Articles | Volume 25, issue 2
https://doi.org/10.5194/npg-25-315-2018
https://doi.org/10.5194/npg-25-315-2018
Research article
 | 
27 Apr 2018
Research article |  | 27 Apr 2018

Quasi-static ensemble variational data assimilation: a theoretical and numerical study with the iterative ensemble Kalman smoother

Anthony Fillion, Marc Bocquet, and Serge Gratton

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Short summary
This study generalizes a paper by Pires et al. (1996) to state-of-the-art data assimilation techniques, such as the iterative ensemble Kalman smoother (IEnKS). We show that the longer the time window over which observations are assimilated, the better the accuracy of the IEnKS. Beyond a critical time length that we estimate, we show that this accuracy finally degrades. We show that the use of the quasi-static minimizations but generalized to the IEnKS yields a significantly improved accuracy.