Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 29, issue 15
Articles | Volume 29, issue 15
https://doi.org/10.5194/hess-29-3687-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-3687-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 29, issue 15
Research article
 | 
12 Aug 2025
Research article |  | 12 Aug 2025

Infilling of missing rainfall radar data with a memory-assisted deep learning approach

Johannes Meuer, Laurens M. Bouwer, Frank Kaspar, Roman Lehmann, Wolfgang Karl, Thomas Ludwig, and Christopher Kadow

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Short summary
Our study focuses on filling in missing precipitation data using an advanced neural network model. Traditional methods for estimating missing climate information often struggle in large regions where data are scarce. Our solution, which incorporates recent advances in machine learning, captures the intricate patterns of precipitation over time, especially during extreme weather events. Our model shows good performance in reconstructing large regions of missing rainfall radar data.
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