
Time-space weak-constraint data assimilation for nonlinear models
Abstract
A general perturbation–linearization scheme is proposed for the problem of data assimilationwith an imperfect and nonlinear model, allowing for the application of the weak constraintrepresenter method. The scheme is shown in discrete formalism for a generic model. An applicationexample is given with computer-generated data in the case of the Burgers equation.Discussion in reference to the assimilation example concerns: the rôle of the model error, seenas a forcing term in the dynamics; the rôle of representers as a posteriori error covariances; acomparison among different choices for a priori dynamic error variance and strong constraintassimilation. Weak and strong constraint methods are also compared in a forecastingexperiment.
© 2000 Francesco Uboldi, Masafumi Kamachi, published by Stockholm University Press
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