Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 17
Articles | Volume 18, issue 17
https://doi.org/10.5194/amt-18-4467-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-4467-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 17
Research article
 | 
12 Sep 2025
Research article |  | 12 Sep 2025

CLEAR: a new discrete multiplicative random cascade model for disaggregating path-integrated rainfall estimates from commercial microwave links

Martin Fencl and Marc Schleiss

Viewed

Total article views: 2,335 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,958 317 60 2,335 59 78
  • HTML: 1,958
  • PDF: 317
  • XML: 60
  • Total: 2,335
  • BibTeX: 59
  • EndNote: 78
Views and downloads (calculated since 24 Mar 2025)
Cumulative views and downloads (calculated since 24 Mar 2025)

Viewed (geographical distribution)

Total article views: 2,335 (including HTML, PDF, and XML) Thereof 2,335 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Saved (final revised paper)

Latest update: 30 Apr 2026
Download
Short summary
A novel disaggregation algorithm for commercial microwave links (CMLs), named CLEAR (CML Segments with Equal Amounts of Rain), is proposed. CLEAR utilizes a multiplicative random cascade generator to control the splitting of link segments. The evaluation performed both on virtual and real CML data shows that CLEAR outperforms a commonly used benchmark algorithm. Moreover, the stochastic nature of CLEAR allows it to represent uncertainty as an ensemble of rain rate distributions along CML paths.
Read more
Share