Articles | Volume 16, issue 3
The Cryosphere, 16, 1007–1030, 2022
https://doi.org/10.5194/tc-16-1007-2022
The Cryosphere, 16, 1007–1030, 2022
https://doi.org/10.5194/tc-16-1007-2022

Research article 15 Mar 2022

Research article | 15 Mar 2022

Evaluation of Northern Hemisphere snow water equivalent in CMIP6 models during 1982–2014

Kerttu Kouki 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: 'Comment on tc-2021-195', Anonymous Referee #1, 19 Aug 2021
    • AC1: 'Reply on RC1', Kerttu Kouki, 11 Oct 2021
  • RC2: 'Comments on Kouki et al. (tc-2021-195)', Anonymous Referee #2, 23 Aug 2021
    • AC2: 'Reply on RC2', Kerttu Kouki, 11 Oct 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (20 Oct 2021) by Carrie Vuyovich
AR by Kerttu Kouki on behalf of the Authors (23 Nov 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (20 Dec 2021) by Carrie Vuyovich
RR by Anonymous Referee #1 (06 Jan 2022)
ED: Publish as is (10 Feb 2022) by Carrie Vuyovich
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Short summary
We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.