Summary:
This paper uses a dataset (introduced in a previous paper) that has co-located cloud and wind profiles. The lidar retrievals reveal a relationship between the Tropical Easterly Jet, deep convection, and cirrus clouds over the Arabian sea during the South-Asian Summer Monsoon (June-October 2020). Cirrus clouds are twice as likely to occur on mornings following a strong TEJ the evening before. The authors hypothesize a few mechanisms for the strengthening of the TEJ, concluding that deep convection is a major source of divergence from the thermal winds derived from theory. The time lag between events suggests a causal relationship on the frequency of occurrence of cirrus clouds.
General comments
The manuscript is much improved from the last version laying out the four hypotheses and using the data to back them up. H4 feels the most significant and supported/interpreted. Section 2.3 Domains of study is a great improvement. However, there are still some major organizational issues that impact clarity and make the paper feel disjointed. This manuscript feels like two separate papers (Sec 4 and 5) being forced into one without much interpretation or connection between the two.
To make the paper feel more unified, you could start with Sec 5 (Deep convection modulates the TEJ on a time scale of half a day). The most significant result of this paper is Fig. 12 showing the schematic of the relationship between deep convection and TEJ; having this main result earlier in the paper could be helpful. Then we look at the impact on cirrus clouds (currently Sec 4) from these changes in both TEJ (winds) and deep convection (and injection or water vapor) after you've already shown that these two (deep convection and TEJ winds) are related. Framing it this way may make it easier to explain the concepts in Sec. 4 since the reader already has developed an understanding of Aeolus, deep convection, and TEJ winds.
The hypotheses in Section 4 were a bit confusing and the results unclear as to which hypotheses you end up supporting. I'd frame these more like three equally likely hypotheses: H1; H2; and H3. Then each subsection dives into each of these hypotheses using data and reanalysis attempting to support or reject each hypothesis: (H1) Wind; (H2) Temperature; and (H3) Deep convection.
Furthermore, there should be a short discussion section to tie these two disparate parts together (this is also where you should discuss "implications for future warming Sec 4.6).
Specific comments
L9: delete comma after “(optically thin)”
L23: always use Oxford commas in scientific writing (add a comma before “or sedimentation”)
L27: “while cirrus cloud cover remains constant” – I think it is more accurate to say that the deep convective and anvil cloud cover decreases disproportionately compared to cirrus clouds; therefore, the net cloud radiative effect is positive. See Sokol et al., 2024: doi.org/10.1038/s41561-024-01420-6
L28: Similar to above, it might be more accurate to say “The change in anvil cloud properties (optical thinning) could have a positive…” instead of “Therefore, the anvil clouds could have a positive…”
L43: “during El Nino/La Nina years, with an intensity” --> “associated with the phase of El Nino Southern Oscillation and the intensity of the TEJ associated with summer monsoon rainfall over India.” (adds parallelism to this sentence structure)
L62: is maximum –> maximizes
L63: This -->This time lag
L65: Layout your hypotheses here. Explicitly state that “we test four hypotheses…”
L65: add the Oxford comma after “deep convective clouds,”
L81: Clarify: Second, due to the flight track of Aeolus, observations occurring…
L82: adequate --> suited
L105: Oxford comma
L107: larger than typically --> typically larger than
L123: delete s in “cloud covers” should be “cloud cover”
L191: “The wind still remains…” delete “still” (it redundant with "remains" right after)
L218-220: please clarify: do you mean the longer lifetime of cirrus clouds leads to this weaker diurnal contrast compared to deep convective clouds?
L225-226: “This indicates…” This is a strong choice of words. Due to the outflow of anvil from deep convection that can thin into cirrus, is it not also probable that the spatial coverage of cirrus is larger due to spreading whereas the deep convection is more restricted in horizontal extent. See Sassen et al., 2009. They show that cirrus cloud cover correlates with regions of deep convection but has a larger spatial extent (likely due to this spreading of anvil outflow effect).
L226: “not directly correlated to deep convective clouds” - In fact, I would say that Fig. 4i shows a good correlation between cirrus cloud cover and deep convective cloud cover for 06 LT. And that cirrus clouds spread out from deep convective core at 06LT. But we still do see a shift in both convection and cirrus cloud cover westward from early morning to late afternoon.
L229: “mainly develops” --> “is strongest”
L229-L231: run on sentence and confusing: “ which has a maximum intensity” --> Does the TEJ have a maximum intensity (implied by the grammar here) or do you mean the deep convection has a max intensity at 06 LT? Be precise in your language.
L232: What exactly about Fig. 4i makes you say this?
L241: Clarify the difference b/w H1 and H3. H1 says wind advects moisture from deep convection; H3 says deep convection occurs due to wind and then the moisture is advected. This difference is a bit subtle and maybe irrelevant?? Or is H3 more like testing direct outflow from deep convection forming cirrus later on?
Section 4.2: Fast wind days could just be thought of as "peak" TEJ in July/Aug...?
Figure 7: Optionally add a horizontal line for the median speed across all sky conditions (i.e., the fast/slow wind day threshold = -23.6 m/s) for comparison
L276: ON a given day FOR each 480 m…
L277: Not only is the peak important but the other local maxima. What does the spreading out of the pdf signify? Why is the peak at higher temperatures stronger for higher cirrus quartiles? Also, why is the second highest quartile (light blue line in Fig. 7b) so different (not following the trend) from the other quartiles? Are the second local maxima related to cirrus detrained from convection?
