Articles | Volume 14, issue 6
Atmos. Meas. Tech., 14, 4565–4574, 2021
https://doi.org/10.5194/amt-14-4565-2021

Special issue: Tropospheric profiling (ISTP11) (AMT/ACP inter-journal SI)

Atmos. Meas. Tech., 14, 4565–4574, 2021
https://doi.org/10.5194/amt-14-4565-2021

Research article 21 Jun 2021

Research article | 21 Jun 2021

Evaluation of micro rain radar-based precipitation classification algorithms to discriminate between stratiform and convective precipitation

Andreas Foth et al.

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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 Andreas Foth on behalf of the Authors (01 Dec 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (07 Jan 2021) by V. Chandrasekar
RR by Anonymous Referee #2 (09 Jan 2021)
RR by Joël Van Baelen (29 Jan 2021)
ED: Publish subject to minor revisions (review by editor) (13 Mar 2021) by V. Chandrasekar
AR by Andreas Foth on behalf of the Authors (16 Mar 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (26 Apr 2021) by V. Chandrasekar
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Short summary
In this paper, we present two micro rain radar-based approaches to discriminate between stratiform and convective precipitation. One is based on probability density functions and the other one is an artificial neural network classification. Both methods agree well, giving similar results. However, the results of the artificial neural network are more reasonable since it is also able to distinguish an inconclusive class, in turn making the stratiform and convective classes more reliable.