the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 May 2023
Overview and statistical analysis of boundary layer clouds and precipitation over the western North-Atlantic Ocean
Christiane Voigt
Bruce E. Anderson
Gao Chen
Ewan C. Crosbie
Richard A. Ferrare
Valerian Hahn
Johnathan W. Hair
Stefan Kaufmann
Richard H. Moore
David Painemal
Claire E. Robinson
Kevin J. Sanchez
Amy J. Scarino
Taylor J. Shingler
Michael A. Shook
Kenneth L. Thornhill
Edward L. Winstead
Luke D. Ziemba
Armin Sorooshian
Abstract. Due to their fast evolution and large variability, the accurate representation of boundary layer clouds in current climate models remains a challenge. One of the regions with large intermodel spread of the Coupled Model Intercomparison Project Phase 6 ensemble is the western North-Atlantic Ocean. Here, statistically representative in-situ measurements can help to develop and constrain the parameterization of clouds in global models. To this end, we performed comprehensive measurements of boundary layer clouds, aerosol, trace gases, and radiation in the western North-Atlantic Ocean during the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. 174 research flights with 574 flight hours for cloud and precipitation measurements were performed with the HU-25 Falcon during three winter (February–March 2020, January–April 2021, and November 2021–March 2022) and three summer seasons (August–September 2020, May–June 2021, and May–June 2022). Here we present a statistical evaluation of 17209 individual cloud events probed by the Fast Cloud Droplet Probe and the Two-Dimensional Stereo cloud probe during 155 research flights in a representative and repetitive flight strategy allowing for robust statistical data analyses. We show that the vertical profiles of distributions of the liquid water content and the cloud droplet effective diameter (ED) increase with altitude in the marine boundary layer. Due to higher updraft speeds, higher cloud droplet number concentrations (Nliquid) were measured in winter compared to summer despite lower cloud condensation nuclei abundance. Flight cloud cover derived from statistical analysis of in-situ data is reduced in summer and shows large variability. This seasonal contrast in cloud coverage is consistent with a dominance of a synoptic pattern in winter that favors conditions for the formation of stratiform clouds in the western edge of cyclones (post-cyclonic). In contrast, a dominant summer anticyclone is concomitant with the occurrence of shallow cumulus clouds and lower cloud coverage. The evaluation of boundary layer clouds and precipitation in the Nliquid-ED phase space sheds light on liquid, mixed-phase, and ice cloud properties and helps to understand their formation. Ice and liquid precipitation, often masked in cloud statistics by high abundance of liquid clouds, is often observed throughout the cloud. The ACTIVATE in-situ cloud measurements provide a wealth of cloud information useful for assessing airborne and satellite remote sensing product, for global climate and weather model evaluations, and for dedicated process studies that address precipitation and aerosol-cloud interactions.
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Simon Kirschler et al.
Interactive discussion
Status: closed
- RC1: 'Comment on egusphere-2023-898', Anonymous Referee #1, 29 May 2023
-
RC2: 'Comment on egusphere-2023-898', Anonymous Referee #2, 15 Jun 2023
Review of “Overview and statistical analysis of boundary layer clouds and precipitation over the western North-Atlantic Ocean” by Kirschler et al., for EGUsphere
General Comments
This manuscript uses ACTIVATE data, which spanned 3 summer and 3 winter seasons, that sampled over 17,000 cloud events using the FCDP and 2D-S in-situ probes. The authors found, consistent with many other previous studies, that both LWC and cloud droplet effective diameter increase with altitude inside clouds. Higher updraft speed in winter boundary layer clouds explains higher cloud droplet number concentrations despite lower CCN. A seasonal contrast in cloud type and coverage is noted: inter clouds are typically stratocumulus, aided by passing synoptic-scale low pressure/frontal systems, whereas summer clouds are more likely to be open cell cumulus. The strength of this paper lies in the thorough overview of the vast quantity of in-situ measurements of boundary layer clouds, whether liquid, mixed-phase or ice clouds, and quantifying their relative occurrence through the entire 3-year dataset.
