Articles | Volume 15, issue 6
https://doi.org/10.5194/essd-15-2445-2023
https://doi.org/10.5194/essd-15-2445-2023
Data description paper
 | 
12 Jun 2023
Data description paper |  | 12 Jun 2023

CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies

Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on essd-2022-367', ali jaan, 02 Dec 2022
    • AC3: 'Reply on CC1', Dirk N. Karger, 17 Feb 2023
  • RC1: 'Comment on essd-2022-367', Anonymous Referee #1, 08 Dec 2022
    • AC1: 'Reply on RC1', Dirk N. Karger, 17 Feb 2023
  • RC2: 'Comment on essd-2022-367', Anonymous Referee #2, 24 Dec 2022
    • AC2: 'Reply on RC2', Dirk N. Karger, 17 Feb 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Dirk N. Karger on behalf of the Authors (06 Apr 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (21 Apr 2023) by Guanyu Huang
RR by Anonymous Referee #1 (27 Apr 2023)
RR by Minghu Ding (07 May 2023)
ED: Publish as is (07 May 2023) by Guanyu Huang
AR by Dirk N. Karger on behalf of the Authors (07 May 2023)
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Short summary
We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
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