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

Li, Dawei; Liu, Yudi; Chen, Chaohui

doi:https://doi.org/10.5194/gmd-14-4019-2021

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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Final revised paper (published on 29 Jun 2021)
Preprint (discussion started on 21 Dec 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

SC1: 'Comment on gmd-2020-363', Astrid Kerkweg, 26 Feb 2021
- SC2: 'Reply on SC1', Dawei Li, 04 Mar 2021
RC1: 'Referee Comments', Anonymous Referee #1, 04 Mar 2021
- AC1: 'Reply on RC1', Dawei Li, 23 Apr 2021
RC2: 'Referee Comment for Li et al.', Anonymous Referee #2, 04 Mar 2021
- AC2: 'Reply on RC2', Dawei Li, 23 Apr 2021
RC3: 'Review of the paper by Li, Liu, and Chen', P. Armand, 06 Mar 2021
- AC4: 'Reply on RC3', Dawei Li, 23 Apr 2021
RC4: 'Comment on Li et al', Anonymous Referee #4, 07 Mar 2021
- AC3: 'Reply on RC4', Dawei Li, 23 Apr 2021

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Dawei Li on behalf of the Authors (11 May 2021) Author's response Author's tracked changes Manuscript

ED: Publish subject to minor revisions (review by editor) (29 May 2021) by Rohitash Chandra

AR by Dawei Li on behalf of the Authors (01 Jun 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (01 Jun 2021) by Rohitash Chandra

AR by Dawei Li on behalf of the Authors (02 Jun 2021) Manuscript

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.