Annual cycle of surface-coupling effects on Arctic mixed-phase clouds during MOSAiC

Griesche, Hannes Jascha; Engelmann, Ronny; Radenz, Martin; Hofer, Julian; Althausen, Dietrich; Ansmann, Albert; Barry, Kevin; Creamean, Jessie; Jimenez, Cristofer; Seifert, Patric

doi:10.5194/egusphere-2025-5708

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https://doi.org/10.5194/egusphere-2025-5708

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16 Dec 2025

| 16 Dec 2025

Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Annual cycle of surface-coupling effects on Arctic mixed-phase clouds during MOSAiC

Hannes Jascha Griesche, Ronny Engelmann, Martin Radenz, Julian Hofer, Dietrich Althausen, Albert Ansmann, Kevin Barry, Jessie Creamean, Cristofer Jimenez, and Patric Seifert

Abstract. Persistent mixed-phase clouds frequently occurred in the Arctic and have significant impacts on the Arctic climate. The surface mixed-layer (SML) coupling status of these clouds impacts their microphysical properties. During an Arctic summer cruise in 2017, surface-coupled clouds were observed to contain ice more often than decoupled clouds at low-supercooling temperatures. Here, an annual cycle of Arctic mixed-phase cloud ice-formation temperatures is presented for the Arctic ice-drift experiment Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in 2019 and 2020. From October until March no clouds with cloud minimum temperatures above −10 °C were observed. From April to September an increased fraction of ice-containing clouds was observed for clouds with minimum temperatures between −7.5 °C and −5 °C (between 40% and 70%). Between April and July SML-coupled clouds with a minimum temperature above −7.5 °C showed an enhanced fraction of ice-containing clouds, compared to decoupled clouds (2–3 times higher). Also, SML-coupled clouds were 2–4 times more likely to be observed during this period. In August + September the ratio of coupled-to-decoupled ice-containing clouds reduced to 1.3, due to a higher frequency of occurrence of ice-containing decoupled clouds. Using surface-based ice-nucleating particle (INP) measurements the observed phenomena could likely be attributed to the presence of INPs active above −15 °C at the surface. Analysis of sea-ice concentration in the surrounding region, the distance to the ice edge, and the travel time along the back-trajectories to the marginal ice zone supports this finding.

Received: 17 Nov 2025 – Discussion started: 16 Dec 2025

Competing interests: Jessie Creamean is a member of the editorial board of ACP.

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Hannes Jascha Griesche, Ronny Engelmann, Martin Radenz, Julian Hofer, Dietrich Althausen, Albert Ansmann, Kevin Barry, Jessie Creamean, Cristofer Jimenez, and Patric Seifert

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RC1:
'Comment on egusphere-2025-5708', Anonymous Referee #2, 26 Dec 2025 reply
This manuscript examines parts of the annual cycle of cloud temperatures and the relative occurrence of ice during the MOSAiC expedition using bimonthly partitioning. The authors combine remote sensing (PollyXT, KAZR) with surface-based INP measurements to associate ice occurrence with primary ice nucleation and long-range INP transport, while dissecting the data by cloud-coupling state. I think the results showing differences in the ice occurrence fraction between coupled and decoupled cases are mostly robust. However, I have major concerns about parts of the methodology: the writing is mediocre (many sentences are difficult to understand), the literature review is lacking, and some references to the literature are inaccurate, leading to misleading statements and undermining the analysis's credibility.
Specific comments:

Methodology and Inaccurate references for methodological approaches:
IWC detectability threshold: In l. 178-179, it is stated that ice detectability by the lidar is determined "by considering the lowest detectable IWC from a lidar of 10-6 kg m-3 (Buhl et al., 2016)." I do not know where the authors found this threshold. Looking at Buhl et al., 2016, IWC values of 10-8 kg m-3 and lower are clearly seen in Fig. 7. (the case of smaller ice corresponding to smaller reflectivity contours), but perhaps there’s something I’ve missed.

Volume depolarization threshold of 0.03 for ice: based on l. 178, looking at Griesche et al. (2021), I do not see any derivation of the 0.03 threshold, other than a very similar quote, which is honestly misleading. It is true that, in theory, very small depolarization values are expected for liquids, but this requires consistent calibration and very accurate corrections and does not account for the occurrence of drizzle (larger non-spherical drops resulting in slightly higher depolarization - see earlier works of Sassen and Platt). A slight deviation in the deadtime correction, for example, could result in high depolarization around the cloud base region and, hence, a false positive for ice. I know the PollyXT is a wonderful instrument, but given the harsh conditions of that remote deployment, I doubt that assumption holds throughout the expedition, though I could be wrong.

