Climate projections of a multivariate heat stress index: the role of downscaling and bias correction

Casanueva, Ana; Kotlarski, Sven; Herrera, Sixto; Fischer, Andreas M.; Kjellstrom, Tord; Schwierz, Cornelia

doi:https://doi.org/10.5194/gmd-12-3419-2019

Articles | Volume 12, issue 8

https://doi.org/10.5194/gmd-12-3419-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-12-3419-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 8

Model evaluation paper

|

05 Aug 2019

Model evaluation paper |

| 05 Aug 2019

Climate projections of a multivariate heat stress index: the role of downscaling and bias correction

Ana Casanueva, Sven Kotlarski, Sixto Herrera, Andreas M. Fischer, Tord Kjellstrom, and Cornelia Schwierz

Download

Final revised paper (published on 05 Aug 2019)
Supplement to the final revised paper
Preprint (discussion started on 14 Jan 2019)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Comments for minor revision', Anonymous Referee #1, 22 Mar 2019
- AC1: 'Reply to Referee #1', Ana Casanueva, 09 May 2019
RC2: 'Review of Climate projections of a multi-variate heat stress index: the role of downscaling and bias correction', Anonymous Referee #2, 06 Apr 2019
- AC2: 'Reply to Referee #2', Ana Casanueva, 09 May 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Ana Casanueva on behalf of the Authors (09 May 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (22 May 2019) by Lauren Gregoire

RR by Anonymous Referee #2 (03 Jun 2019)

ED: Publish subject to minor revisions (review by editor) (01 Jul 2019) by Lauren Gregoire

AR by Ana Casanueva on behalf of the Authors (11 Jul 2019) Author's response Manuscript

ED: Publish as is (15 Jul 2019) by Lauren Gregoire

AR by Ana Casanueva on behalf of the Authors (16 Jul 2019) Manuscript

Short summary

Given the large number of available data sets and products currently produced for climate impact studies, it is challenging to distil the most accurate and useful information for climate services. This work presents a comparison of methods widely used to generate climate projections, from different sources and at different spatial resolutions, in order to assess the role of downscaling and statistical post-processing (bias correction).