Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 15
Articles | Volume 15, issue 15
https://doi.org/10.5194/gmd-15-5967-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-5967-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 15
Model description paper
 | 
01 Aug 2022
Model description paper |  | 01 Aug 2022

Rad-cGAN v1.0: Radar-based precipitation nowcasting model with conditional generative adversarial networks for multiple dam domains

Suyeon Choi and Yeonjoo Kim

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Short summary
Here we present the cGAN-based precipitation nowcasting model, named Rad-cGAN, trained to predict a radar reflectivity map with a lead time of 10 min. Rad-cGAN showed superior performance at a lead time of up to 90 min compared with the reference models. Furthermore, we demonstrate the successful implementation of the transfer learning strategies using pre-trained Rad-cGAN to develop the models for different dam domains.
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