The previous bullet combined with the apparent PollyXT data, which, unless I misinterpreted it, seems off (as demonstrated in Fig. 3):
Backscatter units appear closer to sr-1 m-1 than sr-1 mM-1, though if that is the case, I'd expect values closer to 1e-3 around the liquid cloud peak return (e.g., Thorsen and Fu, 2015, https://doi.org/10.1175/JTECH-D-14-00178.1). Given the Raman capabilities of the PollyXT, I would expect to see the derived backscatter cross-section field, which is more informative than the attenuated backscatter.

Depolarization field: missing depolarization values in-cloud, above cloud base but below the backscatter peak, are shown in Fig. 3b. Those are quite concerning, as I would have expected the cross-polar signal to be strong enough to generate a robust signal. If the NaN (or inf) values were the result of near-zero cross-pol values, then I would not have expected the depolarization to start showing again above a certain depth. Are the elevated values above the NaN region the result of a lack of implementation of multiple-scattering corrections? A very low SNR would likely have resulted in noise rather than a consistent pattern. The problematic depolarization signal around cloud base makes me very uncomfortable with the depolarization-only determination of ice, let alone the extremely small threshold of 0.03. This makes me think that the ice periods are overestimated throughout the analysis period (the radar analysis towards the end, for that matter, might be picking up on some supercooled drizzle, or not - see my penultimate comment of this review).

Trajectory analysis: This analysis is prone to errors when considering single trajectories (no ensembles), and results are very inconclusive, giving the feeling of “cherry picking”:
The authors describe in l. 216-218 the use of 10-day back-trajectories. I doubt that 10-day back trajectories are robust, especially over the polar regions. I believe that a small shift of a few kilometers, or even hundreds of meters, in the starting coordinates could result in major offsets. See the recent literature on the topic, e.g., from ARM.

“weakly coupled” (l. 335-337): I am not familiar with such a "weakly coupled" category. Looking at Silber and Shupe (2022), I do not see any reference to such a "weakly coupled" category. I do see that they used an equivalent ratio value of 5 and not 2, as used here, and their justification was the near-surface uncertainty in ERA5 (model output) over the polar regions, whereas here, real observations over the PolarStern are used, so I do not see a proper justification for this category.

The trajectory analysis results (Fig. 9 and related discussion): Fig. 9a appear inconclusive when considering the ice occurrence fluctuations vs. temperature (as opposed to Fig. 5 and mostly Fig. 8, where coupled cases consistently have higher ice fractions), and could be merely the result of confounders (e.g., time of year and icebreaker position integrated in Fig. 5). Because of this inconsistency, I tend to doubt the results in Fig. 9b, though the explanation in the text does make some sense. That said, note that the number of samples in Fig. 9b are significantly less balanced at T > -15 C, which could strongly influence the apparent agreement albeit the travel time partitioning.

Also, given the results in Fig. 10, how would this figure (9) look if you apply the trajectory partitioning on the radar-based definition?

Overeach statements, for example:
INPs vs. trajectory time in l. 244-246 - Eyeballing Fig. 2, this correlation appears coincidental and not more. There are times with an apparent sharp increase in INPC commensurate (or not) with trajectory travel times. More rigorous analysis is required to support this claim and conclusion.

INP concentration change discussed in l. 247-251: I do not think that more than a 2 orders-of-magnitude increase is "moderate". Moreover, they are at the very least equivalent to the June-July increase when examining the figure in detail.

Conclusions, specifically l. 478-480 (see my final comment below).

Writing – the text contains many sentences that are difficult to understand (some examples: l. 21-22, l. 290-291), the introduction lacks a clear storyline (the intro often reads like a collection of anecdotes on GW effects, etc.), there’s a frequent change of tense within paragraphs (e.g., l. 31-43), and many typos are found throughout the text (e.g., “during a Arctic”; l. 2, a repeating term “my means" in l. 161 and 175 – what does it mean?). The Introduction’s literature survey is lacking references to older works, giving the impression that the vast majority of findings are from the last 4-6 years. What about the extensive works of Tjernström, J. Curry, and more on ACI, Arctic atmosphere's thermodynamic profile, coupling state, etc.? I understand the focus on MOSAiC findings, but Arctic science existed before (SHEBA, etc.).

l. 14 - "along the back-trajectories" - which back trajectories? More information is needed here. Trajectories were not mentioned until now.

l. 23. - "initiated by an INP" - you mean "initiated by INPs"?

