Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 20
Articles | Volume 28, issue 20
https://doi.org/10.5194/hess-28-4539-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-4539-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 20
Research article
 | 
23 Oct 2024
Research article |  | 23 Oct 2024

Assessing rainfall radar errors with an inverse stochastic modelling framework

Amy C. Green, Chris Kilsby, and András Bárdossy

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Short summary
Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
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