the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 30 Jun 2026
Characteristics of multiple-trip echoes observed by EarthCARE Cloud Profiling Radar
Abstract. Observations from the EarthCARE Cloud Profiling Radar (CPR) frequently contain spurious cloud signals caused by mirror images, multiple-scattering (MS) tails, and satellite mirror images (SMIs). These multiple-trip echoes are produced when transmitted radar pulses follow longer-than-nominal propagation paths and return within the reception window of subsequent pulses. Distinguishing and removing them is essential for scientific analyses using CPR observations. This study characterizes global properties of the multiple-trip echoes and evaluates the performance of the identification methods implemented in the JAXA Level 2A CPR one-sensor Echo product (CPR_ECO). For mirror images and MS tails, we adopt modelling approaches previously proposed for CloudSat-based analyses, whereas for SMIs we introduce a new method that exploits their characteristic altitude and Doppler-velocity signature associated with line-of-sight satellite-velocity contamination. Evaluations using collocated Atmospheric Lidar (ATLID) measurements, which provide CPR-independent cloud-top information, objectively show that the method properly identifies most of the multiple-trip echoes. Global statistical analyses using the identification flag reveal distinct geographical distributions, seasonal variations, vertical structures, and surface-state-dependent occurrence conditions among the three echo types. Mirror images are the most frequent type, and their distribution broadly follows cloud occurrence, with a preference for ice-free ocean. MS tails are concentrated in tropical and subtropical convective regions under strongly attenuating conditions. In contrast, SMIs occur almost exclusively over surfaces with near-saturated backscatter, such as melting sea ice and land with surface-water cover. These results provide a basis for improving multiple-trip echo identification and for addressing overlap cases in which spurious echoes contaminate genuine cloud signals.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-3256', Anonymous Referee #1, 01 Jul 2026
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RC2: 'Comment on egusphere-2026-3256', Anonymous Referee #2, 25 Jul 2026
This manuscript describes various type of range-ambiguous signal that can affect the EarthCare Cloud Profiling Radar (CPR) data. The authors categorize these signals into three different types: mirror image and multiple scattering, which have been seen previously, as well as the satellite mirror image (SMI). When I was first reading about the SMI, I was somewhat skeptical that the satellite backscatter could be large enough to still be detectable after another round trip to earth’s surface. However, the evidence presented seems convincing; I do have a couple of questions listed below. In general, the paper is well-written and provides important characteristics for each of the ambiguous sign types. I think it can be of strong interest to users of the EarthCare CPR data. I have some specific comments below.
Line 44: “widow” -> “window
Line 75 – regarding the SMI, have the authors tried to estimate the SMI signal strength by assuming some reasonable radar cross section for the satellite? Also, was CPR ever operated prior to establishing exact nadir pointing, which would preclude SMI, as the authors note (line 78)? See also comment on line 216.
Line 164 – The assumed k-Z relationship is for cirrus clouds. However, I’m assuming a large amount of the attenuation in Figure 2 comes from stratiform precipitation, which likely has a different k-Z relationship. How sensitive are the results to the assumed k-Z relationship?
Line 169 - My initial interpretation of (4) was that it is the level of a desired signal to the level of mirror image (like SNR). Hence, I was puzzled by the next comment, suggesting that SMR depends on the ability to estimate the MI return. It seems like (4) is more of an error measure of the deviation between the observed Z at a given height and the predicted Z_MI at that height. The algorithm identifies small SMR as mirror image. It seems like an observed Z well below the predicted Z_MI would also be identified as MI - could this result in the removal of real high-altitude Z? How accurate does the predicted Z_MI need to be?
Line 197 - what is the physical interpretation of the height h_c ?
Line 216 - Can the typical echo power be replicated by a model that included the path attenuation, ocean reflection coefficient, and satellite radar cross section? Also, please elaborate on the idea of H_SMI being independent of PRF. In the case Hsfc=0, H_SMI = -H_sat mod Ru. This is independent of PRF because PRF depends on H_sat? This would suggest that PRF depends on 1/H_sat... In short please clarify the SMI at 2.4 km, independent of PRF.
Line 225 - what is V(H_sfc)? - actual surface motion, as in ocean?
Line 295 – should the ending phrase be “regardless of whether CTH_ATL are evident or not” ? Or maybe an alternative is “independent of the value of CTH_ATL”.
Line 309 – Figure 9 is referenced prior to Figure 8. It looks like a typo and should be Fig 7b.
Line 333 and Figure 8 a and b – why do the MI clouds appear to come down to a lower level in the 18 km mode than in the 16-km mode?
Line 354 and Figure 9 – I’m not clear on why the fraction color bars go either to 1 or 0.25. Please clarify.
