[HTML][HTML] Adaptive parameter selection in nudging based data assimilation
Data assimilation combines (imperfect) knowledge of a flow's physical laws with (noisy, time-
lagged, and otherwise imperfect) observations to produce a more accurate prediction of flow …
lagged, and otherwise imperfect) observations to produce a more accurate prediction of flow …
Long-time accuracy of ensemble Kalman filters for chaotic and machine-learned dynamical systems
D Sanz-Alonso, N Waniorek - arXiv preprint arXiv:2412.14318, 2024 - arxiv.org
Filtering is concerned with online estimation of the state of a dynamical system from partial
and noisy observations. In applications where the state is high dimensional, ensemble …
and noisy observations. In applications where the state is high dimensional, ensemble …
On the inadequacy of nudging data assimilation algorithms for non-dissipative systems: A computational examination of the Korteweg de-Vries and Lorenz equations
ES Titi, C Victor - arXiv preprint arXiv:2411.08273, 2024 - arxiv.org
In this work, we study the applicability of the Azouani-Olson-Titi (AOT) nudging algorithm for
continuous data assimilation to evolutionary dynamical systems that are not dissipative …
continuous data assimilation to evolutionary dynamical systems that are not dissipative …