Recovering the Parameter $\alpha$ in the Simplified Bardina Model through Continuous Data Assimilation
Dynamical Systems
2025-11-25 v2
Abstract
In this study, we develop a continuous data assimilation algorithm to recover the parameter in the simplified Bardina model. Our method utilizes the observations of finitely many Fourier modes by using a nudging framework that involves recursive parameter updates. We provide a rigorous convergence analysis, showing that the approximate parameter approaches the true value under suitable conditions, while the approximate solution also converges to the true solution.
Cite
@article{arxiv.2511.08421,
title = {Recovering the Parameter $\alpha$ in the Simplified Bardina Model through Continuous Data Assimilation},
author = {Débora A. F. Albanez and Maicon José Benvenutti and Jing Tian},
journal= {arXiv preprint arXiv:2511.08421},
year = {2025}
}