Global climate modeling with improved precipitation  characteristics by learning physics (GRIST-MPS v1.0)  from global storm-resolving modeling

Wang, Yiming; Zhang, Yi; Han, Yilun; Xue, Wei; Chen, Tianru; Zhou, Yihui; Li, Xiaohan; Chen, Haishan

doi:10.5194/gmd-19-5553-2026

Articles | Volume 19, issue 12

https://doi.org/10.5194/gmd-19-5553-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-5553-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 12

Development and technical paper

|

29 Jun 2026

Development and technical paper |

| 29 Jun 2026

Global climate modeling with improved precipitation characteristics by learning physics (GRIST-MPS v1.0) from global storm-resolving modeling

Yiming Wang, Yi Zhang, Yilun Han, Wei Xue, Tianru Chen, Yihui Zhou, Xiaohan Li, and Haishan Chen

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Final revised paper (published on 29 Jun 2026)
Supplement to the final revised paper
Preprint (discussion started on 04 Aug 2025)

Interactive discussion

Status: closed

CEC1:
'Comment on egusphere-2025-2790', Juan Antonio Añel, 08 Aug 2025

Dear authors,
I have come through the "Code and Data availability" section in your manuscript, and I have seen that for the GPM and ERA5 data, instead of providing the files that you have used, you simply have linked the main webpages for the mentioned datasets. For the ERA5 data you do not even provide a link to the specific page of the Climate Data Store, but to the webpage with the description of the reanalysis. This makes harder for the reader and reviewers to know what specific variables and files you have used for your work. I would request you to store in a permanent repository the GPM and ERA5 data that you have used in your work, and to modify the Code and Data availability section of your manuscript to include them, instead of the current links.
Juan A. Añel
Geosci. Model Dev. Executive Editor

Citation: https://doi.org/10.5194/egusphere-2025-2790-CEC1
- AC1:
  'Reply on CEC1', Yi Zhang, 10 Aug 2025
  
  Dear Chief Editor,
  Thank you for your careful review and valuable suggestion. We fully understand the importance of making the exact datasets accessible for readers and reviewers. The specific GPM and ERA5 datasets used in our work were archived in the file input_plot.tar.gz on the Zenodo repository we have provided. We will update the “Code and Data availability” section to reflect this in the next iteration of this manuscript (if any).
  We hope this may address your concerns regarding this issue.
  Kind regards,
  Yi Zhang on behalf of all authors
  
  Citation: https://doi.org/10.5194/egusphere-2025-2790-AC1
  - CEC2: 'Reply on AC1', Juan Antonio Añel, 11 Aug 2025
    
    Dear authors,
    Many thanks for the quick reply and for the clarification regarding the data.
    Juan A. Añel
    Geosci. Model Dev. Executive Editor
    
    Citation: https://doi.org/10.5194/egusphere-2025-2790-CEC2
RC1:
'Comment on egusphere-2025-2790', Anonymous Referee #1, 29 Aug 2025

Please see the attached PDF.

Citation: https://doi.org/10.5194/egusphere-2025-2790-RC1
- AC2: 'Reply on RC1', Yi Zhang, 21 Nov 2025
  
  Dear Reviewer,
  We sincerely thank you for your valuable reviews and constructive comments on our manuscript. We have submitted a revised version, along with a detailed point-by-point response to each of your comments (attached).
  --
  All the best,
  Yi Zhang on behalf of the authors
  
  Citation: https://doi.org/10.5194/egusphere-2025-2790-AC2
RC2:
'Comment on egusphere-2025-2790', Anonymous Referee #2, 01 Sep 2025

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2790/egusphere-2025-2790-RC2-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2025-2790-RC2
- AC3: 'Reply on RC2', Yi Zhang, 21 Nov 2025
  
  Dear Reviewer,
  We sincerely thank you for your valuable reviews and constructive comments on our manuscript. We have submitted a revised version, along with a detailed point-by-point response to each of your comments (attached).
  --
  All the best,
  Yi Zhang on behalf of the authors
  
  Citation: https://doi.org/10.5194/egusphere-2025-2790-AC3

Peer review completion

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

AR by Yi Zhang on behalf of the Authors (19 Nov 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (01 Dec 2025) by Emmanouil Flaounas

RR by Anonymous Referee #2 (04 Dec 2025)

RR by Anonymous Referee #1 (12 Dec 2025)

ED: Reconsider after major revisions (16 Dec 2025) by Emmanouil Flaounas

AR by Yi Zhang on behalf of the Authors (10 Feb 2026) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (17 Feb 2026) by Emmanouil Flaounas

RR by Anonymous Referee #3 (18 May 2026)

ED: Publish subject to minor revisions (review by editor) (25 May 2026) by Emmanouil Flaounas

AR by Yi Zhang on behalf of the Authors (07 Jun 2026) Author's response Author's tracked changes Manuscript

ED: Publish as is (18 Jun 2026) by Emmanouil Flaounas

AR by Yi Zhang on behalf of the Authors (19 Jun 2026)

Short summary

This study demonstrates that short-period Global Storm Resolving Model (GSRM) simulations can inform long-term Global Climate Model (GCM) integrations through a machine-learning-based physics suite. With 80 d of GSRM-derived training data, the hybrid model achieves stable multiyear climate simulations and improved precipitation climatic characteristics.

Global climate modeling with improved precipitation characteristics by learning physics (GRIST-MPS v1.0) from global storm-resolving modeling

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Interactive discussion

Peer review completion

Suggestions for revision or reasons for rejection

Suggestions for revision or reasons for rejection