Articles | Volume 23, issue 15
https://doi.org/10.5194/acp-23-8959-2023
© Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.
Influence of natural and anthropogenic aerosols on cloud base droplet size distributions in clouds over the South China Sea and West Pacific
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- Final revised paper (published on 11 Aug 2023)
- Preprint (discussion started on 20 Jan 2023)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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- RC1: 'Comment on egusphere-2022-1429', Anonymous Referee #1, 16 Feb 2023
- RC2: 'Comment on egusphere-2022-1429', James Hudson, 26 Mar 2023
- AC1: 'Response to RCs on egusphere-2022-1429', Rose Miller, 02 Apr 2023
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Rose Miller on behalf of the Authors (02 Apr 2023)
Author's response
Author's tracked changes
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ED: Referee Nomination & Report Request started (09 May 2023) by Zhanqing Li
RR by Fan Mei (16 May 2023)
RR by James Hudson (22 May 2023)
ED: Publish subject to minor revisions (review by editor) (30 May 2023) by Zhanqing Li
AR by Rose Miller on behalf of the Authors (20 Jun 2023)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (22 Jun 2023) by Zhanqing Li
AR by Rose Miller on behalf of the Authors (05 Jul 2023)
Manuscript
General comments:
This paper discussed the different aerosol sources' influence on cloud base droplet size distribution using a comprehensive dataset from P3 airplane. The data is extremely valuable for improving the current understanding of the aerosol-cloud interaction, especially over the South China sea and the western pacific. The paper is well written and made an excellent measurement report. However, the data analysis did not use the full potential of such a rich dataset nor provide new insight into the aerosol-cloud interaction. Thus, if authors are willing to explore the linkage between the meteorological and climate features in the southeast Asia region and the observation. This paper can contribute more as a research article. Otherwise, it is in good shape as a measurement report after addressing the comments below.
Specific comments:
Abstract: "three primary sources influenced the aerosol chemical composition: marine (ocean source), industrial (Southeast Asia, Manila, and cargo and tanker ship emissions), and biomass burning (Borneo and Indonesia)." The industrial is misleading. The paper discussed ship emissions.
Introduction: The current result is consistent with the previous studies the author quoted in the introduction. "The impact of anthropogenic aerosols such as sulfate, nitrate, and BC has been a main topic of interest for many years as they lead to an increase of CCN that increases the cloud droplet number concentration (Nd) and decreases the effective radius (re) of the droplets, producing more reflective clouds for the same liquid water path.
For example, Radke et al., (1989) observed an increase in total cloud droplet concentrations, but a decrease in cloud droplet sizes in clouds over shipping lanes. Cloud droplet number has also been reported to increase with aerosol loading over the East China Sea (Bennartz et al., 2011)." It is more scientifically significant if the authors can further explore the current results.
Page 6, lines 121-129. How are those meteorological and climate features related to the aerosol-cloud interaction? It will be very insightful to make the linkage.
Page 8, section 2.1. How many flight hours or data points were collected in each category? What criteria do you use to characterize the influence of each aerosol source? Hysplit trajectory? Aerosol concentration? or chemical loading? Or combination?
Page 11, line 203. Please define "nearest", as one hour apart or 10 hours apart? Will that affect the distribution in figure 3?
Page 13, section 2.5. How does this hysplit data link to three aerosol sources?
Figure 4, line 246-251. It is hard to separate the thick and dashed lines in the figure. Maybe use a different color for the altitude < 466 or >466? Maybe also use a larger ring size.
Line 256. AMS has a 30-second resolution. Why do you exclude anything shorter than 10 mins?
Line 261. How does the MBL passes related to the cloud base passes? At the same region? Altitude/longitude boundaries? Please clarify. In addition, here used 1416 passes and later, 1416 seconds were used. Please correct. For 112 MBL passes, how long does each pass last?
Line 305. I am confused about the procedure for determining the suspected source regions. Please clarify. How many backward trajectories do you run for each pass? Why choose 100 hours? How do you separate the long-term transport influence from regional influence with 100-hour trajectories?
Table 1. Please correct. Number of passes or seconds? Please consider adding information about linking each MBL pass with cloud passes, such as the latitude range when sampling. For example, if MBL passes took 490 mins and their corresponding cloud passes only 747 seconds (about 12.5 mins). Does the result meaningfully capture the influence? Please explain.
Figs 5 and 7 provide similar info. Please explain the significant scientific contributions for including both or move one to a supplemental document.
Page 23, section 5.1. HSRL and RSP were discussed here but not included in the Methodology section like FCDP. Please provide more info about the operation.
Line 398-400. What is the median updraft for the different aerosol-influenced clouds? Please consider re-characterize the cloud category to link them with the aerosol category.