Articles | Volume 22, issue 6
Nonlin. Processes Geophys., 22, 645–662, 2015
https://doi.org/10.5194/npg-22-645-2015
Nonlin. Processes Geophys., 22, 645–662, 2015
https://doi.org/10.5194/npg-22-645-2015

Research article 03 Nov 2015

Research article | 03 Nov 2015

Expanding the validity of the ensemble Kalman filter without the intrinsic need for inflation

M. Bocquet et al.

Viewed

Total article views: 4,237 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,990 1,019 228 4,237 232 254
  • HTML: 2,990
  • PDF: 1,019
  • XML: 228
  • Total: 4,237
  • BibTeX: 232
  • EndNote: 254
Views and downloads (calculated since 24 Jul 2015)
Cumulative views and downloads (calculated since 24 Jul 2015)

Cited

Saved (final revised paper)

Latest update: 06 Mar 2021
Download
Short summary
The popular data assimilation technique known as the ensemble Kalman filter (EnKF) suffers from sampling errors due to the limited size of the ensemble. This deficiency is usually cured by inflating the sampled error covariances and by using localization. This paper further develops and discusses the finite-size EnKF, or EnKF-N, a variant of the EnKF that does not require inflation. It expands the use of the EnKF-N to a wider range of dynamical regimes.