Abstract. This paper presents the results of ensemble Riemannian data assimilation for relatively high-dimensional nonlinear dynamical systems, focusing on chaotic Lorenz-96 model and a two-layer quasi-geostrophic (QG) atmospheric circulation. The analysis state in this approach is inferred from joint distribution that optimally couples background probability likelihood function, enabling forma...

This paper deals with parameter estimation problem of large-scale systems. A recursive distributed algorithm, based on the minimization prediction error method, is developed. Specifically, class systems that are composed several interconnected sub-systems considered. Each sub-system modelled by a linear discrete-time state space mathematical model unknown parameters. The convergence analysis th...