Articles | Volume 28, issue 4
Research article
23 Dec 2021
Research article |  | 23 Dec 2021

Inferring the instability of a dynamical system from the skill of data assimilation exercises

Yumeng Chen, Alberto Carrassi, and Valerio Lucarini


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on npg-2021-25', Anonymous Referee #1, 19 Aug 2021
  • RC2: 'Comment on npg-2021-25', Anonymous Referee #2, 26 Aug 2021
  • AC1: 'Comment on npg-2021-25', Yumeng Chen, 12 Oct 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Yumeng Chen on behalf of the Authors (13 Oct 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (17 Nov 2021) by Takemasa Miyoshi
Short summary
Chaotic dynamical systems are sensitive to the initial conditions, which are crucial for climate forecast. These properties are often used to inform the design of data assimilation (DA), a method used to estimate the exact initial conditions. However, obtaining the instability properties is burdensome for complex problems, both numerically and analytically. Here, we suggest a different viewpoint. We show that the skill of DA can be used to infer the instability properties of a dynamical system.