the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 May 2022
Closure analysis of aerosol-cloud composition in tropical maritime warm convection
Abstract. Cloud droplet composition is a key observable quantity that can aid understanding of how aerosols and clouds interact. As part of the Clouds, Aerosols and Monsoon Processes – Philippines Experiment (CAMP2Ex), three case studies were analyzed involving collocated airborne sampling of relevant clear and cloudy airmasses associated with maritime warm convection. Two of the cases represented a polluted marine background, with signatures of transported East Asian regional pollution, aged over water for several days, while the third case comprised a major smoke transport event from Kalimantan fires.
Sea salt was a dominant component of cloud droplet composition, in spite of fine particulate enhancement from regional anthropogenic sources. Furthermore, the proportion of sea salt was enhanced relative to sulfate in rainwater and may indicate both a propensity for sea salt to aid warm rain production and an increased collection efficiency of large sea salt particles by rain in subsaturated environments. Amongst cases, as precipitation became more significant, so too did the variability in the sea salt to (non-sea salt) sulfate ratio. Across cases, nitrate and ammonium were fractionally greater in cloud water than fine-mode aerosol particles; however, a strong co-variability in cloud water nitrate and sea salt was suggestive of prior uptake of nitrate on large salt particles.
A mass-based closure analysis of non-sea salt sulfate compared the cloud water air-equivalent mass concentration to the concentration of aerosol particles serving as cloud condensation nuclei for droplet activation. While sulfate found in cloud was generally constrained by the sub-cloud aerosol concentration, there was significant intra-cloud variability that was attributed to entrainment – causing evaporation of sulfate containing droplets – and losses due to precipitation. In addition, precipitation tended to promote mesoscale variability in the sub-cloud aerosol through a combination of removal, convective downdrafts, and through dynamically-driven convergence. Physical mechanisms exerted such strong control over the cloud water compositional budget that it was not possible to isolate any signature of chemical production/loss using in-cloud observations. The cloud-free environment surrounding the non-precipitating, smoke case indicated sulfate enhancement compared to convective mixing quantified by a stable gas tracer; however, this was not observed in the cloud water (either through use of ratios or the mass closure) perhaps implying that the warm convective cloud time scale was too short for chemical production to be a leading-order budgetary term. Closure of other species was truncated by incomplete characterization of coarse aerosol (e.g., it was found that only 10-50% of sea salt mass found in cloud was captured during clear air sampling) and unmeasured gas phase abundances affecting closure of semi-volatile aerosol species (e.g., ammonium, nitrate and organic aerosols) and soluble volatile organic compound contributions to total organic carbon in cloud water.
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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.
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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.
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Status: closed
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RC1: 'Comment on egusphere-2022-166', Anonymous Referee #1, 16 Jun 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-166/egusphere-2022-166-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2022-166', Anonymous Referee #2, 03 Jul 2022
This manuscript represents an interesting dataset that covers a broad range of topics, and it does a nice job of demonstrating the complexities of conducting and analysing these types of studies. The breadth of the paper limits the focus that is put on any particular topic, and there is a distinct lack of discussion of the process of nucleation scavenging, despite this being fundamental to everything. Samples of water collected for chemical analysis are all classified as cloudwater (CW). A rainwater fraction (RWF) is used to identify the relative contributions from cloudwater versus rainwater, which I think is a nice approach. For a paper about clouds, I think there are too many thoughts about the discrepancies associated with the NH4+ measurement. Overall, the authors have a very nice dataset, including the information about organic components of the cloudwater, but I would like to see this long paper more focussed on a few issues that can be addressed well. For example, since there is disagreement on NH4+ among some of the measurements, eliminate NH4+ from the discussion and put it in another paper after you have completed your related laboratory investigations.
1. Introduction – There seems to be a lot of discussion about why observations don't work well, but then we are told that it is clear that they are needed. The discussion fails to acknowledge observations that have worked, mostly because of the nature of the clouds and well documented instrumentation.
