Articles | Volume 25, issue 3
https://doi.org/10.5194/npg-25-565-2018
https://doi.org/10.5194/npg-25-565-2018
Research article
 | 
24 Aug 2018
Research article |  | 24 Aug 2018

Ensemble variational assimilation as a probabilistic estimator – Part 1: The linear and weak non-linear case

Mohamed Jardak and Olivier Talagrand

Viewed

Total article views: 4,098 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,981 956 161 4,098 148 154
  • HTML: 2,981
  • PDF: 956
  • XML: 161
  • Total: 4,098
  • BibTeX: 148
  • EndNote: 154
Views and downloads (calculated since 24 Jan 2018)
Cumulative views and downloads (calculated since 24 Jan 2018)

Viewed (geographical distribution)

Total article views: 4,098 (including HTML, PDF, and XML) Thereof 3,706 with geography defined and 392 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Dec 2024
Short summary
Ensemble variational assimilation (EnsVAR) has been implemented on two small-dimension non-linear chaotic toy models, as well as on a linearized version of those models. In the linear case, EnsVAR is exactly Bayesian and produced highly reliable ensembles. In the non-linear case, EnsVAR, implemented on temporal windows on the order of magnitude of the predictability time of the systems, shows as good performance as in the exactly linear case. EnsVar is as good an estimator as EnKF and PF.