the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Jul 2026
Persistent decoupling weakens marine stratocumulus, with specific humidity inversions modulating microphysical and radiative responses
Abstract. Marine stratocumulus cloud (MSC) evolution is strongly influenced by boundary-layer coupling and turbulent mixing. However, under decoupled conditions, the impacts of specific humidity inversions (SHIs) on in-cloud mixing and microphysical evolution remain poorly constrained by in situ observations. Here, 12 persistently decoupled MSC cases from six flights during VOCALS-REx, POST, and ACE-ENA are analyzed to examine cloud microphysical, mixing, and radiative evolution with and without SHIs. Persistent decoupling generally suppresses MSC maintenance, reducing cloud thickness, liquid water content (LWC), mean droplet radius (rm), and droplet spectral width. Without SHIs, dry air entrainment drives substantial upper-cloud LWC depletion under inhomogeneous mixing (IM)-dominated conditions, characterized by preferential evaporation of small droplets and super-adiabatic droplet formation, reducing cloud optical thickness (τ), albedo, and shortwave cloud radiative forcing. Conversely, when SHIs are present, moist air entrainment suppresses evaporative losses and modifies the microphysical consequences of IM by favoring collision–coalescence growth. Consequently, droplet spectra broaden toward larger sizes, super-adiabatic droplets form more readily, cloud dissipation is mitigated, and shortwave radiative forcing can be maintained or enhanced. Under sustained cloud-top moisture supply, SHIs can even support cloud maintenance or redevelopment. However, when droplet growth becomes sufficiently strong to promote precipitation-related cloud-water loss, cloud water and optical thickness may decline despite SHIs. Collectively, the observations suggest that MSCs under persistently decoupled boundary-layer conditions may follow distinct evolutionary pathways, including evaporative dissipation, moisture-driven cloud maintenance or redevelopment, and, in some cases, precipitation-related dissipation. These pathways have important implications for low-cloud shortwave radiative feedbacks in climate models.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-3376', Anonymous Referee #1, 27 Jul 2026
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RC2: 'Comment on egusphere-2026-3376', Patrick Chuang, 08 Sep 2026
Review of “Persistent decoupling weakens marine stratocumulus, with specific humidity inversions modulating microphysical and radiative responses” by Zhang et al.
Reviewer: Patrick Chuang, UC Santa Cruz
General thoughts
Before starting, I want to state that I was on the science team for both the VOCALS Twin Otter and POST projects, and so I'm quite familiar with these data sets. In addition, my group made cloud microphysical measurements using a phase-Doppler interferometer (PDI) during both of these campaigns. I also have flown on about a dozen field campaigns with the Twin Otter over the past 20 years (starting in 2005, most recently in July 2026), so I'm very familiar with its instrument package. I have no connection with the ACE-ENA project.
The general idea of studying Sc layers under decoupled conditions is a good one. While it's hard to tell how often they occur, my experience of flying in numerous projects suggests that it's fairly common in the near-coastal environments where the Twin Otter tends to fly. How reflective these conditions are of the more open ocean environment is unclear to me. So I fully support the topic of your study.
Lastly, a few abbreviations for simplicity: BL = boundary layer; FT = free troposphere; CB and CT = cloud base/cloud top.
Now for the main issues that I have with how you've approached this topic.
1) Your paper is VERY difficult to read and digest. You have 12 cases, dozens of variables, and probably hundreds of values, all trying to tell (many) stories. It is way too much for any regular human being to understand. I suggest you focus on a subset of stories, and tell them more clearly. If that means this material has to be broken up into, say, 3 separate papers, I think that's OK.
2) The VOCALS and POST cases you show are flown during the day, and bracketing solar noon. So the most obvious explanation for any BL changes that are observed is the net radiative flux and its evolution. There's a reason that these clouds typically thin during the day, and deepen at night. But I see no discussion that either rules this out as a mechanism for BL evolution, or accounts for this process.
3) I think your classification of cases by SHI makes sense. Your basic argument is that SHIs, as you define them, tell you something about the moisture entrainment flux, and these flux values are the root of all the differences observed among your cases. Unfortunately, you haven't convinced me of this.
