East Europe”?
P22 L22 “with uncertainty analysis” cancel these 3 words? You took the data from Earlinet and rejected wrong entries. Which uncertainty analysis did you do beyond this?
P22, L25, Plural? Other possible sources (?)
Fig 9, sub-plot PDR: I don’t see the data
Fig 12: do the sub-plots belong to the same data set? I am wondering because in the oEUAF case in sub-plot LR532 vs LR355 the standard deviation in LR532 is from approx. 50 to 80 sr, while in sub-plot EAE vs LR532 the standard deviation is from 20 to 80 sr

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p.4 L 10: I really recommend to cancel the sentence “Our approach …” You don’t need it. You describe, how you define a layer. Other authors may have done slightly differently. Honestly, I did not check all your quotes, but Veselovskii et al. 2018 did not describe, how they defined their layers. Even if they did you could only draw the conclusion that your layer detection is in line with Veselovskii if you had taken their beta profiles and derive layers with your code which are then almost identical to the region in which Veselovskii present their Angstroem exponents in their figure 8.

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ED: Publish subject to technical corrections (23 Sep 2020) by Eduardo Landulfo

AR by Mariana Adam on behalf of the Authors (01 Oct 2020) Author's response Manuscript

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Short summary

Biomass burning events measured by EARLINET are analysed using intensive parameters. The pollution layers are labelled smoke layers if fires were found along the air-mass back trajectory. The number of contributing fires to the smoke measurements is quantified. It is shown that most of the time we measure mixed smoke. The methodology provides three research directions: fires measured by several stations, long-range transport from N. America, and an analysis function of continental sources.