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Article
Peer-Review Record

Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset

Remote Sens. 2021, 13(12), 2264; https://doi.org/10.3390/rs13122264
by F. Joseph Turk 1,*, Sarah E. Ringerud 2,3, Andrea Camplani 4,5, Daniele Casella 5, Randy J. Chase 6,7, Ardeshir Ebtehaj 8, Jie Gong 3,9, Mark Kulie 10, Guosheng Liu 11, Lisa Milani 2,3, Giulia Panegrossi 5, Ramon Padullés 12,13, Jean-François Rysman 14, Paolo Sanò 5, Sajad Vahedizade 8 and Norman B. Wood 15
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Remote Sens. 2021, 13(12), 2264; https://doi.org/10.3390/rs13122264
Submission received: 30 April 2021 / Revised: 6 June 2021 / Accepted: 7 June 2021 / Published: 9 June 2021
(This article belongs to the Special Issue Remote Sensing of Precipitation at the Mid- to High-Latitudes)

Round 1

Reviewer 1 Report

The review report is shown in the attached file.

Comments for author File: Comments.pdf

Author Response

We have replied to each point in the review in the attached PDF.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments in the attached file

Comments for author File: Comments.docx

Author Response

We have responded to each point of the review in the attached PDF.

Author Response File: Author Response.pdf

Reviewer 3 Report

This paper demonstrates the applications of CloudSat-TRMM and CloudSat-GPM satellite coincidence data sets in precipitation issues. As learned from the whole manuscript, it is well written and organized. It fully satisfies the scope of Remote Sensing. I would like to accept it in its current form for publication in the journal of Remote Sensing.

Author Response

Thank you for your review of this manuscript.

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