Taking into account correlated observation errors by progressive assimilation of multiscale information - Archive ouverte HAL Access content directly
Poster Communications Year : 2016

Taking into account correlated observation errors by progressive assimilation of multiscale information

(1, 2) , (2) , (2)
1
2

Abstract

The description of correlated observation error statistics is a challenge in data assimilation. Currently, the observation errors are assumed uncorrelated (the covariance matrix is diagonal) which is a severe approximation that leads to suboptimal results. It is possible to use multi-scale transformations to retain the diagonal matrix approximation while accounting for some correlation. However this approach can lead to some convergence problems due to scale interactions. We propose an online scale selection algorithm that improves the convergence properties in such case.
Fichier principal
Vignette du fichier
poster.pdf (290.16 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01402906 , version 1 (25-11-2016)

Licence

Attribution - NonCommercial - NoDerivatives - CC BY 4.0

Identifiers

  • HAL Id : hal-01402906 , version 1

Cite

Vincent Chabot, Maëlle Nodet, Arthur Vidard. Taking into account correlated observation errors by progressive assimilation of multiscale information. American Geophysical Union Fall Meeting, Dec 2016, San Francisco, United States. 2016. ⟨hal-01402906⟩
881 View
92 Download

Share

Gmail Facebook Twitter LinkedIn More