The traditional view is that the entrainment flux of some scalar depends on two things (i) the jump or gradient of that scalar across the top of the BL; and (ii) the strength of the turbulence in the BL. For (i), your SHI definition uses the qt jump or gradient at CT, but this isn't the top of the BL – that's located where the TKE goes to zero. (Which you know, since your BL heights appear to use exactly this definition – so why are SHIs defined at CT?). For (ii), TKE near CT changes by a factor of 5 from the V-RF06 case to the A-0711 case, but you implicitly assume this is NOT relevant, which essentially neglects the role of (ii).
Also, I'm not even sure you've consistently picked out accurate jumps. The jump in qt for A-0707 is big, like 9 or more g/kg for A-0707 case, but you're trying to argue this is a case where moist air is entrained into the BL. Even for A-0711 the jump is 3 to 4 g/kg... which sounds small except V-RF09 also has a jump that's a bit above 4 g/kg.
It is notoriously difficult to compute entrainment fluxes (see Faloona et al., JAS, 2005 for example). That implies that your desire to classify cases based on the entrainment moisture flux is a very difficult thing to do. In addition, your method does not include all the relevant physics.
Summarizing this point: entrainment fluxes are much more complicated than your categorization by SHI, and I don't think your method separates the cases appropriately.
4) Why these specific cases? There must be other decoupled cases in the VOCALS, POST and (presumably) ENA catelog. How did you choose them? Can you convince me that you didn't cherry pick them to tell the story?
5) Along the same line as Point #2, you are trying to argue that time is the only reason for the changes that you observe for each of the 6 flights. However, you have to convince me that the changes aren't due to SPATIAL gradients. For POST, it's probably fine, since there's so much cloud top structure measured across the entire cross-wind line. But for VOCALS, for instance, there are limited vertical soundings, and they may not be in the exact same spot – sometimes they are at opposite ends of our 30-km (10-min) leg. I don't now about ENA, but the point is, you have to choose profiles that are in the exact same (Lagrangian, hopefully) location if you want to look at small changes and convince the reader these are changes over time, not space.
6) In a lot of cases, I was left wondering how many data points were used, especially for profiles. Maybe you could show this on, say, Fig. 2. Since VOCALS was done using mostly level legs, a LOT of the time there isn't much data outside of those specific altitudes. So I found it difficult to understand the statistical significance of anything that relies heavily on profiles, such as your “transition layer” identification.
7) Why did you choose to use the CAS probe for the Twin Otter measurements when you could have used the PDI? (And why did you choose the FCDP for the ENA measurements when you could have used HOLODEC?) So much of your paper is about microphysical properties, but you choose to use the less-reliable CAS probe. The CAS is less reliable, especially for larger drops (see Witte et al., GRL, 2018 for one example) which are critical if you are interested in higher-moment calculations where larger drops matter more (your Eq. 7 uses the SIXTH moment... I'm extremely skeptical that one can trust this calculation from the CAS); even the 3rd moment calculations in your mixing diagrams are, I believe, highly suspect. The CAS is also less reliable in high Nd conditions due to coincidence, which is exactly what VOCALS was – see Lance et al. 2012 for the CDP version of this paper. Obviously I'm biased since my group did the PDI measurements. So I would say that at a minimum, you should show that CAS and PDI compare favorably before you can convince me that your microphysical results are reliable. (Note: we've done it, and they're not, as shown by Witte 2018). Same with ENA and HOLODEC.
8) I obviously didn't go into any specifics, but one thing is highly strange: why does Z_LCL in Fig.4 decrease to zero? I believe the answer is that your Z_LCL isn't actually the Z_LCL, it's the Z_LCL *above* any given altitude. So you should have added the altitude of the measurement into the calculation for Z_LCL. That's why at cloud base, Z_LCL is zero or close to it. But obviously this isn't how anybody uses Z_LCL, which is tremendously confusing.
BTW, this also means that if Z_LCL is constant with height, this isn't some consistent layer where properties are constant with height as you state... it's actually the exact opposite. It's a layer where the real Z_LCL increases with height (since a well-mixed layer should show a decrease with height), suggesting that it's dryer or warmer as you increase with altitude. I think this means your transition layer calculation is incorrect, though I didn't look super closely at it so I might be wrong.
Citation: https://doi.org/10.5194/egusphere-2026-3376-RC2
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This manuscript addresses an important topic concerning the role of specific humidity inversions in the evolution of persistently decoupled marine stratocumulus. The multi-campaign aircraft observations are valuable. However, substantial revisions are needed to quantitatively support the proposed differences between cases with and without SHIs and to clarify several methodological and interpretative issues, as detailed in the attached PDF.