Articles | Volume 15, issue 20
https://doi.org/10.5194/gmd-15-7641-2022
https://doi.org/10.5194/gmd-15-7641-2022
Development and technical paper
 | 
20 Oct 2022
Development and technical paper |  | 20 Oct 2022

A fast, single-iteration ensemble Kalman smoother for sequential data assimilation

Colin Grudzien and Marc Bocquet

Viewed

Total article views: 4,259 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,201 972 86 4,259 88 109
  • HTML: 3,201
  • PDF: 972
  • XML: 86
  • Total: 4,259
  • BibTeX: 88
  • EndNote: 109
Views and downloads (calculated since 06 Oct 2021)
Cumulative views and downloads (calculated since 06 Oct 2021)

Viewed (geographical distribution)

Total article views: 4,259 (including HTML, PDF, and XML) Thereof 4,037 with geography defined and 222 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 08 Oct 2025
Download
Short summary
Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Share