the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 May 2026
EarthCARE Observations of Vertical Motion and Cloud Microphysical Structure in Tropical Cyclones
Abstract. The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite mission provides the first spaceborne Doppler radar measurements, enabling new insights into the vertical structure of clouds and precipitation. In this study, we construct a dataset of EarthCARE overpasses of tropical cyclones (TCs) by collocating satellite observations with the International Best Track Archive for Climate Stewardship (IBTrACS). Based on 14 months of observations, we examine the radial structure of radar reflectivity, Doppler velocity, retrieved air motion, and cloud particle types. The results show a transition from convective-like structures in the eyewall to stratiform-like characteristics in the rainband region. The eyewall exhibits stronger updrafts, enhanced reflectivity, and broader Doppler velocity distributions. In contrast, the rainband region shows that weaker vertical motions and Doppler signals are more strongly influenced by hydrometeor fall speeds. We further evaluate TC simulations using the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) with two different cloud microphysical configurations of hydrometeor fall speeds. Both experiments reproduce the overall TC structure but exhibit more confined distributions of radar reflectivity, Doppler velocity, and air velocity compared to the observations. Differences between the two simulations highlight the sensitivity of vertical structure to hydrometeor fall speeds. These results indicate that EarthCARE Doppler observations provide valuable constraints on the coupling between dynamics and cloud microphysics in TCs.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-2530', Anonymous Referee #1, 29 Jun 2026
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RC2: 'Comment on egusphere-2026-2530', Anonymous Referee #1, 06 Jul 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2530/egusphere-2026-2530-RC2-supplement.pdf
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RC3: 'Comment on egusphere-2026-2530', Anonymous Referee #2, 14 Jul 2026
Review of "EarthCare Observations of Vertical Motion and Cloud Microphysical Structure in Tropical Cyclones"
Overall Assessment
This is a good and interesting manuscript that makes use of a novel observational dataset to characterize vertical motion and cloud microphysical structure in tropical cyclones. That said, I feel the analysis stops somewhat short of its potential, and a deeper treatment of several points below would substantially strengthen the paper's contribution.
Major Comments
- Model improvement pathway needs to be made concrete. The most compelling potential contribution of EarthCARE observations is their ability to improve model representations of TC processes, but this is not developed. For instance, on Line 433 the authors state that "the observational constraints offer guidance for improving the representation of cloud microphysical processes in models," but no specifics are given. I would strongly encourage the authors to elaborate on this point — what specific microphysical parameterizations or processes could be constrained, and how would one go about using these observations to do so? Even a focused discussion of one or two concrete examples would considerably strengthen the paper.
- Justification for single-moment microphysics. Why was a double-moment scheme not tested? NICAM does have a double-moment microphysics option available (see Seiki and Nakajima, 2014, J. Atmos. Sci., 71, 833–853, who developed the NDW6 double-moment scheme). The authors should clarify why they chose to test only a single-moment scheme — even if they also ran a sensitivity test with modified parameters — or, if feasible, discuss how the results might be expected to differ under a double-moment or even bin microphysics representation.
- Imprecise language in places. For example, on Line 418 the text states "with a long tail extending toward 1 g/m³ (Fig. 11a)," but the figure appears to show the distribution extending beyond 1 g/m³. Please review the manuscript for similar instances where the wording does not accurately match what is shown in the figures.
- Sample size should be reported. How many individual tropical cyclones were sampled in this study? This is arguably more important for assessing the robustness and generality of the results than the time period of the dataset, which is currently the only sampling information provided.
Specific/Editorial Comments
- L40: "suggesting that rapid intensification may be a precursor to TC intensification" — this phrasing is circular/redundant and should be rephrased.
- L63: Is TC rapid intensification really absent in coarser-resolution models? Please provide a citation to support this statement.
- L68: "in Roh et al. (2026) they argued" should be revised to "Row et al. (2026) also argued."
- L210: "Between 5–10 km, a mixture of ice and liquid phases exists"Â
- L254: "by particles falling" should replace "the particle falling."
- L455: "although uncertainties remain in the retrieval" — can the authors quantify these uncertainties, even approximately?
Citation: https://doi.org/10.5194/egusphere-2026-2530-RC3
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This paper presents analysis of EarthCARE Doppler velocity measurements that coincide with identified tropical cyclones. It combines EarthCARE measurements and a tropical cyclone tracking dataset to evaluate dynamical and microphysical properties of tropical cyclones.Â
Considering the novelty of this type of data, I think this work has the potential to be impactful. The paper would benefit from reframing of the problem and clearer presentation of data to support the conclusions being made. My main suggestion is to highlight the parts of the study that are novel. For example, the abstract states that the results show a transition from a convective-like structure in the eyewall to a stratiform structure in the rain band. While it is useful to confirm that the orthodox picture of tropical cyclones holds when evaluating it against global Doppler velocity retrievals, the strength of the dataset is that new or uncertain relationships can be evaluated. Moreover, the main value of the data is that it provides global measurements of the "coupling between dynamics and cloud microphysics in TCs", but the conclusions made about the coupling are presented with either weak or unclear evidence. In the following review, I point out places where I suggest the paper should be reframed and strengthened.
