Articles | Volume 17, issue 12
https://doi.org/10.5194/tc-17-5061-2023
https://doi.org/10.5194/tc-17-5061-2023
Research article
 | 
30 Nov 2023
Research article |  | 30 Nov 2023

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

Marco Tedesco, Paolo Colosio, Xavier Fettweis, and Guido Cervone

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2023-56', Anonymous Referee #1, 01 Jun 2023
    • AC1: 'Reply on RC1', Marco Tedesco, 06 Sep 2023
  • RC2: 'Comment on tc-2023-56', Anonymous Referee #2, 18 Jul 2023
    • AC2: 'Reply on RC2', Marco Tedesco, 06 Sep 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish subject to minor revisions (review by editor) (12 Sep 2023) by Alexander Robinson
AR by Marco Tedesco on behalf of the Authors (12 Sep 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (10 Oct 2023) by Alexander Robinson
AR by Marco Tedesco on behalf of the Authors (11 Oct 2023)  Manuscript 
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Short summary
We developed a technique to improve the outputs of a model that calculates the gain and loss of Greenland and consequently its contribution to sea level rise. Our technique generates “sharper” images of the maps generated by the model to better understand and quantify where losses occur. This has implications for improving models, understanding what drives the contributions of Greenland to sea level rise, and more.