This manuscript is very well written, easy to follow along, and comes to accurate and valuable conclusions that will be useful to the broader scientific community looking to investigate cloud properties in this region of the globe across many applications (LES and climate modeling, meteorological influences, etc.). The only area of the manuscript that, in my opinion, needs improvement is in the introduction/literature review: there were many broad-reaching statements that need to be supported (or could be better supported) by recent studies. Specific comments are noted below. I also noted a few areas later in the paper where the results of this work could be directly compared, namely with other similar suborbital campaigns. I think the authors should consider a follow-on study quantifying the role of meteorological influences to the observed cloud properties, as the manuscript makes several references explaining why observed cloud properties occur but only provides temperature data for context. I think this manuscript is very clean in its current form and adding such analysis – in my opinion – is better off as its own separate analysis and manuscript.
Overall, this manuscript merits publication in EGUsphere. The majority of my comments are “minor” in nature, and the authors have a high degree of flexibility in how they choose to address them.
Specific Comments
L25-38 (Paragraph 1): This paragraph flows well, but several of the statements need additional references, especially more recent references that have addressed or provided new evidence for some of the statements.
L29: You can just say “Weather systems”, drop “Meteorological”.
L30: “... can induce ice nucleation or the formation of precipitation” reference(s) for this?
L31: “...due to the fast evolution and large variability of clouds...” again, some references for this statement showing this in CMIP6 (or previous versions of CMIP) would be good here.
L32 “... the representation of clouds in climate models remains a challenge” how have other modeling groups found this challenging? I think you can expand this and make it stronger by adding another 1-2 sentences with additional supporting references.
L37: CMIP6 showed a large intermodel spread of what exactly? Please clarify.
L39-40: “... significantly departs from observations.” this is a strong statement, and needs supporting references.
L42: Suggested re-write: “This provides ideal conditions” --> “... and frontal systems (Field et al., 2017a), providing ideal conditions for...”
L44-48: Were there other studies done to support the findings of X.-Y. Li & F. Tornow?
L60-62: The wording of this sentence is awkward. Do you mean to say “Altogether the WNAO experiences interesting and complex weather patterns, thus providing a natural laboratory to study shallow and broken cumulus clouds in a broad spectrum of aerosol and meteorological conditions.”?
Figure 1: This is a very nice overview figure. Perhaps this question will be answered later as I continue reviewing this paper, but could you comment on the potential impact of the underlying Gulf Stream on potential cloud properties? The flight track locations mostly seem to take place across the primary area here, but I am curious if anyone has done work to show if the warm Gulf stream waters affect boundary layer cloud maintenance in the WNAO.
L102: “15%/40%/45% respectively”.
L115: Are these calibration uncertainties true for all ACTIVATE flights? Please clarify. I would also add a reference here if these calibration uncertainties have been previously published.
Section 2.2: This section is very nicely detailed and written.
L141-142: Given LWC and IWC are integral parts of your study, you should show equations for both after Eq. (1).
L149-150: I had a similar comment earlier, but are these “corresponding uncertainties” published elsewhere? If so, I would add a reference to that study here as well.
L172-176: You may find the following two studies interesting. Sinclair et al. (2021) showed using polarimetric and radar data how cloud top DSDs can be used to infer precipitation in conditions where rainwater path (and hence liquid water path) might be quite low. Dzambo et al. (2021) used these same datasets to partition cloud path and rainwater path – Figure 2 in Section 4 shows that, when using RSP data to constrain cloud LWP, cloud water content is generally in the 0.05 g/m3 to ~0.4 g/m3 range, so mentioning that in-cloud LWC of ~0.02 g/m3 can exclude some precipitation makes for a very interesting comparison as both of those studies used ORACLES data (from the SE Atlantic, also a very aerosol-rich environment). Note for both studies that the results are for stratocumulus.
Sinclair, K., van Diedenhoven, B., Cairns, B., Alexandrov, M., Dzambo,
A. M., & L'Ecuyer, T. (2021). Inference of precipitation in warm stratiform clouds using remotely sensed observations of the cloud top droplet size distribution. Geophysical Research Letters, 48, e2021GL092547. https://doi. Org/10.1029/2021GL092547General Comment: I am personally most familiar with the NASA ORACLES field campaign, but several other campaigns (e.g., CAMP2EX, NAAMES, SEAC4RS) have similar objectives to ACTIVATE but in different regions of the globe. I have added a few references worth considering to start (here and below), but I would recommend to the authors that they go through relevant and similar studies to this one on those campaigns and check to see how the results of this study compare to those. Ultimately, it will be very useful to the broader modeling communities how observed cloud properties vary by region, in addition to fortifying your own conclusions.
