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

Model code and software

yumengch/InferDynPaper: PaperResults Y. Chen

DAPPER v1.1.0 P. Raanes and C. Grudzien

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.