Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 13, issue 3
Articles | Volume 13, issue 3
https://doi.org/10.5194/amt-13-1227-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-1227-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 3
Research article
 | 
13 Mar 2020
Research article |  | 13 Mar 2020

Unsupervised classification of vertical profiles of dual polarization radar variables

Jussi Tiira and Dmitri Moisseev

Viewed

Total article views: 4,794 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,630 1,043 121 4,794 258 158 171
  • HTML: 3,630
  • PDF: 1,043
  • XML: 121
  • Total: 4,794
  • Supplement: 258
  • BibTeX: 158
  • EndNote: 171
Views and downloads (calculated since 20 Aug 2019)
Cumulative views and downloads (calculated since 20 Aug 2019)

Viewed (geographical distribution)

Total article views: 4,794 (including HTML, PDF, and XML) Thereof 4,616 with geography defined and 178 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 04 May 2026
Download
Short summary
Modern weather radars are sensitive for properties of precipitating snow particles, such as their sizes, shapes and number concentration. Vertical profiles of such radar measurements can be used for studying the processes through which snow is formed. We created a profile classification method for this purpose, and we show how it can be used for automatic identification of snow growth processes. Being able to identify the processes is expected to improve radar-based precipitation estimation.
Read more
Share