Articles | Volume 17, issue 7
https://doi.org/10.5194/amt-17-2165-2024
https://doi.org/10.5194/amt-17-2165-2024
Research article
 | 
17 Apr 2024
Research article |  | 17 Apr 2024

Improved rain event detection in commercial microwave link time series via combination with MSG SEVIRI data

Maximilian Graf, Andreas Wagner, Julius Polz, Llorenç Lliso, José Alberto Lahuerta, Harald Kunstmann, and Christian Chwala

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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
Hydrol. Earth Syst. Sci., 28, 5163–5171, https://doi.org/10.5194/hess-28-5163-2024,https://doi.org/10.5194/hess-28-5163-2024, 2024
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Cited articles

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Short summary
Commercial microwave links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is a crucial processing step. We investigate the usage of rainfall data from MSG SEVIRI for this task, compare this approach with existing methods, and introduce a novel combined approach. The results show certain advantages for SEVIRI-based methods, particularly for CMLs where existing methods perform poorly. Our novel combination yields the best performance.
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