L284: “we can discard our hypothesis H2” - With all of your caveats after this statement, I don't think you should say "discard" here. maybe more like "while we cannot thoroughly disprove H2 based on these results, we can conclude that the temperature is not the main or sole driver of cirrus clouds in this region"
L290: “second” --> “third hypothesis H3”
L307-310: Move to before line 290. Start the section with this analysis - it is the strongest evidence. Then move to fast vs slow wind days.
Add "this shows that deep convection is important for cirrus formation and persistence; deep convection provides a direct source of ice crystals in the upper troposphere and acts as a source for water vapor which is then advected by the TEJ to over the Arabian sea. We explore the relationship of wind by categorizing each day into fast or slow wind days as described in Fig. 5.”
L312-313: You could move this up to L293 to set up the analysis discussion rather than note it at the end.
Section 4.5: the alpha parameter is confusing. In the previous section you just showed that deep convective cloud cover is not fixed, so why should we assume that it is fixed here. You can see that cirrus cloud fraction changes from the other analyses.
However, the other points here about the wind speed influencing whether or not the pass of Aeolus at 6LT "sees" the detrained cirrus is SUPER important.
L320-327: This should be in the domain section (2.3) so you can just refer back to that here instead of explaining it a few times throughout the paper
L338-340: I’m not sure its necessarily the cirrus clouds leaving a “trail” of ice crystals (which would themselves constitute a cloud), maybe: At speeds faster than 25 m/s, the cirrus clouds may have traveled beyond the Aeolus passover at 06 LT; however, we still see higher ice crystal concentrations likely due to the large spatial coverage/long lifetime of cirrus clouds
Section 4.6 Implications in a warming climate should be moved to the discussion section since none of this is a result from anything you are showing.
L355: “convective patterns AND locations”
L426: It might be useful to show this derivation in an appendix. Or provide a citation. Can you reasonably ignore the d/dx component of vorticity?
Figure 13: panel c has contour lines without a colorbar associated. At least say the increment between contour lines and if orange or purple is positive or negative.
L470: (on the order of days) your analysis seems to be only looking at 12-hour increments, so why not be specific here. Or did you look at 12 hr, 24 hr, 36 hr, 48 hr, etc.? |
General comment:
The manuscript by Titus et al. investigates the relationship between thin clouds, deep convective clouds and upper tropospheric wind structures over the Indian monsoon region using a synergistic cloud and wind profile dataset from Aeolus during the summer monsoon 2020 time period. They conclude that a higher occurrence of thin clouds over the Arabian Sea is associated with stronger westerly winds combined with higher amount of water vapor injected in the upper troposphere by deep convection over India and the Bay of Bengal.
They further show that the strength of the TEJ is mainly consistent with thermal-wind balance, but that the short-term regional variability of the TEJ is modulated by the outflow and divergence, vorticity perturbations caused by deep convection.
While Aeolus’s repeat cycle is usually 7-days, the authors benefit from the orbit configuration to have 12 hours between an ascending and descending orbit with spatial distances of 1150 km, which provides them the opportunity to study advection processes. This is unique for a single observing system.
The dataset is valuable and the topic is very relevant. The study addresses several interesting scientific implications, which are explained in detail. My only concerns are regarding the structural clarify in sections 3-5 plus a few minor comments.
Detailed comments:
The manuscript is clear and well written, the abstract, introduction and conclusion read very well and communicate the motivation and relevance of the study. However, I have several concerns regarding the structure.
While section 2 (Dataset and method) is very descriptive and easy to follow, sections 3, 4 and 5 present a mixture of observational findings (what does the data show us directly without interpretation), interpretations from these findings and hypothesis. Also, the subsection “method” re-appears in section 5 for the individual hypothesis about deep convection and the strength of the TEJ. This causes that the narrative reads as a sequence of results, observations, impacts and hypothesis with no clear logical hierarchy. I recommend separating the observational results, interpretations, discussion and conclusions, either globally, or if you like to keep the hypothesis-driven sectioning, also per section.
Section 5: Deep convection strengthens … This is more like a conclusion or hypothesis. Maybe rephrase title to “Impact of deep convection on TEJ strength over Arabian Sea”?
Section 4: I actually like the idea to already provide the conclusions with the title, but later, with 4.2.1 you refer to the role of temperature and 4.2.2. the role of opaque clouds. Maybe better call section 4: “Drivers affecting the occurrence of thin high clouds over the Arabian Sea” Then you go to 4.1. wind, 4.2. temperature and 4.3. opaque high clouds over India ? This is just a suggestion to make the order clearer.
The abstract is clear and well written, but you have some room for further details. You mention the Aeolus dataset, some results, numbers and implications, which is a nice structure for the abstract. One sentence about the methodology (disentangling the effects) would make it rounder.
The Sub-grid scale variability below the native resolution of Aeolus is not resolved by the merged and re-gridded cloud-wind dataset. You should add some sentence that this high-resolution dataset nicely compares to the resolution of CALIOP, but does not provide higher level of details compared to the native Aeolus resolution, which brings some uncertainties, especially with respect to the cloud top levels.
The manuscript reports convective perturbation wind components (u_conv) on the order of −1.7 to +1.3 m/s at the end of Section 5. However, no uncertainty estimate is provided for these values, nor is their magnitude discussed relative to the wind measurement uncertainty and derived thermal-wind uncertainty described in Titus et al. (2025). Without this context, it is difficult to assess whether the reported perturbations are robust and statistically distinguishable from dataset uncertainty. I recommend providing uncertainty estimates or at least add a reference of typical random errors of Aeolus Mie-cloudy wind and to compare them to the observed amplitude.
Minor technical comments: