Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 25, issue 2
Articles | Volume 25, issue 2
https://doi.org/10.5194/npg-25-315-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/npg-25-315-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 2
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

Viewed

Total article views: 3,407 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,057 1,171 179 3,407 225 264
  • HTML: 2,057
  • PDF: 1,171
  • XML: 179
  • Total: 3,407
  • BibTeX: 225
  • EndNote: 264
Views and downloads (calculated since 16 Nov 2017)
Cumulative views and downloads (calculated since 16 Nov 2017)

Viewed (geographical distribution)

Total article views: 3,407 (including HTML, PDF, and XML) Thereof 3,216 with geography defined and 191 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 24 Dec 2025
Download
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.
Read more
Share
Special issue
Numerical modeling, predictability and data assimilation in...