Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 6
Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-4019-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-4019-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 6
Model description paper
 | 
29 Jun 2021
Model description paper |  | 29 Jun 2021

MSDM v1.0: A machine learning model for precipitation nowcasting over eastern China using multisource data

Dawei Li, Yudi Liu, and Chaohui Chen

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Short summary
In the daily weather forecast business, numerical weather prediction is mainly used to forecast precipitation, but its performance for nowcasting tasks within 0–2 h is very poor. Hence, we hope to use machine learning to improve the accuracy and resolution of quantitative precipitation nowcasting (QPN) tasks. Previous works focused on the extrapolation of radar echo without using abundant meteorological data. Therefore, we designed a model using three kinds of data for QPN in eastern china.
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