Articles | Volume 13, issue 3
Research article
04 Jul 2022
Research article |  | 04 Jul 2022

A non-stationary extreme-value approach for climate projection ensembles: application to snow loads in the French Alps

Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on esd-2021-79', Anonymous Referee #1, 23 Nov 2021
  • RC2: 'Comment on esd-2021-79', Antonio Speranza, 27 Nov 2021
  • RC3: 'Comment on esd-2021-79', Tamas Bodai, 30 Nov 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (24 Mar 2022) by Valerio Lucarini
AR by Guillaume Evin on behalf of the Authors (08 Apr 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (18 May 2022) by Valerio Lucarini
AR by Guillaume Evin on behalf of the Authors (10 Jun 2022)  Manuscript 
Short summary
Anticipating risks related to climate extremes is critical for societal adaptation to climate change. In this study, we propose a statistical method in order to estimate future climate extremes from past observations and an ensemble of climate change simulations. We apply this approach to snow load data available in the French Alps at 1500 m elevation and find that extreme snow load is projected to decrease by −2.9 kN m−2 (−50 %) between 1986–2005 and 2080–2099 for a high-emission scenario.
Final-revised paper