2. Lines 200-202 – Why were liquid drops “universally assumed”, when you have 2D instrumentation you can use to avoid an assumption?
3. Line 218 – RWF is a ratio. Unless LWC includes RWC, the fraction should be RWF = RWC/(LWC+RWC). Please clarify. Also, here it would be helpful to clearly state that all samples of water are referred to as CW with RWF used to indicate the relative proportion of rainwater in each. In Figure 6, identify samples that are RW in some way. For example, are the samples that appear to have been collected below cloud in Case II actually RW or is there some discrepancy in cloud base?
4. Section 2.5 - How were the blank samples, mentioned on page six, used? What were the detection limits?
5. Section 2.7 and Figure 1 – The implication here is that this represents one cloud. The very sharp and narrow downdraft just past 20 seconds suggests a possible outer edge of the larger cell. Does this time series represent two clouds in different stages?
6. Section 3 – For each case, it would be helpful to have a conceptual 2D cartoon showing the relative proximity of the clear-air profile to the cloud and the wind directions with heights. That is, something similar to Figure 6, but showing the proximity of the clear-air work to the sampled cloud.
7. Line 416 – “PILS SS showed a marked reduction in US”. Was that meant to be “DS”, and reduction relative to what: in the DS intervals, SS:nnSo4= appears to be higher?
8. Lines 472-473 – The statement “A large number of airmass properties that characterize sub-micrometer aerosol” seems a bit odd. Should it be reversed: i.e., “A large number of sub-micrometer aerosol properties that help to characterize the airmass”?
9. Lines 506-507 – With an hour and a half between the stacked legs, should you expect consistency?
10. Lines 520-522 – This does not appear to be true, as increases in nitrate coincide with the spikes in calcium, which you note later in this paragraph in connection with the possible reactions of HNO3 with insoluble (or less soluble) calcium-containing soil molecules. Related - lines 525-529 – Why would insoluble components be responsible for the spikes if they’re insoluble?
11. Lines 584-586 – Why is sulphate a useful candidate for closure, since in-cloud production of sulphate is a dominant factor contributing to global sulphate? Also, if you are to undertake a closure analysis of sulphate, you must consider the fraction of sulphate scavenged by nucleation. It would seem from the many measurements you mention, including size resolved sulphate from the AMS and droplet distributions, that you have the tools to include nucleation scavenging in a reasonable manner.
12. Line 598 – Your statement about the implication of “positive curvature” is interesting, but I would like to see a little more discussion here. It seems reasonable that the wide variation of SO4= at a near constant CO of about 0.135 ppm may be indicative of precipitation scavenging (Case I), but there can be influences affecting SO4= as well as CO. In making your statements in this section, your discussion should consider major losses and sources of CO and SO4= in order to rule out other explanations for the behaviour of the clear-air curves in Cases II and III.
13. Lines 709-611 – I think this statement belongs in section 2.7.
14. Lines 613-622 – It is here that you first distinguish between CW samples collected in cloud and CW samples collected in precipitation in otherwise clear air (“unsaturated precipitation” as you call it, which is might better stated as precipitation in unsaturated air.) RW is subject to some additional processes than CW. As I mention above, the distinction should be shown in Figure 6.
15. Lines 621-622 – I would appreciate a more detailed explanation of the statement that “The singular Case III data point… is perhaps indicative … that … a reference parcel with 100% scavenged fraction is unrealistic, even under undilute conditions, given the competition for water vapor in the highly particle-loaded smoke plume.” What is a reference parcel with 100% scavenged fraction? What does competition for water vapour have to do with the reference parcel?
16. Lines 624-635 – Are the quartiles in SO4=CW/SO4=ML different across Z/Ztop, across RWF and across w/sigmaw after taking into account the uncertainties in the measurements and sampling constraints (e.g., how representative is your SO4=ML of SO4= at cloud base?)
