the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Diurnal cycle of stratocumuli mesoscale convective cells in the South-East Pacific
Abstract. Stratocumulus (StCu)-topped boundary layers exhibit complex mesoscale cellular convection that remains a primary source of uncertainty in climate radiative forcing and a persistent challenge for climate models. While daytime snapshots have established a characteristic aspect ratio (AR)—the ratio of cell size λ to boundary-layer depth—of 30–40, its evolution over the full diurnal cycle remains poorly constrained.
Here we use high-resolution infrared observations from GOES-East (2020–2025) over the South-East Pacific during August–September to provide a continuous day-to-night characterization of StCu spatial metrics. Using a brightness temperature difference framework (ΔTb = Tb12.3 µm – Tb10.3 µm), we reveal a robust universal four-phase diurnal cycle: morning growth, early-afternoon plateau, rapid late-afternoon downscaling, and a stable nocturnal regime.
We demonstrate a striking decoupling between metrics: while λ varies significantly across years, the AR curves collapse into a nearly identical diurnal signal across the 2020–2025 period, effectively filtering out interannual variability. However, this invariance is modulated by cloud-fraction regimes, which control the amplitude of the cycle and the timing of its growth and decay phases for AR.
This allows us to establish a nocturnal AR of 25 ± 2, with a transient daytime maximum of 31 ± 1.5. These results suggest a fundamental compensation between horizontal and vertical scales, with AR acting as a dynamical attractor of stratocumulus organization. Its persistence raises a key question: why does mesoscale organization maintain this characteristic scale ratio throughout the diurnal cycle?
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RC1: 'Comment on egusphere-2026-2160', Anonymous Referee #1, 15 May 2026
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2160/egusphere-2026-2160-RC1-supplement.pdfReplyCitation: https://doi.org/
10.5194/egusphere-2026-2160-RC1 -
RC2: 'Comment on egusphere-2026-2160', Anonymous Referee #2, 16 May 2026
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Review of Monnier et al: Diurnal cycle of stratocumuli mesoscale convective cells in the
South-East Pacific
The authors have constructed an aspect ratio product using cloud cell size and estimated cloud top height for MODIS and GOES retrievals, the latter also offering a day-night product. A diurnal analysis shows a robust pattern of increasing aspect ratio from sunrise until a few hours after noon, then an afternoon decrease, and a stable signal overnight. This pattern is regionally consistent in the SE Pacific study region, and temporally consistent for the five years of GOES data, though ENSO does appear to modify the mean aspect ratio. Cloud amount modulates the amplitude of the diurnal cycle of aspect ratio to some extent, but the study suggests that the aspect ratio diurnal cycle may be an intrinsic feature of Sc clouds, mostly invariant to other controlling factors.
This study produces unique and valuable results concerning the process-scale properties of marine stratocumulus. Successful modeling of such clouds is essential for accurate climate and weather forecasting, and these emergent features offer a great baseline for comparing model results with reality. The study is well presented, with excellent figures. The language could benefit from additional copy-editing, but is not problematic. The paper is well-constructed overall, the results are well supported, and the work is in no need of major methodological changes, however a few minor revisions would benefit the work.
Main points:
Scene selection: Can you add a few words on why you chose the domain sizes, and whether results are sensitive to this decision?
Paragraph on line 161: How is the 45% threshold determined? Also, how are you interpolating the gaps. Linear 2-D? Maybe be a little more explicit describing this so it could be more accurately reproduced.
The aqua-terra CTH disparity in Figure 5a looks like a sensitivity/calibration issue perhaps? Any insights into this?
Maybe I missed it somewhere in the text, but did you match the CTT spatial scales between MODIS and ABI before calculating CTH? Differing resolutions will likely cause differing CTT distributions.
Please reference the data sources for the points listed from lines 95 to 112.
It’s clear that the AR follows the cell width in Figures 6 and 8, but why not at least show the cycles of CTH as well? This would allow the reader to better gauge the contributions of CTH and lambda. Same for Figures 13 and 14.
The figures do a good job in showing that the temporal evolution of AR is driven primarily by cell size. Could you set up a similar argument when looking at the spatial fields in Figure 9, where we could also compare the spatial distributions of Lambda and CTH? This would allow us to see whether the spatial distributions are also driven by cell size.
Regarding CF in Figure 11: How is CF retrieved? The jump in CF near sunrise and sunset has the look of a low-sun-angle bias in visible data. Is it possible that visible channels are being used for the daylight CF values, but not for night? This could cause the spurious jump in CC during sunrise/sunset. I don’t believe that these jumps have been seen in corresponding LWP data, or in any surface observations. They look non-physical.
In fact, many figures show clear non-physical behavior between sunrise and 8 LST, then from 16 LST to sunset. I recommend omitting these distracting, non-physical features, and leaving the figures blank during those times. No data is preferable to wrong data.
More of a comment for future work: An obvious place to start looking at modulating factors is upper-level humidity. If the radiative balance at cloud top sets the AR, then increased upper humidity may somewhat mimic an increase in sun angle, since both add downwelling radiation to the cloud top.
This may be more of a future work comment again, but can you address possible differences in MCC types? Figure 3 shows a pocket of open cells embedded within closed cells. Do open cell aspect ratios behave in the same way as closed? This would be interesting to study given the differences in mechanisms. I recommend mentioning this possibility somewhere in the paper.
Figure 9 needs latitude-longitude lines.
Citation: https://doi.org/10.5194/egusphere-2026-2160-RC2
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