Articles | Volume 13, issue 3
https://doi.org/10.5194/amt-13-1227-2020
https://doi.org/10.5194/amt-13-1227-2020
Research article
 | 
13 Mar 2020
Research article |  | 13 Mar 2020

Unsupervised classification of vertical profiles of dual polarization radar variables

Jussi Tiira and Dmitri Moisseev

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Jussi Tiira on behalf of the Authors (17 Nov 2019)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (04 Dec 2019) by S. Joseph Munchak
RR by Anonymous Referee #1 (20 Dec 2019)
RR by Anonymous Referee #2 (21 Dec 2019)
ED: Publish subject to minor revisions (review by editor) (27 Dec 2019) by S. Joseph Munchak
AR by Jussi Tiira on behalf of the Authors (21 Jan 2020)  Author's response   Manuscript 
ED: Publish as is (02 Feb 2020) by S. Joseph Munchak
AR by Jussi Tiira on behalf of the Authors (06 Feb 2020)  Manuscript 
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Short summary
Modern weather radars are sensitive for properties of precipitating snow particles, such as their sizes, shapes and number concentration. Vertical profiles of such radar measurements can be used for studying the processes through which snow is formed. We created a profile classification method for this purpose, and we show how it can be used for automatic identification of snow growth processes. Being able to identify the processes is expected to improve radar-based precipitation estimation.