the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Mar 2024
Drivers of Droplet Formation in East Mediterranean Orographic Clouds
Abstract. The purpose of this study is to understand the drivers of cloud droplet formation in orographic clouds. We used a combination of modeling, in-situ and remote sensing measurements at the high-altitude Helmos Hellenic Atmospheric Aerosol and Climate Change station ((HAC)2), which is located at the top of Mt. Helmos (1314 metres above sea level), Greece during the Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISTHO) campaign in Fall 2021 (https://calishto.panacea-ri.gr/) to examine the origins of the aerosols (i.e., local aerosol from the Planetary Boundary Layer (PBL), or long-range transported aerosol from the Free Tropospheric Layer (FTL) contributing to the Cloud Condensation Nuclei (CCN), their characteristics (hygroscopicity, size distribution and mixing state), as well as the vertical velocities distributions and resulting supersaturations.
We found that the characteristics of the PBL aerosol were considerably different from FTL aerosol and use the aerosol particle number and equivalent mass concentration of the black carbon (eBC) in order to determine when the (HAC)2 was within the FTL or PBL based on timeseries of the height of the PBL. During the (HAC)2 cloud events we sample a mixture of interstitial aerosol and droplet residues, which we characterize using a new approach that utilizes the in-situ droplet measurements to determine time periods where the aerosol sample is purely interstitial. From the dataset we determine the properties (size distribution and hygroscopicity) of the pre-cloud, activated and interstitial aerosol. The hygroscopicity of activated aerosol is found to be higher than that of the interstitial or pre-cloud aerosol. A series of closure studies with the droplet parameterization shows that cloud droplet concentration (Nd) and supersaturation can be predicted to within 25 % of observations when the aerosol size distributions correspond to pre-cloud conditions. Analysis of the characteristic supersaturation of each aerosol population indicates that droplet formation in clouds is aerosol-limited when formed in FTL airmasses – hence droplet formation is driven by aerosol variations, while clouds formed in the PBL tend to be velocity limited and droplet variations are driven by fluctuations in vertical velocity. Given that the cloud dynamics do not vary significantly between airmasses, the variation in aerosol concentration and type is mostly responsible for these shifts in cloud microphysical state and sensitivity to aerosol. With these insights, remote sensing of cloud droplets in such clouds can be used to infer either CCN spectra (when in the FTL) or vertical velocity (when in the PBL). In conclusion, we show that a coordinated measurement of aerosol and cloud properties, together with the novel analysis approaches presented here allow for the determination of the drivers of droplet formation in orographic clouds and their sensitivity to aerosol and vertical velocity variations.
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Notice on discussion status
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.
- Preprint
(1593 KB) - Metadata XML
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Supplement
(782 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on Foskinis et al 2024', Anonymous Referee #1, 18 Apr 2024
- AC1: 'Responses to Reviewer 1', Athanasios Nenes, 25 May 2024
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RC2: 'Comment on egusphere-2024-490', Anonymous Referee #2, 24 Apr 2024
The manuscript deals with aerosol and cloud droplet microphysics determined at a mountain site in the Peloponnesus (Greece). This is part of a series of publications dedicated to the CALISTHO campaign. Aerosol activation in orographic clouds certainly is not a new topic, but CALISTHO convincingly provides a demonstration of what can be achieved by employing state-of-the-art instrumentation including wind lidar observations for assessing vertical velocity regimes. The paper provides a comprehensive set of relevant new information about emerging ground-based observations targeting aerosol-cloud interactions. The manuscript is generally well written; however, Section 3.4 deserves more focus as it contains some obscure arguments.
Specific comments:
Section 2.3.1: When determining the hygroscopicity kappa value starting from the chemical composition, what factor has been applied to the organic mass fraction?
Lines 301 – 303: “we identified three prevailing wind directions, that correspond to the local transport patterns (Figure S2f) from 90°, 180° and 320° N, where the NTotal obtains its maximum values (~3300 cm-3)”. It is not clear whether the maximum values for NTotal are found only at the 320° direction or all the three selected wind directions.
Line 306: It is not really clear in Figure S2 what are the wind directions tracing an air flow passing over mountain peaks. In addition, with wind directions from 330 – 360°, the PBL height is large and vertical velocity as well (Fig S2b) which is the other way around with respect to what stated in the text.
Lines 308 – 310: the references to the panels in Fig. S2 (panels b, c, d) in the text do not match with what shown in Fig. S2 in the supplementary. Are the Authors referring to Fig S3 instead?
Fig. 2. Panel b: the PBL / FTL mask is not clear; for instance, in days 11-14 Nov the PBLH is lower than the (HAC)2 elevation but this period is classified green (PBL); the same occurs on 20 – 23 Nov. Panel c: In the wind direction plot, please use a palette with colours changing with continuity between 360° and 0°.
Fig. 3a: the y axis of the figure on the left cannot report simply concentrations in cm-3 but must be in dN/dlogDp units. The specific period of the campaign providing this subset of data should be reported. Same for Fig. 5.
About the “virtual cutoff”. Clearly, a (physical) PM10 cutoff cannot provide a net separation between interstitial aerosols and cloud droplets when Deff is small, which in fact results into too small values of the difference [pre-cloud]-[in-cloud] concentrations with respect to CDNC (Figure 3b). The interesting analysis performed by the Authors leads to the conclusion that residual (evaporated) droplets are absent in the PM10 inlet when Deff is larger than 13.5 µm (line 363 – 364: “Thus, we confirm that this threshold is consistent with allowing only interstitial to pass through the inlet”). This would imply that measured interstitial aerosol concentrations are reliable only for cased with Deff > 13.5 µm (which represent a limited subset of the full in-cloud measurement period, Fig. S4). However, the following analysis (Fig. 5) is carried out on an “interstitial aerosols dataset derived after removing from the in-cloud dataset the data were the Deff was exceeding the threshold of 13.5 μm” (lines 431 - 433). However, with Deff < 13.5 µm, the interstitial dataset should be contaminated from the concentrations of droplet residuals. Please, explain.
