Articles | Volume 28, issue 4
Nonlin. Processes Geophys., 28, 501–532, 2021
https://doi.org/10.5194/npg-28-501-2021
Nonlin. Processes Geophys., 28, 501–532, 2021
https://doi.org/10.5194/npg-28-501-2021

Research article 14 Oct 2021

Research article | 14 Oct 2021

Identification of linear response functions from arbitrary perturbation experiments in the presence of noise – Part 1: Method development and toy model demonstration

Guilherme L. Torres Mendonça 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 npg-2021-9', Anonymous Referee #1, 24 Mar 2021
    • AC1: 'Reply on RC1', Guilherme Torres Mendonça, 31 Mar 2021
  • RC2: 'Comment on npg-2021-9', Anonymous Referee #2, 28 Mar 2021
    • AC2: 'Reply on RC2', Guilherme Torres Mendonça, 08 Apr 2021
  • CC1: 'Comment on npg-2021-9', Valerio Lucarini, 10 Apr 2021
    • AC3: 'Reply on CC1', Guilherme Torres Mendonça, 14 Apr 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Guilherme Torres Mendonça on behalf of the Authors (13 Jun 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (25 Jun 2021) by Ilya Zaliapin
RR by Anonymous Referee #2 (26 Jun 2021)
RR by Anonymous Referee #3 (09 Jul 2021)
ED: Publish subject to minor revisions (review by editor) (26 Jul 2021) by Ilya Zaliapin
AR by Guilherme Torres Mendonça on behalf of the Authors (04 Aug 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (01 Sep 2021) by Ilya Zaliapin
Short summary
Linear response functions are a powerful tool to both predict and investigate the dynamics of a system when subjected to small perturbations. In practice, these functions must often be derived from perturbation experiment data. Nevertheless, current methods for this identification require a tailored perturbation experiment, often with many realizations. We present a method that instead derives these functions from a single realization of an experiment driven by any type of perturbation.