L209: “in summer” --> “during the summer”
L211-212: “which could result in more frequent occurrence of stratiform cloud decks” this could indeed be true, but this raises the classic question regarding the relative roles of meteorological conditions versus background aerosol conditions in explaining the more frequent occurrence of stratiform. Can you comment on the role that atmospheric subsidence might play in maintaining stratiform? The works by Lee et al. (2009) and Jia et al. (2021, specifically Figs. 2 and 3) might be relevant here:
Lee, S. S., Donner, L. J., and Phillips, V. T. J.: Sensitivity of aerosol and cloud effects on radiation to cloud types: comparison between deep convective clouds and warm stratiform clouds over one-day period, Atmos. Chem. Phys., 9, 2555–2575, https://doi.org/10.5194/acp-9-2555-2009, 2009.
Jia, H., Ma, X., Yu, F. et al. Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods. Nat Commun 12, 3649 (2021). https://doi.org/10.1038/s41467-021-23888-1
L227: This is beyond the scope of your study, but it would be really interesting to see a follow-on study to this work diving deeper into the role of meteorology (namely, inversion strength, subsidence strength, etc.) has on the cloud properties you observe here. Perhaps partition the results you show in Figure 4 into estimated inversion strength and a second variable (relative humidity or subsidence strength) similar to Figure 3 in Douglas and L’Ecuyer (2020):
Douglas, A. and L'Ecuyer, T.: Quantifying cloud adjustments and the radiative forcing due to aerosol–cloud interactions in satellite observations of warm marine clouds, Atmos. Chem. Phys., 20, 6225–6241, https://doi.org/10.5194/acp-20-6225-2020, 2020.
L240-242: This is very interesting. Figure 5 shows mixed-phase conditions quite clearly, relative to graupel conditions.
L253-255: Do you mean to say your results provide evidence here of precipitation suppression?
L280: I agree with the conclusions in this paragraph.
Figure 8: To be clear, the frequency of precipitation implies the fraction (percent) of cloud events that had precipitation? Based on the frequency % of these results, some readers might assume that nearly every winter 2021 cloud event had observed precipitation.
L302-303: Another idea you could pursue is investigating/applying the work of the aforementioned Sinclair et al. (2021) study to explore cloud top DSDs during ACTIVATE, and if enough data are available, could “bridge” the in-situ results to relevant satellite studies of the area. Validating satellite measurements with remote sensing instrumentation isn’t an easy task, however...
L321: This could be a good area to add discussion about the role of the Gulf Stream, and any seasonal variability it has, on surface heat/moisture fluxes & subsequent influence on cloud formation.
Figure 10: I really like this visualization method – very clever and informative given the vast amount of data you have.
L335: This study is very clean and thorough in quantifying/assessing cloud properties observed throughout the ACTIVATE campaign, and I think as readers go through this work, they will likely have some good ideas for how to carry this work forward – a hallmark of a very well written manuscript. In my opinion, assessing the role of meteorology on the cloud properties you observed will make for a nice follow-on. I would mention here near the end of this paragraph (or as a separate paragraph as this final paragraph in this section is already quite long) some ideas for how you would investigate the role of meteorology on all these cloud properties. The discussion here, objectively speaking, offers several viable (and accurate) explanations for why you observe these cloud properties, hence quantifying this would be good going forward.
L369-374: I agree with all of these conclusions. Excellent overview of the in-situ cloud microphysical measurements and observations from ACTIVATE – I definitely learned a lot reading this.
Citation: https://doi.org/10.5194/egusphere-2023-898-RC2 -
AC1: 'Comment on egusphere-2023-898', Simon Kirschler, 28 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-898/egusphere-2023-898-AC1-supplement.pdf
Interactive discussion
Status: closed
- RC1: 'Comment on egusphere-2023-898', Anonymous Referee #1, 29 May 2023
-
RC2: 'Comment on egusphere-2023-898', Anonymous Referee #2, 15 Jun 2023
Review of “Overview and statistical analysis of boundary layer clouds and precipitation over the western North-Atlantic Ocean” by Kirschler et al., for EGUsphere
General Comments
This manuscript uses ACTIVATE data, which spanned 3 summer and 3 winter seasons, that sampled over 17,000 cloud events using the FCDP and 2D-S in-situ probes. The authors found, consistent with many other previous studies, that both LWC and cloud droplet effective diameter increase with altitude inside clouds. Higher updraft speed in winter boundary layer clouds explains higher cloud droplet number concentrations despite lower CCN. A seasonal contrast in cloud type and coverage is noted: inter clouds are typically stratocumulus, aided by passing synoptic-scale low pressure/frontal systems, whereas summer clouds are more likely to be open cell cumulus. The strength of this paper lies in the thorough overview of the vast quantity of in-situ measurements of boundary layer clouds, whether liquid, mixed-phase or ice clouds, and quantifying their relative occurrence through the entire 3-year dataset.
