Articles | Volume 17, issue 22
https://doi.org/10.5194/amt-17-6547-2024
https://doi.org/10.5194/amt-17-6547-2024
Research article
 | 
15 Nov 2024
Research article |  | 15 Nov 2024

PEAKO and peakTree: tools for detecting and interpreting peaks in cloud radar Doppler spectra – capabilities and limitations

Teresa Vogl, Martin Radenz, Fabiola Ramelli, Rosa Gierens, and Heike Kalesse-Los

Viewed

Total article views: 544 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
393 117 34 544 20 15
  • HTML: 393
  • PDF: 117
  • XML: 34
  • Total: 544
  • BibTeX: 20
  • EndNote: 15
Views and downloads (calculated since 10 Apr 2024)
Cumulative views and downloads (calculated since 10 Apr 2024)

Viewed (geographical distribution)

Total article views: 544 (including HTML, PDF, and XML) Thereof 534 with geography defined and 10 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 15 Nov 2024
Download
Short summary
In this study, we present a toolkit of two Python algorithms to extract information from Doppler spectra measured by ground-based cloud radars. In these Doppler spectra, several peaks can be formed due to populations of droplets/ice particles with different fall velocities coexisting in the same measurement time and height. The two algorithms can detect peaks and assign them to certain particle types, such as small cloud droplets or fast-falling ice particles like graupel.