the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Asymmetries in winter cloud microphysical properties ascribed to sea ice leads in the central Arctic
Pablo Saavedra Garfias
Heike Kalesse-Los
Luisa von Albedyll
Hannes Griesche
Gunnar Spreen
Abstract. To investigate the influence of sea ice openings like leads on wintertime Arctic clouds, the air mass transport is exploited as humidity feeding mechanism which modifies cloud properties like total water content, cloud phase partitioning, cloud altitude, and thickness. Cloud microphysical properties in the Central Arctic are analyzed as a function of sea ice conditions during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020. A state-of-the-art cloud classification algorithm is used to characterize the clouds based on observations by vertical pointing lidar, radar, microwave radiometer, and atmospheric thermodynamic state from the observatory on board the research vessel Polarstern. To link the sea ice conditions around the observational site with the cloud observations, the water vapor transport (WVT) being conveyed towards the Polarstern has been exploited as a mechanism to associate sea ice conditions upwind with the measured cloud properties. This novel methodology is used to classify the observed clouds as coupled or decoupled to the WVT based on the location of the maximum vertical gradient of WVT height relative to the cloud-driven mixing layer extending above and below the cloud top and base, respectively. Only a conical sub-sector of sea ice concentration (SIC) and lead fraction (LF) centered at the Polarstern location and extending up to 50 km radius and azimuth angle governed by the time-dependent wind direction measured at the maximum WVT is related to the observed clouds. We found significant asymmetries for cases when the clouds are coupled or decoupled to the WVT, and when cases are selected by LF regimes. Liquid water path of low level clouds is found to increase as a function of LF while ice water path does so only for deep precipitating systems. Clouds coupled to WVT are found to be low level clouds and are thicker than decoupled clouds. Thermodynamically, we found that for coupled cases the cloud top temperature is warmer and accompanied by a temperature inversion at cloud top, whereas the decoupled cases are found to closely be compliant with the moist adiabatic temperature lapse rate. The ice water fraction within the cloud layer has been found to present a noticeable asymmetry when comparing coupled versus decoupled cases. This novel approach of coupling sea ice to cloud properties via the WVT mechanism unfolds a new tool to study Arctic surface-atmosphere processes. With this formulation long-term observations can be analyzed to enforce the statistical significance of the asymmetries. Our results serve as an opportunity to better understand the dynamic linkage between clouds and sea ice and to evaluate its representation in numerical climate models for the Arctic system.
Pablo Saavedra Garfias et al.
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2023-623', Anonymous Referee #1, 05 May 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-623/egusphere-2023-623-RC1-supplement.pdf
-
RC2: 'Comment on egusphere-2023-623', Anonymous Referee #2, 15 May 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-623/egusphere-2023-623-RC2-supplement.pdf
-
RC3: 'Comment on egusphere-2023-623', Anonymous Referee #3, 17 May 2023
The article "Asymmetries in winter cloud microphysical properties ascribed to sea ice leads in the central Arctic" studies the impact of the presence of leads on cloud properties based on data from the MOSAiC campaign. The authors efficiently use the synergy of different datasets to constrain several parameters (coupled vs. decoupled cases, different lead fractions...). The study highlights the importance of considering the leads to study the properties of Arctic clouds. The dataset, the method and the analyses seem to be robust and the results are convincing. The authors show some interesting results: For example, the lead fraction has an important influence on the cloud thickness and on the ice water path. I have a few comments (see below) that I would like the authors to consider, but the topic and content of the paper are within the scope of the journal, so I recommend publication.
General comments:
- I wonder if the authors looked at the effect of melt ponds or what they think about it. Would it have a similar effect as the leads (maybe weaker effect)?
- The authors use the Cloudnet dataset based on observations to retrieve cloud properties. Like any observation, Cloudnet should have an error in the observations and in the retrievals, but this is not shown here. I expect that this uncertainty should appear in the results, or at least be discussed.
- Methodology: The considered wind profile is measured at the RV Polarstern and not at the leads. Therefore, I think Figure 4 is misleading, but I understand that it is considered constant between the leads and RV Polarstern: How true is this hypothesis, have the authors quantified the possible biases from a change in WVT along the way (between the lead and Polarstern)?
- Do the authors look at what types of clouds we are mainly looking at in the study? In terms of mixed-phase clouds, are they mainly the typical mixed-phase clouds with precipitating ice below a liquid layer, or are they more mixed?
- Figure 7: From the plot, it appears that clouds are mixed phase in the coupled situations and only ice in the decoupled situations. Is this always the case? Can the authors comment on this? And the next question is: Could we use the presence of mixed phase to detect coupled situations (or vice versa)? Could we use the presence of leads (and coupled situations) to detect mixed phase clouds (or vice versa)?
- I was wondering if the authors considered the effect of aerosols. Leads could be a source of marine aerosols and therefore affect the thermodynamic phase of the cloud. I guess Polarstern might have measurements of this. The increase in moisture would be the most important effect on cloud properties, but aerosols might not be negligible.
Minor comments:
- Title: I do not like the term "Asymmetries" because it emphasizes more a difference than an asymmetry. Also, I found that this term is more associated with geographical differences, but that may be just me, but I recommend changing the title.
- Abstract: There is a lot of technical details in the abstract that could be removed here.
- Line 42: We usually refer to the Wegener-Bergeron-Findeisen process. Then the citation Wegener 1911 could be added
- Wegener, A. (1911). Thermodynamik der atmosphäre. JA Barth
- Line 118: “We note that leads…” Do the authors mean that in this situation the leads are considered to be sea ice? If so, I wonder if they quantify the error from this.
- Line 160: “described as following”, at first, I thought the authors were explaining the identification of sea ice leads, but they are describing the potential influence of leads on cloud properties. I suggest changing the sentence.
- Line 166: The acronym CO is confusing because it is already used for coupled. Perhaps it is not necessary to have an acronym for Central Observatory since it is not used that often.
- l. 180: are of having -> are having
- l.190: “meaning the lidar signal is attenuated by low-level liquid clouds”, I am not sure I understand. Does this mean that the algorithm does not detect the low level cloud, but the signal is attenuated by the cloud and therefore the measurements are biased? Have the authors quantified the effect on the results?
- l. 201: The constant g appears in equation 1, so it should be defined there.
- l. 273: CMLH of below -> CMLH or below
- l. 277: to be take -> to be
- l. 332: “clear”, I would be careful with the term "clear" because some points are not within 3 sigma. Also from Figure 8, I wonder how the fit is done.
- l. 347: “Figure 8 … -10˚ C km-1” I am not sure I understand the sentence, can the authors rephrase it?
- Figure 11 caption: the subscripts (c) and (d) are not correct.
- Section 5 Conclusion and Outlook: What is missing is a discussion section where the various results are summarized. This is done in Figure 4, but I would go a bit further before the conclusions. I do not think much is needed, but just highlighting what the results bring to the model would be enough.
- l. 559: WVF -> Do you mean WVT?
Citation: https://doi.org/10.5194/egusphere-2023-623-RC3
Pablo Saavedra Garfias et al.
Pablo Saavedra Garfias et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 236 | 78 | 9 | 323 | 4 | 0 |
- HTML: 236
- PDF: 78
- XML: 9
- Total: 323
- BibTeX: 4
- EndNote: 0
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1