The continuous reference to INPs as singular throughout the text results in incorrect English when referring to "an INP". At some point in the text this changes and INPs are referred to in the plural form.

l. 44 - "INPs of different composition trigger ice formation at different temperatures." - is that accurate? INPs are more likely to activate at different temperatures depending on composition, with the likelihood increasing at lower temperatures, but the text does not reflect that.

l. 71 - "which is capped by a temperature inversion" - while this is typically true, temperature inversions are NOT ALWAYS the case (see earlier work mentioned above), or do the authors have a specific definition for a temperature inversion?

l. 83 - "decoupled from the WVT" - you mean decoupled from the sea ice leads?

l. 112 - define HYSPLIT and provide reference (likely Stein et al.). This is provided later in the text but should be stated here.

Fig. 1 - provide lat/lon information (what latitude does the inner circle denote? Some ticks, at the very least, are missing for longitude).

l. 133 - "another remote-sensing site" - you mean remote sensing facility? Or perhaps a remote sensing platform?

Table 1: Some of the information appears to be misleading: Can't the volume depolarization ratio exceed 0.5? What about KAZR Ze? can't it exceed +20 dBZ? I doubt that is the case.

Table 2 - Equation for decoupling height is inconsistent with the text description (l. 189-191).

l. 150. was --> were

l. 170 - 1e-5 sr-1 mM-1? So you use a threshold of 1e-8 sr-1 km-1 for liquid? I doubt it. Perhaps 1e-2 sr-1 km -1?

l. 271-273 - again, I could be missing something here, but the results in Buhl et al. support the detection of ice throughout the depicted period, considering the reflectivity values.

The observations in Fig. 3 seem somewhat off:
panel a - backscatter units (see major comment above)

panel b - Missing depolarization values in-cloud (see major comment above)

panel c - why is the cloud base not shown here as well? It is critical here for case evaluation. Also, see my other comment concerning ice detection.

panel d - I agree with your deduction of liquid only between 19-23 UTC. It all appears to indicate drizzle below cloud base, but why does Cloudnet classify it as ice? Is it purely a detectable echo at temperatures below 0 °C?

Also, no letters for panels

Also, the cloud base curve should be thinner (or smoothed) to enable lidar data evaluation of more pixels

l. 282 - In general, is the fraction of ice-containing clouds an accurate term? I mean, what happens in multi-layer cases? Perhaps you mean the fraction of ice-containing clouds among the lowest liquid clouds, or a similar definition? I think you already refer to this entire analysis as focusing on the lowest liquid clouds, but only towards the very end of the manuscript. This should be stated earlier, much closer to the beginning (and perhaps even in the abstract)

l. 293 - define how the uncertainty is calculated? Based on Seifert et al., I presume this is simply the standard error, which may or may not represent the _actual_ uncertainty. Given that the definition is rather simple, why not simply provide it “in full”?

l. 318 onward - until now the discussion was about coupled-decoupled but now it is in terms of free-tropospheric clouds. I recommend choosing a fixed terminology and using it throughout the text.

l. 350 - without INPs active at T > -15 C - so no INPs whatsoever, or just very small values? Based on Fig. 2d, and as one would expect, there are always INPs, even if at very small concentrations.

Also, no clouds were observed at all or do you mean ice-containing clouds were not observed?

l. 394-395 and Table 3 - EDR in log10 of what units? Specify.

l. 405-409 - I agree that it is more likely to detect sporadic ice crystals with a Ka-band radar than with a lidar, but how did you determine the radar echoes are necessarily precipitating ice and not supercooled drizzle for example?

Conclusions: in l.478-480 - This is indeed an apparent connection, but only an associative one. Recommend stating "associative" since without appropriate modeling accounting for these processes, one can suggest this connection, but not state that it is proven. Tone down.

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Citation: https://doi.org/10.5194/egusphere-2025-5708-RC1

Hannes Jascha Griesche, Ronny Engelmann, Martin Radenz, Julian Hofer, Dietrich Althausen, Albert Ansmann, Kevin Barry, Jessie Creamean, Cristofer Jimenez, and Patric Seifert

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Short summary

A full annual cycle of mixed-phase ice-formation temperatures in the high Arctic is presented. Ship-based remote sensing with lidar and cloud radar from the Arctic expedition MOSAiC was used to investigate the impact of surface processes on mixed-phase cloud properties. Surface mixed-layer cloud coupling was derived base on radiosonde profiles. Combined with INP filter samples, sea ice concentration and back-trajectory analysis an influence of surface processes on the cloud properties was found.


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