Articles | Volume 28, issue 4
https://doi.org/10.5194/npg-28-633-2021
https://doi.org/10.5194/npg-28-633-2021
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

Viewed

Total article views: 2,301 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,775 484 42 2,301 34 18
  • HTML: 1,775
  • PDF: 484
  • XML: 42
  • Total: 2,301
  • BibTeX: 34
  • EndNote: 18
Views and downloads (calculated since 12 Jul 2021)
Cumulative views and downloads (calculated since 12 Jul 2021)

Viewed (geographical distribution)

Total article views: 2,301 (including HTML, PDF, and XML) Thereof 2,147 with geography defined and 154 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 18 Apr 2024
Download
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.