Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm

Kalesse, Heike; Vogl, Teresa; Paduraru, Cosmin; Luke, Edward

doi:https://doi.org/10.5194/amt-12-4591-2019

Articles | Volume 12, issue 8

https://doi.org/10.5194/amt-12-4591-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-12-4591-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 8

Research article

|

30 Aug 2019

Research article |

| 30 Aug 2019

Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm

Heike Kalesse, Teresa Vogl, Cosmin Paduraru, and Edward Luke

Download

Final revised paper (published on 30 Aug 2019)
Preprint (discussion started on 28 Mar 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review for amt-2019-48', Anonymous Referee #1, 18 May 2019
- AC1: 'Reply to comments of reviewer #1', Heike Kalesse, 04 Jul 2019
RC2: 'amt-2019-48 manuscript review', Anonymous Referee #2, 30 May 2019
- AC2: 'replies to reviewer #2', Heike Kalesse, 04 Jul 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Heike Kalesse-Los on behalf of the Authors (04 Jul 2019) Author's response Manuscript

ED: Publish as is (10 Jul 2019) by Mark Kulie

Short summary

In a cloud, different particles like liquid water droplets and ice particles can exist simultaneously. To study the evolution of cloud particles from cloud top to bottom one has to find out how many different types of particles with different fall velocities are present. This can be done by analyzing the number of peaks in upward-looking cloud radar Doppler spectra. A new machine-learning algorithm (named PEAKO) that determines the number of peaks is introduced and compared to existing methods.