RAP-Net: Region Attention Predictive Network  for  precipitation nowcasting

Zhang, Zheng; Luo, Chuyao; Feng, Shanshan; Ye, Rui; Ye, Yunming; Li, Xutao

doi:https://doi.org/10.5194/gmd-15-5407-2022

Articles | Volume 15, issue 13

https://doi.org/10.5194/gmd-15-5407-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-15-5407-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 13

Development and technical paper

|

15 Jul 2022

Development and technical paper |

| 15 Jul 2022

RAP-Net: Region Attention Predictive Network for precipitation nowcasting

Zheng Zhang, Chuyao Luo, Shanshan Feng, Rui Ye, Yunming Ye, and Xutao Li

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Final revised paper (published on 15 Jul 2022)
Preprint (discussion started on 11 Feb 2022)

Interactive discussion

Status: closed

RC1:
'Comment on gmd-2022-19', Anonymous Referee #1, 02 Mar 2022

The comment was uploaded in the form of a supplement: https://gmd.copernicus.org/preprints/gmd-2022-19/gmd-2022-19-RC1-supplement.pdf

Citation: https://doi.org/10.5194/gmd-2022-19-RC1
- RC2:
  'Reply on RC1', Anonymous Referee #2, 17 Mar 2022
  
  The paper describes a RAP-Net network that can be used for radar echo extrapolation. Experiments demonstrate the effectiveness of this method. The authors are suggested to supplement the experimental comparison of high-intensity echoes.
  
  Citation: https://doi.org/10.5194/gmd-2022-19-RC2
  - AC2: 'Reply on RC2', Chuyao Luo, 05 Apr 2022
    
    Thanks for your comments. The details of the reply can be found in the supplement.
    
    Citation: https://doi.org/10.5194/gmd-2022-19-AC2
- AC1: 'Reply on RC1', Chuyao Luo, 05 Apr 2022
  
  The details of the reply can be found in the supplement.
  
  Citation: https://doi.org/10.5194/gmd-2022-19-AC1
RC3:
'Comment on gmd-2022-19', Anonymous Referee #3, 19 Mar 2022

The comment was uploaded in the form of a supplement: https://gmd.copernicus.org/preprints/gmd-2022-19/gmd-2022-19-RC3-supplement.pdf

Citation: https://doi.org/10.5194/gmd-2022-19-RC3
- AC3: 'Reply on RC3', Chuyao Luo, 05 Apr 2022
  
  Thanks for your comments. The details of the reply can be found in the supplement.
  
  Citation: https://doi.org/10.5194/gmd-2022-19-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Chuyao Luo on behalf of the Authors (10 Apr 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (12 Apr 2022) by Charles Onyutha

RR by Anonymous Referee #1 (26 Apr 2022)

ED: Publish subject to minor revisions (review by editor) (27 Apr 2022) by Charles Onyutha

AR by Chuyao Luo on behalf of the Authors (30 Apr 2022) Author's response Author's tracked changes Manuscript

ED: Publish subject to minor revisions (review by editor) (03 May 2022) by Charles Onyutha

AR by Chuyao Luo on behalf of the Authors (04 May 2022) Author's response Author's tracked changes Manuscript

ED: Publish as is (07 May 2022) by Charles Onyutha

AR by Chuyao Luo on behalf of the Authors (15 May 2022) Author's response Manuscript

Short summary

In this paper, we develop a model to predict radar echo sequences and apply it in the precipitation nowcasting field. Different from existing models, we propose two new attention modules. By introducing them, the performance of RAP-Net outperforms other models, especially in those regions with moderate and heavy rainfall. Considering that these regions cause more threats to human activities, the research in our work is significant for preventing natural disasters caused by heavy rainfall.