17. Line 635 – By “scavenged” here, do you mean nucleation scavenged?
18. Line 641-642 – There are at least two reasons why I don’t think you can make this statement about nssSO4=:
a. You don't appear have sufficient information to help assess the importance of sulphate production in cloud.
b. You haven't assessed nucleation scavenging at cloud base. If only 50% of the SO4= is scavenged, some aspects of the assessments arrived at from Figures 6-8 could be quite different.
19. Line 642-643 – Four microns seems to be around the cut off for sampling coarse particles from many aircraft, but the statement about “grossly underpredicted” sea salt particles should be either toned down or better supported. You have measurements to give you information on the profiles of coarse particles that can be used to help assess the potential contribution from larger sea salt particles to your cloudwater samples.
20. Line 649 – “as anticipated” – We expect sea salt particles to be entirely incorporated into cloud during nucleation because of their generally larger sizes. We do not expect SO4= particles to always be entirely incorporated (Jensen and Charlson, Tellus, 1984; Leaitch et al., Tellus, 1986). For that reason, it is possible that your SS/SO4= can be higher in the CW than in the PILS samples. You bring up nucleation scavenging occasionally, but you do not try to address it in anyway with your measurements, despite it being a major process impacting your discussions.
21. Line 669 – “susceptible to washout” should be referenced, e.g., Seinfeld and Pandis.
22. Lines 669-670 – “CW SS in unsaturated environments”. Are you proposing to change terminology: i.e., rain becomes cloudwater in unsaturated environments? This complicates reading.
23. Line 676 – Just the 2nd leg, not “The lower (2nd) leg”. It is not lower than 3 or 4.
24. Section 4.3.1 - Consider references to Leaitch et al. (JGR, 1986; https://doi.org/10.1029/JD091iD11p11821) and Hill et al. (JGR, 2007; doi:10.1029/2006JD008002) that discuss measured enhancements in nitrate in cloudwater collected in convective cloud.
25. Line 729 – The Quinn reference appears to be missing.
26. Lines 734-747 – The aim of this paragraph seems to be a reference to justify the lab experiment some of the authors are conducting. Otherwise, it tells us nothing because there are so many uncertainties associated with the NH4+ measurements and so many related processes to consider. This paragraph complicates the paper and I suggest removing it.
27. Line 806 – I think it is reasonably well known that oxalic acid can be unstable, depending on temperature, but your statement that oxalate is not thermodynamically favored on sea salt particles needs a reference. Are you referring to oxalate after reaction of oxalic acid with NaCl?
28. Line 818 – Does this consider the AMS-CE and CVI collection efficiencies as well as size constraints on CW sampling?
29. Lines 831-832 – This is a good example of something that could stand to have more focus and detail. There are many indications that OA can be distributed more broadly across the size spectrum than SO4=.
30. Lines 838-841 – Interesting, but the analysis is again insufficient.
31. Lines 904-905 – about 25% of the total carbon was measured in the CW samples.Citation: https://doi.org/10.5194/egusphere-2022-166-RC2 -
AC1: 'Comment on egusphere-2022-166', Ewan Crosbie, 11 Aug 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-166/egusphere-2022-166-AC1-supplement.pdf
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-166', Anonymous Referee #1, 16 Jun 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-166/egusphere-2022-166-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2022-166', Anonymous Referee #2, 03 Jul 2022
This manuscript represents an interesting dataset that covers a broad range of topics, and it does a nice job of demonstrating the complexities of conducting and analysing these types of studies. The breadth of the paper limits the focus that is put on any particular topic, and there is a distinct lack of discussion of the process of nucleation scavenging, despite this being fundamental to everything. Samples of water collected for chemical analysis are all classified as cloudwater (CW). A rainwater fraction (RWF) is used to identify the relative contributions from cloudwater versus rainwater, which I think is a nice approach. For a paper about clouds, I think there are too many thoughts about the discrepancies associated with the NH4+ measurement. Overall, the authors have a very nice dataset, including the information about organic components of the cloudwater, but I would like to see this long paper more focussed on a few issues that can be addressed well. For example, since there is disagreement on NH4+ among some of the measurements, eliminate NH4+ from the discussion and put it in another paper after you have completed your related laboratory investigations.
