Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-1743-2021
https://doi.org/10.5194/amt-14-1743-2021
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

Viewed

Total article views: 2,768 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,004 703 61 2,768 58 88
  • HTML: 2,004
  • PDF: 703
  • XML: 61
  • Total: 2,768
  • BibTeX: 58
  • EndNote: 88
Views and downloads (calculated since 24 Sep 2020)
Cumulative views and downloads (calculated since 24 Sep 2020)

Viewed (geographical distribution)

Total article views: 2,768 (including HTML, PDF, and XML) Thereof 2,639 with geography defined and 129 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Dec 2024
Download
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.