General Comments: To demonstrate the utility of the newly available EarthCARE data, the authors in this study investigate the EarthCARE CPR radar measured Doppler velocity in convective and stratiform precipitating clouds and interpret it in relation to precipitation growth processes. The uniqueness of this study is the combined use of both EarthCARE CPR and GPM DPR data, which allows the authors to explore the difference of particle growth processes in stratiform and convective clouds. The paper seems to serve 2 purposes: First, it demonstrates the quality and usefulness of the first-ever space-borne cloud radar Doppler velocity measurements, and second, using the Doppler velocity measurements, it confirms some of the understandings on microphysical processes in convective and stratiform clouds. The paper is well structured, and the messages are well presented.  It will be a good contribution to this special collection of papers on EarthCARE. I suggest accepting after addressing some minor concerns.

Specific Comments:

1.  Doppler velocity Vd in the EarthCARE product. In the manuscript, the authors stated that the Doppler velocity in the EarthCARE product is derived from “the phase shift of the radar signal and is therefore less affected by attenuation”. I understand that the retrieval of Vd is not the focus of this paper, but I do like to see a brief explanation on this topic in the  Data and Methods section. Because many of the cases involved in this study are related to moderate to heavy rainfall, CPR should suffer significant attenuation particularly for the rain portion in the vertical profiles. Are there any studies on the impact on Vd retrieval accuracy by attenuation when using phase shift method?
2. 10 km horizontal integration. Please explain the reason for 10 km integration for EarthCARE data. The DPR footprint size is about 5 km, then you have to average 2 DPR pixels to match 13 (=10./0.75) EarthCARE pixels? Is there a reason not using ~7 EarthCARE pixels to match 1 DPR pixel? Will the results be different if do so? In short, the decision to use 10 km seems to be somewhat arbitrary, may need couple sentence to justify.
3. The use of temperature as vertical coordinate. The use of temperature as vertical coordinate is an interesting way to investigate microphysical processes. However, there is a shortcoming when global data are mixed into one figure such as Figure 4. I suspect that most of data near 20C are from tropics or warm season mid-latitudes. In the meantime, data near 0C are from almost all the places. When we put all data into one figure, explaining the features in a way that particles are falling from aloft to lower part is somewhat misleading. I’d like the authors mention this shortcoming, and remind readers that future studies should separate data into groups with similar temperature range in the vertical.
4. Just a comment. It is great to see in Figure 5 that Vd in the cold range (-10C) is around -1 m/s and the derived Vt is matching well with measured Vd. This gives us great confidence that the Vd quality is high.
5. Misc.

Line 55. “The Tropical … (TRMM) was launched in 1997, and the TRMM carried …”.  I think it is better to say: “The Tropical … (TRMM) satellite was launched in 1997,  and it carried …”  

Line 105.  I don’t see “CSATGPM” appearing in any place before this point. Please define it.

Line 137. The exclusion of 5 and 10 range bins are somewhat arbitrary. Are they about 0.5 and 1.0 km, respectively? Please add a couple of sentences to explain why excluding these many bins is enough.

Line 164-165. Earlier in the text, it is mentioned that EarthCARE data is integrated to a 10 km “pixel”. Here it sounds like the matching is between 1 EarthCARE original pixel (750 m size) with 1 DPR pixel (5 km size). Please clarify.

Line 276-277. Do you have a rough number of profiles (in percent) that is detected by CPR but not DPR?

 Figure 6. An interesting feature is that most stratiform precipitation tops (by DPR) are around -15C although their cloud tops (by CPR) are all over the place. Any explanations?

Line 447. “theoretical W-band terminal velocity”  ->  “theoretical terminal velocity”. Terminal velocity should not be band-dependent.

This work analyses Ku-, Ka-, and W-band radar measurements of precipitating clouds using a one-year dataset of matchup EarthCARE and GPM observations. Following a quick demonstration of two case studies, statistical properties of radar reflectivity and Doppler velocity profiles are investigated for different particle phases (liquid/solid) and different precipitation types (shallow/convective/stratiform). A new method is devised to evaluate the vertical air motion in raining layers by subtracting the terminal velocity deduced by DPR-derived DSD from the EarthCARE Doppler velocity. 

This is a well written paper presenting robust analysis results that align with theoretical expectations and physical intuition. The authors' effort to construct a matchup EarthCARE and GPM dataset should be applauded and will be welcomed by the cloud/precipitation science community. I suggest a few revisions that are mostly minor in nature with the possible exception of the first point. Otherwise I would recommend that the paper be published in AMT.

Main comments --------------------

1. JAXA's EarthCARE CPR Level-2 cloud product (L2a CPR_CLP) contains its own vertical air motion estimated from Doppler velocity. The CPR reflectivitiy (and hence DSD estimates crucial for V_t and V_air as well) is subject to heavy attenuation for intense rain as the authors pointed out (ll. 210-211). That being said, a substantial number of CPR reflectivities would be still usable, being not entirely washed out by attenuation even beneath the 0-degree level as far as I can tell from Fig. 2c and 3c. This means that there would be plenty of simultaneous measurements available for both EarthCARE-provided V_air and GPM Dm estimates.

I am curious how consistent the V_t estimates are between the CPR standard product and the current method using DPR-derived DSD. You would find discrepancies because the CPR_CLP relies on its own built-in DSD assumption which is not guaranteed to accord with DPR Dm. An additional plot or two comparing the CPR-only and DPR-based V_t and V_air estimates would tell us how reliable the CPR products are, offering useful information for EarthCARE algorithm developers and interested users.

2. In the paper, V_t and V_air are shown only for rain layers (Fig. 10). Why not add V_t and V_air for solid precipitation too (Fig. 9)? The DPR Dm might not be as reliable for snow as for rain because the KuPR is not sensitive enough to small frozen hydrometeors, but a comparison with the CPR_CLP product would be worth studying for solid precipitation as well.

Specific points -----------------

3. l. 55: and The TRMM -> and the TRMM

4. l. 73: weaker hydrometeors -> smaller hydrometeors

5. l.135: are more frequently appear -> more frequently appear

6. ll. 144-146: I am puzzled by the claim that "only data from the HS mode are used". The KaHS mode has been reassigned to match the outer KuPR swath to complement the inner KaMS swath since the scan pattern was changed in May 2018. As far as I can tell from Figs. 2 and 3, the whole DPR swath (that is, both MS and HS modes) seems to be analysed in this work.

7. l. 153: which calculated -> which were calculated

8. l.156: "equatorial" region may be better replaced by low- and mid-latitude regions. 65S-N is much wider than the equatorial region.

9. l. 170: samplings -> samples

10. Figure 4c/d: Why are the KuPR and KaPR CFEDs sharply (presumably artificially) cut off above a certain level, with a temperature threshold around -42C for Ku and -35C for Ka?

11. l. 303: "However" does not really fit the context here. Please try "On the other hand" or "In contrast" instead.

12. Figure 6: The joint histogram of Ku- and W-band Z reminds me of Fig. 8 of Stephens and Wood (2007, DOI: 10.1175/MWR3321.1). They showed CFADs separated for different cloud types, which also bears resemblance to the present work. I just thought this might be worth a brief discussion.

13. l.375: "Intense" deep convection (DC-I) could be misleading, given that higher echo tops do not necessarily guarantee more intense convection (e.g., Hamada et al., 2015, DOI: 10.1038/ncomms7213). Something like Tall deep convection (DC-T) may be a safer alternative.

14. l. 394: is generally low -> are generally low

 

15. l. 415: Here again, "However" may be better rephrased by "By contrast" etc.