Articles | Volume 13, issue 3
https://doi.org/10.5194/amt-13-1227-2020
https://doi.org/10.5194/amt-13-1227-2020
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: 2,809 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,013 722 74 2,809 174 74 66
  • HTML: 2,013
  • PDF: 722
  • XML: 74
  • Total: 2,809
  • Supplement: 174
  • BibTeX: 74
  • EndNote: 66
Views and downloads (calculated since 20 Aug 2019)
Cumulative views and downloads (calculated since 20 Aug 2019)

Viewed (geographical distribution)

Total article views: 2,809 (including HTML, PDF, and XML) Thereof 2,494 with geography defined and 315 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 26 Jul 2024
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.