1. Introduction – There seems to be a lot of discussion about why observations don't work well, but then we are told that it is clear that they are needed. The discussion fails to acknowledge observations that have worked, mostly because of the nature of the clouds and well documented instrumentation.
2. Lines 200-202 – Why were liquid drops “universally assumed”, when you have 2D instrumentation you can use to avoid an assumption?
3. Line 218 – RWF is a ratio. Unless LWC includes RWC, the fraction should be RWF = RWC/(LWC+RWC). Please clarify. Also, here it would be helpful to clearly state that all samples of water are referred to as CW with RWF used to indicate the relative proportion of rainwater in each. In Figure 6, identify samples that are RW in some way. For example, are the samples that appear to have been collected below cloud in Case II actually RW or is there some discrepancy in cloud base?
4. Section 2.5 - How were the blank samples, mentioned on page six, used? What were the detection limits?
5. Section 2.7 and Figure 1 – The implication here is that this represents one cloud. The very sharp and narrow downdraft just past 20 seconds suggests a possible outer edge of the larger cell. Does this time series represent two clouds in different stages?
6. Section 3 – For each case, it would be helpful to have a conceptual 2D cartoon showing the relative proximity of the clear-air profile to the cloud and the wind directions with heights. That is, something similar to Figure 6, but showing the proximity of the clear-air work to the sampled cloud.
7. Line 416 – “PILS SS showed a marked reduction in US”. Was that meant to be “DS”, and reduction relative to what: in the DS intervals, SS:nnSo4= appears to be higher?
8. Lines 472-473 – The statement “A large number of airmass properties that characterize sub-micrometer aerosol” seems a bit odd. Should it be reversed: i.e., “A large number of sub-micrometer aerosol properties that help to characterize the airmass”?
9. Lines 506-507 – With an hour and a half between the stacked legs, should you expect consistency?
10. Lines 520-522 – This does not appear to be true, as increases in nitrate coincide with the spikes in calcium, which you note later in this paragraph in connection with the possible reactions of HNO3 with insoluble (or less soluble) calcium-containing soil molecules. Related - lines 525-529 – Why would insoluble components be responsible for the spikes if they’re insoluble?
11. Lines 584-586 – Why is sulphate a useful candidate for closure, since in-cloud production of sulphate is a dominant factor contributing to global sulphate? Also, if you are to undertake a closure analysis of sulphate, you must consider the fraction of sulphate scavenged by nucleation. It would seem from the many measurements you mention, including size resolved sulphate from the AMS and droplet distributions, that you have the tools to include nucleation scavenging in a reasonable manner.
12. Line 598 – Your statement about the implication of “positive curvature” is interesting, but I would like to see a little more discussion here. It seems reasonable that the wide variation of SO4= at a near constant CO of about 0.135 ppm may be indicative of precipitation scavenging (Case I), but there can be influences affecting SO4= as well as CO. In making your statements in this section, your discussion should consider major losses and sources of CO and SO4= in order to rule out other explanations for the behaviour of the clear-air curves in Cases II and III.
13. Lines 709-611 – I think this statement belongs in section 2.7.
14. Lines 613-622 – It is here that you first distinguish between CW samples collected in cloud and CW samples collected in precipitation in otherwise clear air (“unsaturated precipitation” as you call it, which is might better stated as precipitation in unsaturated air.) RW is subject to some additional processes than CW. As I mention above, the distinction should be shown in Figure 6.
15. Lines 621-622 – I would appreciate a more detailed explanation of the statement that “The singular Case III data point… is perhaps indicative … that … a reference parcel with 100% scavenged fraction is unrealistic, even under undilute conditions, given the competition for water vapor in the highly particle-loaded smoke plume.” What is a reference parcel with 100% scavenged fraction? What does competition for water vapour have to do with the reference parcel?
