Estimating model‐error covariances in nonlinear state‐space models using Kalman smoothing and the expectation–maximization algorithm

Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation–maximization (EM) algorithm to estimate the model‐error covariances using classical extended and ensemble versions of the Kalman smoother. We show tha...

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