Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 1
Articles | Volume 14, issue 1
https://doi.org/10.5194/amt-14-185-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-185-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 1
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: 1,940 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,239 634 67 1,940 66 63
  • HTML: 1,239
  • PDF: 634
  • XML: 67
  • Total: 1,940
  • BibTeX: 66
  • EndNote: 63
Views and downloads (calculated since 18 Dec 2019)
Cumulative views and downloads (calculated since 18 Dec 2019)

Viewed (geographical distribution)

Total article views: 1,940 (including HTML, PDF, and XML) Thereof 1,885 with geography defined and 55 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Jul 2024
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.
Read more