This paper presents a multi-faceted approach for identifying aggregation and advanced riming leading to graupel formation using ground-based remotely-sensed observations from the DACAPO-PESO experiment in Punta Arenas, Chile. The paper is well-written and the figures are produced to a high quality. The analysis is thoroughly described and grounded in the literature. The results comprise four case studies, two indicative of riming of graupel and two of aggregation of low-density snowflakes in the absence of riming. My main comments are focused only on illustrating and highlighting the interpretation of the case studies with some changes to the figures and discussion of the results.

This is a high-quality paper, providing novel results based on recently-developed techniques, which help to better understand the remote-sensing signatures of key microphysical processes. I recommend this paper for publication in AMT, with only minor revisions.

Comments:

1. Each case study uses three figures illustrating: (Figure A) the time-series of zenith-pointing radar and lidar measurements, overlaid with temperature contours from the ECMWF analysis; (Figure B) RHI scans of SLDR and vertical distribution of the polarizability ratio from a short period within the case study, and (Figure C) Doppler spectra and profiles of reflectivity from a selected profile during the period relating to Figure B.
   
   
   
   The detailed discussion of the results requires frequent references to all of these figures, including specific height and temperature ranges, across the multiple figures, which each may have different ranges in the height axis.
   
   
   
   A few additional touches to the figures would greatly assist the reader in this cross-referencing and interpretation:
   • Please annotate on Figure A the time period of the RHI scans and profiles used in Figures B and C
   • On Figures B and C, please include information about the critical temperature ranges which help us to interpret which processes are most likely: I leave it to you to decide how to show this (e.g. duplicate y-axes, or an additional profile added to panel b) in both figures or an additional panel, or simply annotating selected height levels with the corresponding temperature)
   • When specific layers are frequently referred to in the text, consider annotating these layers in Figures B and C
   • Please also consider adding subtitles to the panels of each figure to assist the reader when jumping back-and-forth between figures. 

2. Some aspects of the interpretation of the case studies could be clarified and expanded upon:

1. In Section 4.1.2 the lowest layer is interpreted as “large aggregates…falling into a layer of supercooled liquid droplets and… forming smaller but more dense and isometric particles such as graupel”. The possible mechanisms for a decrease in the size of the particles are not commented on. Are the low-density aggregates breaking up during the riming process? Does the turbulence near cloud-base indicate mixing with sub-saturated air leading to sublimation-driven breakup?
2. In Section 4.2.1 the lowest layer, apparently containing spheroidal/low-density aggregates according to VDPS method (Figure 8b), is mostly discussed in terms of ruling out the presence of supercooled liquid and therefore of riming; however, the other observations characterising this layer include a very broad Doppler spectrum (Figure 9a) and indications of turbulence in the Doppler velocity (Figure 7c), as well as a rapid reduction of radar reflectivity (Figure 9b) toward cloud-base. Please comment on the interpretation of these features. 

Typos and minor comments:

• L4: “harsh atmospheric conditions such as the presence of orographic gravity waves”. Not sure if “harsh conditions” is the right word here; perhaps “adverse” with respect to Doppler-velocity based methods.
• L5-6: “Core of the approach…” could be either “At the core of the approach…” or “Core to the approach…”
• L39: “low” instead of “small density”
• L46: “...by a lack of a efficient ice nucleating particles…” may have a missing word or a typo here.
• L118: “...94-GHz radar and operates at 3.2-millimeter wavelength.” This is already implicit in the 94-GHz frequency, so could read more like “...94-GHz radar (3.2-millimeter wavelength).”
• L269: “...by the presence low values of…” missing “of”
• L300: should be “...provide evidence of…”

The Paper presents a case study analysis of ground-based cloud radar measurements for studying and identifying cloud microphysical growth processes. In this study, retrieval techniques and Doppler spectrum analysis are combined to identify and differentiate the microphysical processes. Overall, the paper is well written and contains well-presented figures supporting its hypothesis and findings.

My Main comments are related to improving the understanding of the paper and listed below.

Overall, this is an excellent paper that offers fresh insights derived from newly developed techniques, aiding in the understanding of remote-sensing signatures related to important microphysical processes. I endorse this paper for publication in AMT, pending only minor revisions.

Section 3.2:

Do you have questions related to liquid water attenuation correction? How do you localize liquid layers in your measurements? Additionally, how do you distribute the column-integrated retrieval information of the LWP from the microwave radiometer over the columnar measurements of the radar? Do you also apply this to the scans of the Mira35? Since liquid water correction of radar measurements isn’t a standard method, I would like to gain more insights into the process.

Section 4.

You mentioned that you use the LimRad94 Spectra to calculate the Ze values and other moments. Additionally, you utilize Doppler spectrograms for microphysical process analyses, as well as for detecting liquid layers and secondary ice production. Could you comment on how other noise clipping in the Doppler spectrum would influence your results? How did you set the noise threshold during processing? Providing such information would be helpful for the repeatability of these studies.

Section 4.1.1.

Line 250: Can you briefly explain in the text what a white bad is?

Section 4.1.2

Perhaps I missed it, but can you comment on why the Ze-time-height plot and the Ze e-profile of these cans show an increase in Ze from 4 to 3 km height? And why does there seem to be a minimum of Ze before the aggregation?

Section 4.2.1.

Line 339: I find it hard to identify the secondary mode in Fig. 9. Is the broadening of the spectra around 4 km really a second mode and not due to turbulence? Additionally, Figure 7c shows a large variation in the Doppler velocity field.

Overall comments related to figures:

Is it possible to also get grids in the RHI scan figures and the polarizability ratio profiles? Identifying the corresponding heights is not always easy. As an alternative, one could indicate the regions of interest using circles or letters.

Regarding the SLDR figures, the contrast of the plots is not the largest. Is it possible to use a color bar where the signatures you want to show are more prominent?