This manuscript is very well written, easy to follow along, and comes to accurate and valuable conclusions that will be useful to the broader scientific community looking to investigate cloud properties in this region of the globe across many applications (LES and climate modeling, meteorological influences, etc.). The only area of the manuscript that, in my opinion, needs improvement is in the introduction/literature review: there were many broad-reaching statements that need to be supported (or could be better supported) by recent studies. Specific comments are noted below. I also noted a few areas later in the paper where the results of this work could be directly compared, namely with other similar suborbital campaigns. I think the authors should consider a follow-on study quantifying the role of meteorological influences to the observed cloud properties, as the manuscript makes several references explaining why observed cloud properties occur but only provides temperature data for context. I think this manuscript is very clean in its current form and adding such analysis – in my opinion – is better off as its own separate analysis and manuscript.
Overall, this manuscript merits publication in EGUsphere. The majority of my comments are “minor” in nature, and the authors have a high degree of flexibility in how they choose to address them.
Specific Comments
L25-38 (Paragraph 1): This paragraph flows well, but several of the statements need additional references, especially more recent references that have addressed or provided new evidence for some of the statements.
L29: You can just say “Weather systems”, drop “Meteorological”.
L30: “... can induce ice nucleation or the formation of precipitation” reference(s) for this?
L31: “...due to the fast evolution and large variability of clouds...” again, some references for this statement showing this in CMIP6 (or previous versions of CMIP) would be good here.
L32 “... the representation of clouds in climate models remains a challenge” how have other modeling groups found this challenging? I think you can expand this and make it stronger by adding another 1-2 sentences with additional supporting references.
L37: CMIP6 showed a large intermodel spread of what exactly? Please clarify.
L39-40: “... significantly departs from observations.” this is a strong statement, and needs supporting references.
L42: Suggested re-write: “This provides ideal conditions” --> “... and frontal systems (Field et al., 2017a), providing ideal conditions for...”
L44-48: Were there other studies done to support the findings of X.-Y. Li & F. Tornow?
L60-62: The wording of this sentence is awkward. Do you mean to say “Altogether the WNAO experiences interesting and complex weather patterns, thus providing a natural laboratory to study shallow and broken cumulus clouds in a broad spectrum of aerosol and meteorological conditions.”?
Figure 1: This is a very nice overview figure. Perhaps this question will be answered later as I continue reviewing this paper, but could you comment on the potential impact of the underlying Gulf Stream on potential cloud properties? The flight track locations mostly seem to take place across the primary area here, but I am curious if anyone has done work to show if the warm Gulf stream waters affect boundary layer cloud maintenance in the WNAO.
L102: “15%/40%/45% respectively”.
L115: Are these calibration uncertainties true for all ACTIVATE flights? Please clarify. I would also add a reference here if these calibration uncertainties have been previously published.
Section 2.2: This section is very nicely detailed and written.
L141-142: Given LWC and IWC are integral parts of your study, you should show equations for both after Eq. (1).
L149-150: I had a similar comment earlier, but are these “corresponding uncertainties” published elsewhere? If so, I would add a reference to that study here as well.
L172-176: You may find the following two studies interesting. Sinclair et al. (2021) showed using polarimetric and radar data how cloud top DSDs can be used to infer precipitation in conditions where rainwater path (and hence liquid water path) might be quite low. Dzambo et al. (2021) used these same datasets to partition cloud path and rainwater path – Figure 2 in Section 4 shows that, when using RSP data to constrain cloud LWP, cloud water content is generally in the 0.05 g/m3 to ~0.4 g/m3 range, so mentioning that in-cloud LWC of ~0.02 g/m3 can exclude some precipitation makes for a very interesting comparison as both of those studies used ORACLES data (from the SE Atlantic, also a very aerosol-rich environment). Note for both studies that the results are for stratocumulus.
