Articles | Volume 14, issue 3
Geosci. Model Dev., 14, 1267–1293, 2021
https://doi.org/10.5194/gmd-14-1267-2021

Special issue: Evaluation of Model Intercomparison Projects

Geosci. Model Dev., 14, 1267–1293, 2021
https://doi.org/10.5194/gmd-14-1267-2021

Model evaluation paper 09 Mar 2021

Model evaluation paper | 09 Mar 2021

Evaluation of regional climate models ALARO-0 and REMO2015 at 0.22° resolution over the CORDEX Central Asia domain

Sara Top et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Sara Top on behalf of the Authors (10 Jul 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (23 Jul 2020) by Fabien Maussion
RR by Anonymous Referee #2 (04 Sep 2020)
ED: Reconsider after major revisions (09 Sep 2020) by Fabien Maussion
AR by Sara Top on behalf of the Authors (21 Oct 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (26 Oct 2020) by Fabien Maussion
RR by Anonymous Referee #2 (07 Dec 2020)
ED: Reconsider after major revisions (09 Dec 2020) by Fabien Maussion
AR by Sara Top on behalf of the Authors (20 Jan 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish subject to technical corrections (29 Jan 2021) by Fabien Maussion
AR by Sara Top on behalf of the Authors (30 Jan 2021)  Author's response    Manuscript
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Short summary
Detailed climate data are needed to assess the impact of climate change on human and natural systems. The performance of two high-resolution regional climate models, ALARO-0 and REMO2015, was investigated over central Asia, a vulnerable region where detailed climate information is scarce. In certain subregions the produced climate data are suitable for impact studies, but bias adjustment is required for subregions where significant biases have been identified.