Section 3.4: if clouds are observed only at the (HAC)2 site and not at VL, why the values in the y axes differ between the two graphs in Fig. 6? Most noticeably, in the FTL conditions, Deff is larger than 13.5 µm and the PM10 inlet at (HAC)2 site should sample interstitial aerosols free of cloud residuals, so why the closure is worse in this case? Please, clarify.
Citation: https://doi.org/10.5194/egusphere-2024-490-RC2 - AC2: 'Responses to Reviewer 2', Athanasios Nenes, 25 May 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on Foskinis et al 2024', Anonymous Referee #1, 18 Apr 2024
- AC1: 'Responses to Reviewer 1', Athanasios Nenes, 25 May 2024
-
RC2: 'Comment on egusphere-2024-490', Anonymous Referee #2, 24 Apr 2024
The manuscript deals with aerosol and cloud droplet microphysics determined at a mountain site in the Peloponnesus (Greece). This is part of a series of publications dedicated to the CALISTHO campaign. Aerosol activation in orographic clouds certainly is not a new topic, but CALISTHO convincingly provides a demonstration of what can be achieved by employing state-of-the-art instrumentation including wind lidar observations for assessing vertical velocity regimes. The paper provides a comprehensive set of relevant new information about emerging ground-based observations targeting aerosol-cloud interactions. The manuscript is generally well written; however, Section 3.4 deserves more focus as it contains some obscure arguments.
Specific comments:
Section 2.3.1: When determining the hygroscopicity kappa value starting from the chemical composition, what factor has been applied to the organic mass fraction?
Lines 301 – 303: “we identified three prevailing wind directions, that correspond to the local transport patterns (Figure S2f) from 90°, 180° and 320° N, where the NTotal obtains its maximum values (~3300 cm-3)”. It is not clear whether the maximum values for NTotal are found only at the 320° direction or all the three selected wind directions.
Line 306: It is not really clear in Figure S2 what are the wind directions tracing an air flow passing over mountain peaks. In addition, with wind directions from 330 – 360°, the PBL height is large and vertical velocity as well (Fig S2b) which is the other way around with respect to what stated in the text.
Lines 308 – 310: the references to the panels in Fig. S2 (panels b, c, d) in the text do not match with what shown in Fig. S2 in the supplementary. Are the Authors referring to Fig S3 instead?
Fig. 2. Panel b: the PBL / FTL mask is not clear; for instance, in days 11-14 Nov the PBLH is lower than the (HAC)2 elevation but this period is classified green (PBL); the same occurs on 20 – 23 Nov. Panel c: In the wind direction plot, please use a palette with colours changing with continuity between 360° and 0°.
Fig. 3a: the y axis of the figure on the left cannot report simply concentrations in cm-3 but must be in dN/dlogDp units. The specific period of the campaign providing this subset of data should be reported. Same for Fig. 5.
About the “virtual cutoff”. Clearly, a (physical) PM10 cutoff cannot provide a net separation between interstitial aerosols and cloud droplets when Deff is small, which in fact results into too small values of the difference [pre-cloud]-[in-cloud] concentrations with respect to CDNC (Figure 3b). The interesting analysis performed by the Authors leads to the conclusion that residual (evaporated) droplets are absent in the PM10 inlet when Deff is larger than 13.5 µm (line 363 – 364: “Thus, we confirm that this threshold is consistent with allowing only interstitial to pass through the inlet”). This would imply that measured interstitial aerosol concentrations are reliable only for cased with Deff > 13.5 µm (which represent a limited subset of the full in-cloud measurement period, Fig. S4). However, the following analysis (Fig. 5) is carried out on an “interstitial aerosols dataset derived after removing from the in-cloud dataset the data were the Deff was exceeding the threshold of 13.5 μm” (lines 431 - 433). However, with Deff < 13.5 µm, the interstitial dataset should be contaminated from the concentrations of droplet residuals. Please, explain.
Section 3.4: if clouds are observed only at the (HAC)2 site and not at VL, why the values in the y axes differ between the two graphs in Fig. 6? Most noticeably, in the FTL conditions, Deff is larger than 13.5 µm and the PM10 inlet at (HAC)2 site should sample interstitial aerosols free of cloud residuals, so why the closure is worse in this case? Please, clarify.
Citation: https://doi.org/10.5194/egusphere-2024-490-RC2 - AC2: 'Responses to Reviewer 2', Athanasios Nenes, 25 May 2024
Peer review completion
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Cited
2 citations as recorded by crossref.
Romanos Foskinis
Ghislain Motos
Maria I. Gini
Olga Zografou
Kunfeng Gao
Stergios Vratolis
Konstantinos Granakis
Ville Vakkari
Kalliopi Violaki
Andreas Aktypis
Christos Kaltsonoudis
Zongbo Shi
Mika Komppula
Spyros N. Pandis
Konstantinos Eleftheriadis
Alexandros Papayannis
Athanasios Nenes
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1593 KB) - Metadata XML
-
Supplement
(782 KB) - BibTeX
- EndNote
- Final revised paper