Articles | Volume 15, issue 8
Methods for assessment of models
19 Apr 2022
Methods for assessment of models |  | 19 Apr 2022

An ensemble-based statistical methodology to detect differences in weather and climate model executables

Christian Zeman and Christoph Schär


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-248', Anonymous Referee #1, 08 Nov 2021
  • RC2: 'Comment on gmd-2021-248', Anonymous Referee #2, 16 Nov 2021
  • AC1: 'Comment on gmd-2021-248', Christian Zeman, 14 Dec 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Christian Zeman on behalf of the Authors (08 Feb 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (11 Feb 2022) by Christoph Knote
RR by Anonymous Referee #1 (28 Feb 2022)
ED: Publish subject to technical corrections (07 Mar 2022) by Christoph Knote
AR by Christian Zeman on behalf of the Authors (15 Mar 2022)  Author's response    Manuscript
Short summary
Our atmosphere is a chaotic system, where even a tiny change can have a big impact. This makes it difficult to assess if small changes, such as the move to a new hardware architecture, will significantly affect a weather and climate model. We present a methodology that allows to objectively verify this. The methodology is applied to several test cases, showing a high sensitivity. Results also show that a major system update of the underlying supercomputer did not significantly affect our model.