Articles | Volume 14, issue 2
Research article
26 Apr 2023
Research article |  | 26 Apr 2023

Direct and indirect application of univariate and multivariate bias corrections on heat-stress indices based on multiple regional-climate-model simulations

Liying Qiu, Eun-Soon Im, Seung-Ki Min, Yeon-Hee Kim, Dong-Hyun Cha, Seok-Woo Shin, Joong-Bae Ahn, Eun-Chul Chang, and Young-Hwa Byun


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on esd-2022-33', Anonymous Referee #1, 14 Sep 2022
    • AC1: 'Reply on RC1', Liying Qiu, 13 Oct 2022
  • RC2: 'Comment on esd-2022-33', Anonymous Referee #2, 17 Sep 2022
    • AC2: 'Reply on RC2', Liying Qiu, 14 Oct 2022
      • AC3: 'Reply on AC2', Liying Qiu, 14 Oct 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (11 Nov 2022) by Sagnik Dey
AR by Liying Qiu on behalf of the Authors (12 Nov 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (02 Mar 2023) by Sagnik Dey
RR by Nicholas Osborne (23 Mar 2023)
RR by Anonymous Referee #2 (23 Mar 2023)
ED: Publish as is (02 Apr 2023) by Sagnik Dey
AR by Liying Qiu on behalf of the Authors (05 Apr 2023)
Short summary
This study evaluates four bias correction methods (three univariate and one multivariate) for correcting multivariate heat-stress indices. We show that the multivariate method can benefit the indirect correction that first adjusts individual components before index calculation, and its advantage is more evident for indices relying equally on multiple drivers. Meanwhile, the direct correction of heat-stress indices by the univariate quantile delta mapping approach also has comparable performance.
Final-revised paper