16. Lines 624-635 – Are the quartiles in SO4=CW/SO4=ML different across Z/Ztop, across RWF and across w/sigmaw after taking into account the uncertainties in the measurements and sampling constraints (e.g., how representative is your SO4=ML of SO4= at cloud base?)
17. Line 635 – By “scavenged” here, do you mean nucleation scavenged?
18. Line 641-642 – There are at least two reasons why I don’t think you can make this statement about nssSO4=:
a. You don't appear have sufficient information to help assess the importance of sulphate production in cloud.
b. You haven't assessed nucleation scavenging at cloud base. If only 50% of the SO4= is scavenged, some aspects of the assessments arrived at from Figures 6-8 could be quite different.
19. Line 642-643 – Four microns seems to be around the cut off for sampling coarse particles from many aircraft, but the statement about “grossly underpredicted” sea salt particles should be either toned down or better supported. You have measurements to give you information on the profiles of coarse particles that can be used to help assess the potential contribution from larger sea salt particles to your cloudwater samples.
20. Line 649 – “as anticipated” – We expect sea salt particles to be entirely incorporated into cloud during nucleation because of their generally larger sizes. We do not expect SO4= particles to always be entirely incorporated (Jensen and Charlson, Tellus, 1984; Leaitch et al., Tellus, 1986). For that reason, it is possible that your SS/SO4= can be higher in the CW than in the PILS samples. You bring up nucleation scavenging occasionally, but you do not try to address it in anyway with your measurements, despite it being a major process impacting your discussions.
21. Line 669 – “susceptible to washout” should be referenced, e.g., Seinfeld and Pandis.
22. Lines 669-670 – “CW SS in unsaturated environments”. Are you proposing to change terminology: i.e., rain becomes cloudwater in unsaturated environments? This complicates reading.
23. Line 676 – Just the 2nd leg, not “The lower (2nd) leg”. It is not lower than 3 or 4.
24. Section 4.3.1 - Consider references to Leaitch et al. (JGR, 1986; https://doi.org/10.1029/JD091iD11p11821) and Hill et al. (JGR, 2007; doi:10.1029/2006JD008002) that discuss measured enhancements in nitrate in cloudwater collected in convective cloud.
25. Line 729 – The Quinn reference appears to be missing.
26. Lines 734-747 – The aim of this paragraph seems to be a reference to justify the lab experiment some of the authors are conducting. Otherwise, it tells us nothing because there are so many uncertainties associated with the NH4+ measurements and so many related processes to consider. This paragraph complicates the paper and I suggest removing it.
27. Line 806 – I think it is reasonably well known that oxalic acid can be unstable, depending on temperature, but your statement that oxalate is not thermodynamically favored on sea salt particles needs a reference. Are you referring to oxalate after reaction of oxalic acid with NaCl?
28. Line 818 – Does this consider the AMS-CE and CVI collection efficiencies as well as size constraints on CW sampling?
29. Lines 831-832 – This is a good example of something that could stand to have more focus and detail. There are many indications that OA can be distributed more broadly across the size spectrum than SO4=.
30. Lines 838-841 – Interesting, but the analysis is again insufficient.
31. Lines 904-905 – about 25% of the total carbon was measured in the CW samples.Citation: https://doi.org/10.5194/egusphere-2022-166-RC2 -
AC1: 'Comment on egusphere-2022-166', Ewan Crosbie, 11 Aug 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-166/egusphere-2022-166-AC1-supplement.pdf
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Ewan Crosbie
Luke D. Ziemba
Michael A. Shook
Claire E. Robinson
Edward L. Winstead
K. Lee Thornhill
Rachel A. Braun
Alexander B. MacDonald
Connor Stahl
Armin Sorooshian
Susan C. van den Heever
Joshua P. DiGangi
Glenn S. Diskin
Sarah Woods
Paola Bañaga
Matthew D. Brown
Francesca Gallo
Miguel Ricardo A. Hilario
Carolyn E. Jordan
Gabrielle R. Leung
Richard H. Moore
Kevin J. Sanchez
Taylor J. Shingler
Elizabeth B. Wiggins
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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