Line 422 – The sentence starting with “As implied …” is not clear to me. It seems that MI does not occur either with low sigma0 (surface reflectivity) or high attenuation, but I’m not clear on how that relates to the occurrence frequency of cloud echoes in Fig. 11b.
Line 453 – the lowest possible MI altitude – this is computed for each Z profile in Figure 8 using CTH_ATL. Is that true here as well?
Citation: https://doi.org/10.5194/egusphere-2026-3256-RC2 -
CC1: 'Comment on egusphere-2026-3256', V. Shcherbakov, 30 Jul 2026
To my knowledge, satellite mirror images (SMIs) were not reported in the literature before the work DOI: 10.5194/egusphere-2026-3256. Therefore, comprehension of that effect is of importance. Whereas the experimental data (Fig. 3) are convincing, presented by the authors explanation of properties of Doppler velocity (Fig. 3c) is far from being sufficient.
I assume that V(H_fsc) and V_Los of Eq. (7) are dopplerVelocityAtSurfaceBin and satelliteVelocityContamination values, respectively, of CPR L1b Level 1 Product (see URL: https://www.eorc.jaxa.jp/EARTHCARE/data/L1/CPR_NOM_e.html; last access 29 July 2026). Accordingly, the properties of V_SMI follow the properties of those two parameters. In my opinion, the properties of V(H_fsc) should be dominating.
According to Fig. 8 of the work DOI: 10.5194/egusphere-2025-4819, the measured Doppler velocity at surface is on average within the range [-0.4, 0,3] m/s. According to Fig. 4 of the work DOI: 10.5194/amt-18-5607-2025, EarthCARE CPR antenna mispointing leads to Doppler velocity bias within the range [-0.2, 0,8] m/s. Consequently, the data of Fig. 3c are really exceptional and the authors must propose a working model aiming to explain observed properties.
First of all, that working model must give reliable ideas explaining why V_SMI (I suppose that V(H_fsc) as well) fairly increases with latitude decreasing / longitude increasing. Moreover, the increase is so high that the jump, which corresponds to doubled Nyquist-velocity, is observed at a latitude of about 78°. Roughly, the increase in V_SMI and V(H_fsc) is about 10 m/s.
According to the authors (lines 21 -22) “… SMIs occur almost exclusively over surfaces with near-saturated backscatter, such as melting sea ice and land with surface-water cover.” Conditions of melting sea ice or land with surface-water cover can be associated with the specular reflection in non-uniform beam filling (NUBF) conditions. Accordingly, the question is: how NUBF, which is statistically homogeneous, can lead to the linear increase of V_SMI and V(H_fsc) in Fig. 3c?
There is another possibility related to the fact of the “near-saturated backscatter”. The SMIs data in Fig. 3 could be an artefact due to the CPR electronics operating in near-saturated conditions. The authors should provide explanations why the possibility of the electronics artefact was discarded.
Citation: https://doi.org/10.5194/egusphere-2026-3256-CC1
Data sets
EarthCARE/CPR L2A CPR one-sensor Echo Product (CPR_ECO) JAXA https://doi.org/10.57746/EO.01jdvd0xm10ema4rxwbpcd0dn1
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This paper provides a clear and comprehensive description of second- and multiple-trip echoes in EarthCARE observations. It proposes practical methods to identify and screen these echoes while thoroughly characterizing their vertical and zonal distributions. Very interesting to see also the discussion about the satellite mirror, the first time this is seen in cloud spaceborne radars. Overall, the manuscript is very well written, with clear figures, a logical structure, and well-supported arguments. I have only a few minor comments that I believe would further improve the paper.
1) Figure 1 and explanation of SMI height
In Figure 1, the term nR_u appears, but the parameter n is not defined. Please clarify its meaning in either the figure or the caption. In addition, in Lines 215–218 you explain why, over ocean surfaces, the SMIs consistently appear near H_SMI = 2.4 km regardless of the pulse repetition frequency (PRF). Since this is not immediately intuitive, especially for readers who are not familiar with radar principles, I think a simple timing diagram (chronogram) would be very helpful to illustrate this behavior.
2) Line 23, The phrase "surfaces with near-saturated backscatter" is somewhat vague for readers who are not familiar with Cloud Profiling Radar (CPR) observations. It would be helpful to provide a more quantitative description, for example by indicating an approximate σ⁰ threshold corresponding to near-saturated backscatter.
3) Figure 13: I suggest placing slightly more emphasis on the feature shown in Figure 13e over the tropical region. The persistence of reflectivities around −20 dBZ near cloud top, rather than decreasing toward the CPR sensitivity limit, appears to be a clear indication that second-trip echoes have not been completely eliminated or separated from the genuine cloud signal. Have the authors considered subtracting the extrapolated multiple-scattering tail from the observations? It would be interesting to assess whether such a correction recovers a more expected behavior in the figure.