Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 1
Articles | Volume 17, issue 1
https://doi.org/10.5194/gmd-17-399-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-399-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 1
Model description paper
 | 
16 Jan 2024
Model description paper |  | 16 Jan 2024

GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement

Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng

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Latest update: 23 Nov 2024
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Short summary
Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
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