Articles | Volume 22, issue 2
https://doi.org/10.5194/npg-22-205-2015
https://doi.org/10.5194/npg-22-205-2015
Research article
 | 
07 Apr 2015
Research article |  | 07 Apr 2015

Improved variational methods in statistical data assimilation

J. Ye, N. Kadakia, P. J. Rozdeba, H. D. I. Abarbanel, and J. C. Quinn

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Short summary
We propose an improved method of data assimilation, in which measured data are incorporated into a physically based model. In data assimilation, one typically seeks to minimize some cost function; here, we discuss a variational approximation in which model and measurement errors are Gaussian, combined with an annealing method, to consistently identify a global minimum of this cost function. We illustrate this procedure with archetypal chaotic systems, and discuss higher-order corrections.