- L47: How do you know that "the presence of supercooled liquid water has important implications for latent heat release in the upper levels."? The latent heat of freezing is an order of magnitude smaller than the latent heat of condensation/deposition, so there would need to be significantly more supercooled water freezing than other types of latent heat release for it to contribute a lot to TCs.Â
- Lines 46-56 summarize an open problem in the field that I think this paper may address. The summary states that there has been some prior work examining how supercooled water in the upper parts of the tropical cyclone impacts TC intensity, but there is disagreement about whether or not supercooled water exists in large quantities there. It seems to me that the EarthCARE data presented in this work can both evaluate whether the supercooled water exists in large quantities (compared to other condensate) and whether the presence of supercooled water impacts the intensity of the TC. (Whether it impacts the vertical velocity or maximum radial wind.)
- Fig. 2: I'm unclear on how these figures are generated. Do you collocate the TC, then take the average radar reflectivity given by EarthCARE over the portion of the TC that EarthCARE crosses? Then bin the resulting 1D profile by the RMW of the TC? If that is indeed the methodology, then how do you deal with the following two cases: (1) the EarthCARE satellite passes 900 km away from an RMW=10 tropical cyclone, in an area where there is just stratiform precipitation and (2) the satellite passes through the center of an RMW=10 tropical cyclone? In Fig. 2b, would these two profiles get averaged together? The method you use should be clearly presented in the paper.Â
- The second sentence in Section 3.1 states that sufficient number of samples exist for RMW ranging from 2 to RMW. The next sentence then draws a conclusion about RMW<2. Since the number of samples is low there, it is unreasonable to draw conclusions about those results.Â
- I don't see why this is true: "A relative minimum in reflectivity at 5 RMW suggests a separation between the primary and outer rainband regions." What other evidence do you have, or prior work, shows this?Â
- It looks like air velocity is positive everywhere in the tropical cyclones that you observe, according to Fig. 2b. Is that what you expect? Why is that?Â
- Fig. 3 b-d. Is the probability distribution normalized by each row, or is this a two-dimensional histogram? Should we interpret these figures as the probability density of the doppler velocity at 5 km, for example? Moreover, when you write Eyewall-Outer and rainband-Outer, do you mean that you compute the PDFs of each, then subtract the PDFs?
- "Above 6 km, enhanced reflectivity is generally associated with Doppler velocities below the upper quartile, suggesting that Doppler velocity in the rainband is contributed by the particle falling" Isn't Doppler velocity always impacted by falling hydrometeors? What is this statement attempting to distinguish about the rainband?
- "We eliminate the points where sample size less than 5." That's a very low threshold. How does increasing this impact the results?
- Fig. 6. It may be worth emphasizing that this probability density plot differs from the other types of probability density plots you showed. It looks like the probability is normalized by column here, which is not the case for the others (like 3 or 7). Are we to interpret each column as the probability density of (in (a), for example) small ice particles occurring at each height, binned by the RMW? This plot is also missing labels on the x axis and color bar.
- Why not plot Fig. 7 with air velocity instead of Doppler velocity on the x axis? It seems to me that you are aiming to relate condensate and air motion in the text, so the figure might support your conclusions better if it used air velocity.
- "In particular, the occurrence of supercooled water and mixed-phase particles in regions of upward motion implies that riming processes are likely enhanced within convective updrafts, where supercooled liquid water is available." This sentence is stated in reference to Fig. 7, which combines all the data, whether it was taken at the eyewall or rainband. Since that's the case, it is unreasonable to make conclusions specifically about convective updrafts based on this figure. Is it possible to subset to only the convective part of the storms to evaluate your hypothesis? Is it possible to show that riming is more important than other condensate formation processes?
- Fig. 7d shows the two-dimensional histogram of supercooled water. It looks like supercooled water is most prevalent when the dopper velocity is highest. The claim that supercooled water is more prevalent than expected would be stronger if there was a clearer comparison of the relative frequencies of the different type of particles.Â
Minor comments
- Typo in affiliation 1: Atmoshpere -> AtmosphereÂ
- Typo in correspondence name: Hunag -> Huang
- L42: This sentence is unclear, should rephrase: "The above studies demonstrated a breakthrough in TC understanding using CloudSat observations despite only radar reflectivity"
- L48: Should be past tense, and phrasing is unclear: "Therefore, supercooled water is regarded as the target to weaken TC structure and intensity by seeding during STORMFURY (Willoughby et al., 1985)." Is this saying that the goal of the campaign was to reduce the amount of supercooled water in storms?
- I suggest editing the text for clarity.Â
- Fig 2a: The color bar chosen here makes it hard to distinguish small and large values.
- Fig 7: hard to see the black line on dark blue background
- Fig. 10, 11: hard to see the tick labels
- How many samples are there? How many TCs did EarthCARE intercept over the 14 month period?Â