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

Model code and software

yumengch/InferDynPaper: PaperResults Y. Chen https://doi.org/10.5281/zenodo.5788693

DAPPER v1.1.0 P. Raanes and C. Grudzien https://doi.org/10.5281/zenodo.2029295

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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.