Sinclair, K., van Diedenhoven, B., Cairns, B., Alexandrov, M., Dzambo,
A. M., & L'Ecuyer, T. (2021). Inference of precipitation in warm stratiform clouds using remotely sensed observations of the cloud top droplet size distribution. Geophysical Research Letters, 48, e2021GL092547. https://doi. Org/10.1029/2021GL092547General Comment: I am personally most familiar with the NASA ORACLES field campaign, but several other campaigns (e.g., CAMP2EX, NAAMES, SEAC4RS) have similar objectives to ACTIVATE but in different regions of the globe. I have added a few references worth considering to start (here and below), but I would recommend to the authors that they go through relevant and similar studies to this one on those campaigns and check to see how the results of this study compare to those. Ultimately, it will be very useful to the broader modeling communities how observed cloud properties vary by region, in addition to fortifying your own conclusions.
L209: “in summer” --> “during the summer”
L211-212: “which could result in more frequent occurrence of stratiform cloud decks” this could indeed be true, but this raises the classic question regarding the relative roles of meteorological conditions versus background aerosol conditions in explaining the more frequent occurrence of stratiform. Can you comment on the role that atmospheric subsidence might play in maintaining stratiform? The works by Lee et al. (2009) and Jia et al. (2021, specifically Figs. 2 and 3) might be relevant here:
Lee, S. S., Donner, L. J., and Phillips, V. T. J.: Sensitivity of aerosol and cloud effects on radiation to cloud types: comparison between deep convective clouds and warm stratiform clouds over one-day period, Atmos. Chem. Phys., 9, 2555–2575, https://doi.org/10.5194/acp-9-2555-2009, 2009.
Jia, H., Ma, X., Yu, F. et al. Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods. Nat Commun 12, 3649 (2021). https://doi.org/10.1038/s41467-021-23888-1
L227: This is beyond the scope of your study, but it would be really interesting to see a follow-on study to this work diving deeper into the role of meteorology (namely, inversion strength, subsidence strength, etc.) has on the cloud properties you observe here. Perhaps partition the results you show in Figure 4 into estimated inversion strength and a second variable (relative humidity or subsidence strength) similar to Figure 3 in Douglas and L’Ecuyer (2020):
Douglas, A. and L'Ecuyer, T.: Quantifying cloud adjustments and the radiative forcing due to aerosol–cloud interactions in satellite observations of warm marine clouds, Atmos. Chem. Phys., 20, 6225–6241, https://doi.org/10.5194/acp-20-6225-2020, 2020.
L240-242: This is very interesting. Figure 5 shows mixed-phase conditions quite clearly, relative to graupel conditions.
L253-255: Do you mean to say your results provide evidence here of precipitation suppression?
L280: I agree with the conclusions in this paragraph.
Figure 8: To be clear, the frequency of precipitation implies the fraction (percent) of cloud events that had precipitation? Based on the frequency % of these results, some readers might assume that nearly every winter 2021 cloud event had observed precipitation.
L302-303: Another idea you could pursue is investigating/applying the work of the aforementioned Sinclair et al. (2021) study to explore cloud top DSDs during ACTIVATE, and if enough data are available, could “bridge” the in-situ results to relevant satellite studies of the area. Validating satellite measurements with remote sensing instrumentation isn’t an easy task, however...
L321: This could be a good area to add discussion about the role of the Gulf Stream, and any seasonal variability it has, on surface heat/moisture fluxes & subsequent influence on cloud formation.
Figure 10: I really like this visualization method – very clever and informative given the vast amount of data you have.
L335: This study is very clean and thorough in quantifying/assessing cloud properties observed throughout the ACTIVATE campaign, and I think as readers go through this work, they will likely have some good ideas for how to carry this work forward – a hallmark of a very well written manuscript. In my opinion, assessing the role of meteorology on the cloud properties you observed will make for a nice follow-on. I would mention here near the end of this paragraph (or as a separate paragraph as this final paragraph in this section is already quite long) some ideas for how you would investigate the role of meteorology on all these cloud properties. The discussion here, objectively speaking, offers several viable (and accurate) explanations for why you observe these cloud properties, hence quantifying this would be good going forward.
L369-374: I agree with all of these conclusions. Excellent overview of the in-situ cloud microphysical measurements and observations from ACTIVATE – I definitely learned a lot reading this.
Citation: https://doi.org/10.5194/egusphere-2023-898-RC2 -
AC1: 'Comment on egusphere-2023-898', Simon Kirschler, 28 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-898/egusphere-2023-898-AC1-supplement.pdf
Simon Kirschler et al.
Data sets
Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment Armin Sorooshian http://doi.org/10.5067/SUBORBITAL/ACTIVATE/DATA001
Simon Kirschler et al.
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