Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 23
Articles | Volume 28, issue 23
https://doi.org/10.5194/hess-28-5163-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-5163-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 23
Technical note
 | 
29 Nov 2024
Technical note |  | 29 Nov 2024

Technical note: A simple feedforward artificial neural network for high-temporal-resolution rain event detection using signal attenuation from commercial microwave links

Erlend Øydvin, Maximilian Graf, Christian Chwala, Mareile Astrid Wolff, Nils-Otto Kitterød, and Vegard Nilsen

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Short summary
Two simple neural networks are trained to detect rainfall events using signal loss from commercial microwave links. Whereas existing rainfall event detection methods have focused on hourly resolution reference data, this study uses weather radar and rain gauges with 5 min and 1 min temporal resolutions, respectively. Our results show that the developed neural networks can detect rainfall events with a higher temporal precision than existing methods.
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