the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation of EarthCARE retrievals of ice microphysics and vertical wind using in-situ aircraft observations
Abstract. The novel observational capabilities of the EarthCARE satellite promise the most accurate retrievals of the vertical profile of ice clouds yet achieved from space, but independent evaluation is essential. In this paper we use in-situ sampling from five underflights of EarthCARE in ice clouds between -10 and -45 °C during the UK "VERIFY" and Canadian "ECALOT" campaigns to evaluate and improve its microphysical and vertical-wind retrievals, as well as testing prior assumptions such as the mass–size relationship and the radar ice scattering model. We find that, to a good approximation, the small-scale fluctuations in radar-measured Doppler velocity can be attributed to vertical wind and the larger-scale averages to ice terminal fall speed. When EarthCARE’s "C-CD" algorithm is updated to exploit this finding, its vertical wind retrieval is able to capture the amplitude and phase of gravity waves measured by the aircraft. Retrievals of IWC and extinction by the radar-only "C-CLD" algorithm, the lidar-only "A-EBD" algorithm and the synergistic "ACM-CAP" algorithm, are in good agreement with the aircraft but highlight the important challenge of retrieving ice particle density. Comparing the 94-GHz radar reflectivity observed by EarthCARE with values computed from the aircraft probes enables us to successfully validate the Self-Similar Rayleigh-Gans scattering model even when non-Rayleigh scattering reduces the reflectivity below the equivalent Rayleigh value by 15 dB. However, the calculations of reflectivity-weighted terminal fall speed from the aircraft are systematically 15–30 % higher than measured by EarthCARE’s Doppler radar, suggesting the need for further work on models of ice fall speed.
Competing interests: PK is a member of the editorial board of Atmospheric Measurement Techniques. RH and DD serves as editor for the special issue.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-5054', Alain Protat, 29 Sep 2026
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RC2: 'Comment on egusphere-2026-5054', Anonymous Referee #2, 30 Sep 2026
The authors evaluate in this manuscript recent EarthCARE retrieval products of ice microphysics and vertical wind using aircraft in-situ data from five underflights collected during different aircraft campaigns.
Overall, I find the paper very well written and an important study for the evaluation of the new EarthCARE retrieval products. It really highlights the potential and quality of the new global satellite dataset. I have a few comments, suggestions, and questions which I would like the authors to address. I think the paper needs some revision before it can be published.
Major Comments:
One of my major concerns regarding the analysis is that uncertainties of the airborne observations and EarthCARE retrievals are not properly discussed. From many previous publications and conference presentations I got the impression that airborne in-situ data (for example IWC) from different probes measuring the same cloud can quite significantly deviate from each other. Considering the multitude of previous aircraft campaigns, are there no uncertainty estimates available for these basic quantities like IWC, PSD, or vertical air velocity? I understand that uncertainty estimates might be difficult to derive from such complex probes but as a reader, I would at least like to know a rough number. The only uncertainty value I found was the 50% IWC uncertainty for particle “rebound” (L. 75-77). While 50% is already quite big in my opinion, I wonder what is the total uncertainty in IWC? And how much more uncertain are more “difficult” quantities, such as PSD? Similar arguments also apply to the EarthCARE retrievals. How big are the uncertainties and how do they compare to the differences between EarthCARE and aircraft data (or forward simulated radar quantities)? I assume the ESA retrieval products do contain some uncertainty estimates, so why are they not discussed or shown?
Many acronyms for retrieval products and instruments are used in this study. They are properly introduced and explained but it might be convenient for the reader to have a list of acronyms and abbreviations provided at the end.
Specific comments and typos:
L. 32: “radar reflectivity at the level of the aircraft” What is the blind range of the airborne radar? I guess it is not zero, hence the first useable range gate will not be exactly at flight level.
L.32-33: Please specify what is meant with “significant amounts of supercooled water”. What threshold was used? At L. 55 you state that cases with any SLW were excluded. What is the sensitivity level of the airborne SLW probes? It should also be noted that absence of SLW at flight level does not guarantee SLW-free conditions elsewhere in the cloud. Wouldn’t it be possible to use the PIA of the airborne W-Band radar as indicator of SLW? Or was the aircraft equipped with a microwave radiometer?
