Articles | Volume 14, issue 1
https://doi.org/10.5194/amt-14-185-2021
https://doi.org/10.5194/amt-14-185-2021
Research article
 | 
12 Jan 2021
Research article |  | 12 Jan 2021

Separation of convective and stratiform precipitation using polarimetric radar data with a support vector machine method

Yadong Wang, Lin Tang, Pao-Liang Chang, and Yu-Shuang Tang

Viewed

Total article views: 3,107 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,087 909 111 3,107 135 148
  • HTML: 2,087
  • PDF: 909
  • XML: 111
  • Total: 3,107
  • BibTeX: 135
  • EndNote: 148
Views and downloads (calculated since 18 Dec 2019)
Cumulative views and downloads (calculated since 18 Dec 2019)

Viewed (geographical distribution)

Total article views: 3,107 (including HTML, PDF, and XML) Thereof 3,034 with geography defined and 73 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 09 Feb 2026
Download
Short summary
The motivation of this work is to develop a precipitation separation approach that can be implemented on those radars with fast scanning schemes. In these schemes, the higher tilt radar data are not available, which poses a challenge for the traditional approaches. This approach uses artificial intelligence, which integrates polarimetric radar variables. The quantitative precipitation estimation will benefit from the output of this algorithm.
Share