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Review
Peer-Review Record

Polarimetric Radar Quantitative Precipitation Estimation

Remote Sens. 2022, 14(7), 1695; https://doi.org/10.3390/rs14071695
by Alexander Ryzhkov 1,2,*, Pengfei Zhang 1,2, Petar Bukovčić 1,2, Jian Zhang 2 and Stephen Cocks 1,2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Remote Sens. 2022, 14(7), 1695; https://doi.org/10.3390/rs14071695
Submission received: 21 February 2022 / Revised: 26 March 2022 / Accepted: 28 March 2022 / Published: 31 March 2022
(This article belongs to the Special Issue Radar-Based Studies of Precipitation Systems and Their Microphysics)

Round 1

Reviewer 1 Report

This study presents a review of existing polarimetric methodologies for rain and snow estimation and their operational implementation. Overall, the review is of high value to the both the science and practice. I only have a few minor comments as follows. And I suggest acceptance after minor revision.

Minor comments:

L38 to 40: ‘The advantages of polarimetric radar measurements for rainfall estimation have been demonstrated in a number of research studies back in the nineties and early 2000s.’ I suggest referencing a couple examples (not an exhaustive list) of the important studies here. It is a bit odd to have specified the content and times of the previous studies without actually citing them.

L104: ‘more’ instead of ‘stronger’.

Figure 1-3: The greyscale plots hardly show any difference between R(Z) and R(Z, ZDR). It is hard to tell the scatters of R(Z,ZDR) is narrower than R(Z), like what is claimed in Line 114. A suggestion is perhaps to calculate and show R2 for all scenarios and it would be much clearer.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

Specific comments are attached.

Comments for author File: Comments.pdf

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 3 Report

Review of “Polarimetric radar quantitative precipitation estimation”

The manuscript reviews extensively the topic of radar-based quantitative precipitation estimation (QPE). The QPE algorithms of liquid phase from R(Z), dual-polarization QPE and R(A) were introduced. The various forms of snowfall rate estimation and the challenges were discussed as well. The issues of vertical profile correction using various form of VPR were shown as well. Finally, the combination of various forms of QPE algorithms using MRMS technique. The manuscript well documents the development and the current status of QPE in US. The manuscript is well written and only need some minor revision.    

 

Minor comments:

  1. Most of the QPE algorithms and examples are from US, it will be more appropriate to revise the title or make a clear statement in abstract or introduction.
  2. The development of various QPE algorithms from Z(R), dual-pol QPE to R(A) QPE were introduced in the manuscript. Yet, the systematic comparison of these QPE algorithms was not shown in the manuscript. A table to summarize the performance of these QPEs is strongly recommended.
  3. In the vertical profile correction, there are various techniques, namely VPR, PVPR, dpVPR, til-VPR, QVP, EQVP and more, to obtained the vertical profile. Can author make an overall comment of these techniques? Which one is better?
  4. In the end, what is the performance of MRMS? Can author provide quantitative scores?

Author Response

Please see the attachment

Author Response File: Author Response.docx

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