L. 36-37: I am a bit confused: You mention that Z94 is sensitive to mass-size relation and scattering assumptions. I completely agree. But I don’t understand how you can distinguish the effect of each of them by comparing measured and forward simulated Z94? You have two unknows and only one observable.
L. 69: A reference for the anti-shattering algorithm should be provided.
L. 73-74: Why exactly 50%? A reference for this value should be provided. As you mention in the next sentence, the grey band in the figures show this potential 50% uncertainty. But how accurately is this known? Can’t the rebounding error be dependent on the particle properties you are probing. What other error sources or uncertainties are known for the Nevzorow probe?
L. 89: Couldn’t the m-D relationship also be strongly altered by the ice particles having simply a different shape (e.g. columns vs plates)? Does the density factor in the end account for shape and riming effects?
L. 95-100: Why is A(D) not dependent on fp? Increasing riming will also have an effect on the cross sectional area, or?
L. 102: Is Dm simply the mass median diameter?
L. 109: What is meant with “all radar frequencies”? Aren’t you only simulating W-band in this manuscript?
L. 115-117: Shouldn’t the SSRGA coefficients also depend on the density factor df (see for example study of Maherndl et al., QJ, 2023, https://doi.org/10.1002/qj.4573)?
L. 133: Please specifiy what “some horizontal averaging” means? Is the horizontal averaging window adjustable? In which range?
L. 139: What is meant by “geophysical variability”? Changes in particle properties and vertical air motion? Please specify.
L. 145: Consider including a reference to the section you are referring to.
L. 198: “how whether”
L. 369: Did the authors consider to test other hydrodynamic models, such as Böhm 1992? For example, in Karrer et al., JAMES, 2020 (their Fig. A2, https://doi.org/10.1029/2020MS002066 ) the Heymsfield-Westbrook-2010 model shows the highest estimates for sedimentation velocities of synthetic particles (especially for larger sizes which will dominate reflectivity weighted Doppler velocities).
Citation: https://doi.org/10.5194/egusphere-2026-5054-RC2 -
RC3: 'Comment on egusphere-2026-5054', Anonymous Referee #3, 05 Oct 2026
This manuscript describes validation of EarthCARE Level 2 products of ice microphysics and vertical wind using 5 flights installing in-situ cloud sensors.
EarthCARE/CPR is first sensor that can observe vertical Doppler information of clouds from a satellite. Data processing algorithms to estimate ice cloud microphysics and vertical air-velocity has been developed using Doppler information, so far. However, as to evaluate those accuracy, in-situ observations using airplane under satellite is necessary. This paper shows not only accuracy of those products but also difference between estimated cloud microphysics and in-situ measurement. I think this paper is very valuable for algorithm developers and data users, because it shows several problems of current algorithms and useful suggestions for new algorithm developments.
I judge that this paper is acceptable for publishing as it is. However, I will give some minor comments for your reference.
1. EarthCARE data products and processing algorithms are not familiar to almost all readers. It is useful to show the table of level 2 data processing (C-CD, C-CLD, A-EBD, ACM-CAP) including its products and its release version used in this paper. I think data processor version is very important because results may change with algorithm version. Please add some explanation about version such that first letter shows major version and second letter shows minor version on “BD-baseline version” “BA data product baseline”
2. Latitude is used for horizontal axis in all figures. But I think it is more comprehensible to use distance from satellite passing. I also want to know rough time difference between satellite and airplane observation.
3. Doppler velocity and estimated vertical velocity in VERYFY2 and ECALOT6 show very good agreement to airplane measurement and show gravity-wave-like perturbation. I am surprised by these agreements because I thought the vertical velocity measurements from the airplane were difficult and less accurate. Are there any inferences on cause of gravity waves? Mountain topography?
Citation: https://doi.org/10.5194/egusphere-2026-5054-RC3
Data sets
Colocated EarthCARE retrievals and aircraft in-situ measurements of ice clouds (Version 1.0) R. J. Hogan et al. https://doi.org/10.5281/zenodo.22043988
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