Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 1
Articles | Volume 17, issue 1
https://doi.org/10.5194/gmd-17-53-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-53-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 1
Model experiment description paper
 | 
04 Jan 2024
Model experiment description paper |  | 04 Jan 2024

Deep learning model based on multi-scale feature fusion for precipitation nowcasting

Jinkai Tan, Qiqiao Huang, and Sheng Chen

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Short summary
This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
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