Articles | Volume 15, issue 17
Geosci. Model Dev., 15, 6747–6758, 2022
https://doi.org/10.5194/gmd-15-6747-2022
Geosci. Model Dev., 15, 6747–6758, 2022
https://doi.org/10.5194/gmd-15-6747-2022
Model evaluation paper
06 Sep 2022
Model evaluation paper | 06 Sep 2022

Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44

Jorge Baño-Medina et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comments on gmd-2022-57', Anonymous Referee #1, 16 Apr 2022
    • AC1: 'Reply on RC1', Jorge Baño-Medina, 15 Jun 2022
  • RC2: 'Comment on gmd-2022-57', Anonymous Referee #2, 21 Apr 2022
    • AC2: 'Reply on RC2', Jorge Baño-Medina, 15 Jun 2022
  • RC3: 'Comment on gmd-2022-57', Anonymous Referee #3, 23 Apr 2022
    • AC3: 'Reply on RC3', Jorge Baño-Medina, 15 Jun 2022
  • RC4: 'Comment on gmd-2022-57', Anonymous Referee #4, 23 Apr 2022
    • AC4: 'Reply on RC4', Jorge Baño-Medina, 15 Jun 2022
  • CEC1: 'Comment on gmd-2022-57', Juan Antonio Añel, 25 Apr 2022
    • AC6: 'Reply on CEC1', Jorge Baño-Medina, 15 Jun 2022
  • RC5: 'Comment on gmd-2022-57', Anonymous Referee #5, 06 May 2022
    • AC5: 'Reply on RC5', Jorge Baño-Medina, 15 Jun 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Jorge Baño-Medina on behalf of the Authors (13 Jul 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (24 Jul 2022) by Charles Onyutha
RR by Anonymous Referee #5 (02 Aug 2022)
RR by Anonymous Referee #2 (03 Aug 2022)
RR by Anonymous Referee #4 (05 Aug 2022)
ED: Publish as is (06 Aug 2022) by Charles Onyutha
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Short summary
Deep neural networks are used to produce downscaled regional climate change projections over Europe for temperature and precipitation for the first time. The resulting dataset, DeepESD, is analyzed against state-of-the-art downscaling methodologies, reproducing more accurately the observed climate in the historical period and showing plausible future climate change signals with low computational requirements.