the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Influence of natural and anthropogenic aerosol on cloud base droplet size distributions in clouds over the South China Sea and Western Pacific
Abstract. Cumulus clouds are common over maritime regions. They are important regulators of the global radiative energy budget and global hydrologic cycle, and a key contributor to the uncertainty in anthropogenic climate change projections due to uncertainty in aerosol-cloud interactions. These interactions are regionally specific owing to their strong influences on aerosol sources and meteorology. Here, our analysis focuses on the statistical properties of marine boundary layer (MBL) aerosol chemistry and the relationships of MBL aerosol to cumulus cloud properties just above cloud base as sampled in 2019 during the NASA Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex). The aerosol and clouds were sampled by instruments on the NASA P-3 aircraft over three distinct maritime regions around the Philippines: the West Pacific, the South China Sea, and the Sulu Sea.
Our analysis show 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 marine aerosol chemical composition had low values of all sampled chemical signatures, specifically median values of 2.3 µg/m3 of organics (ORG), 6.1 µg/m3 of SO4, 0.1 µg/m3 of NO3, 1.4 µg/m3 of NH4, 0.04 µg/m3 of Cl, and 0.0074 µg/m3 of refractory black carbon (BC). Chemical signatures of the other two aerosol source regions were: industrial, with elevated SO4 having a median value of 6.1 µg/m3 and biomass burning, with elevated median concentrations of ORG 21.2 µg/m3 and BC 0.1351 µg/m3. The industrial component was primarily from ship emissions based on chemical signatures. The ship emissions were sampled within 60 km of ships and within projected ship plumes. Normalized cloud-droplet size distributions in clouds sampled near the MBL passes of the P-3 showed that clouds impacted by industrial and biomass burning contained higher concentrations of cloud droplets, by as much as 1.5 orders of magnitude for sizes with diameters < 13 µm compared to marine clouds, while at size ranges between 13.0–34.5 µm the median concentrations of cloud droplets in all aerosol categories were nearly an order of magnitude less than the marine category. In the droplet size bins centered at diameters > 34.5 µm concentrations were equal to, or slightly exceeded, the concentrations of the marine clouds. These analyses show that anthropogenic aerosol generated from industrial and biomass burning sources significantly influence cloud base microphysical structure in the Philippine region enhancing the small droplet concentration and reducing the concentration of mid-sized droplets.
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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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Preprint
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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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Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-1429', Anonymous Referee #1, 16 Feb 2023
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.
Â
Specific comments:
Â
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.
Â
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.
Â
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.
Â
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.
Â
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?
Â
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?
Â
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.
Â
Line 256. AMS has a 30-second resolution. Why do you exclude anything shorter than 10 mins?
Â
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?
Â
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?
Â
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.
Â
Â
Figs 5 and 7 provide similar info. Please explain the significant scientific contributions for including both or move one to a supplemental document.
Â
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.
Â
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.Â
Citation: https://doi.org/10.5194/egusphere-2022-1429-RC1 -
RC2: 'Comment on egusphere-2022-1429', James Hudson, 26 Mar 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1429/egusphere-2022-1429-RC2-supplement.pdf
- AC1: 'Response to RCs on egusphere-2022-1429', Rose Miller, 02 Apr 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-1429', Anonymous Referee #1, 16 Feb 2023
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.
Â
Specific comments:
Â
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.
Â
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.
Â
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.
Â
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.
Â
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?
Â
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?
Â
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.
Â
Line 256. AMS has a 30-second resolution. Why do you exclude anything shorter than 10 mins?
Â
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?
Â
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?
Â
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.
Â
Â
Figs 5 and 7 provide similar info. Please explain the significant scientific contributions for including both or move one to a supplemental document.
Â
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.
Â
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.Â
Citation: https://doi.org/10.5194/egusphere-2022-1429-RC1 -
RC2: 'Comment on egusphere-2022-1429', James Hudson, 26 Mar 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1429/egusphere-2022-1429-RC2-supplement.pdf
- AC1: 'Response to RCs on egusphere-2022-1429', Rose Miller, 02 Apr 2023
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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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