Abstract
In this study the proper orthogonal decomposition (POD) methodology to model reduction is applied to construct a reduced-order control space for simple advection-diffusion equations. Several 4D-Var data assimilation experiments associated with these models are carried out in the reduced control space. Emphasis is laid on the performance evaluation of an adaptive POD procedure, with respect to the solution obtained with the classical 4D-Var (full model), and POD 4D-Var data assimilation. Despite some perturbation factors characterizing the model dynamics, the adaptive POD scheme presents better numerical robustness compared to the other methods, and provides accurate results.
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Dimitriu, G., Apreutesei, N., Ştefănescu, R. (2010). Numerical Simulations with Data Assimilation Using an Adaptive POD Procedure. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2009. Lecture Notes in Computer Science, vol 5910. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12535-5_18
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DOI: https://doi.org/10.1007/978-3-642-12535-5_18
Publisher Name: Springer, Berlin, Heidelberg
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