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

Fencl, Martin; Schleiss, Marc

doi:https://doi.org/10.5194/amt-18-4467-2025

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

Data sets

Data and codes underlying the publication: "CLEAR: a new discrete multiplicative random cascade model for disaggregating path-integrated rainfall estimates from commercial microwave links Martin Fencl and March Schleiss https://doi.org/10.4121/5c4ad375-4e88-402b-ac46-d27bb47250c3.v1

Model code and software

Data and codes underlying the publication: "CLEAR: a new discrete multiplicative random cascade model for disaggregating path-integrated rainfall estimates from commercial microwave links Martin Fencl and March Schleiss https://doi.org/10.4121/5c4ad375-4e88-402b-ac46-d27bb47250c3.v1

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.