Articles | Volume 14, issue 6
Geosci. Model Dev., 14, 4019–4034, 2021
https://doi.org/10.5194/gmd-14-4019-2021
Geosci. Model Dev., 14, 4019–4034, 2021
https://doi.org/10.5194/gmd-14-4019-2021

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 et al.

Model code and software

MSDM v1.0: A machine learning model for precipitation nowcasting over East China using multisource data D. Li https://doi.org/10.5281/zenodo.4749183

Download
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.