A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar

Hu, Xiaoyu; Ge, Jinming; Du, Jiajing; Li, Qinghao; Huang, Jianping; Fu, Qiang

doi:https://doi.org/10.5194/amt-14-1743-2021

Articles | Volume 14, issue 2

https://doi.org/10.5194/amt-14-1743-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-14-1743-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 2

Research article

|

03 Mar 2021

Research article |

| 03 Mar 2021

A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar

Xiaoyu Hu, Jinming Ge, Jiajing Du, Qinghao Li, Jianping Huang, and Qiang Fu

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Final revised paper (published on 03 Mar 2021)
Preprint (discussion started on 24 Sep 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Referee #1 Comments (RC)', Anonymous Referee #1, 02 Nov 2020
- AC1: 'Response to Anonymous Referee #1', Jinming Ge, 02 Dec 2020
RC2: 'anonymous review', Anonymous Referee #3, 15 Dec 2020
- AC2: 'Response to Referee #3', Jinming Ge, 22 Dec 2020

Peer-review completion

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

AR by Jinming Ge on behalf of the Authors (30 Dec 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (04 Jan 2021) by Brian Kahn

ED: Publish as is (25 Jan 2021) by Brian Kahn

AR by Jinming Ge on behalf of the Authors (27 Jan 2021)

Post-review adjustments

AA: Author's adjustment | EA: Editor approval

AA by Jinming Ge on behalf of the Authors (26 Feb 2021) Author's adjustment Manuscript

EA: Adjustments approved (26 Feb 2021) by Brian Kahn

Short summary

Cloud radars are powerful instruments that can probe detailed cloud structures. However, radar echoes in the lower atmosphere are always contaminated by clutter. We proposed a multi-dimensional probability distribution function that can effectively discriminate low-level clouds from clutter by considering their different features in several variables. We applied this method to the radar observations at the SACOL site and found the results have good agreement with lidar detection.