Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 20
Articles | Volume 15, issue 20
https://doi.org/10.5194/gmd-15-7641-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-7641-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 20
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: 3,421 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,579 768 74 3,421 61 45
  • HTML: 2,579
  • PDF: 768
  • XML: 74
  • Total: 3,421
  • BibTeX: 61
  • EndNote: 45
Views and downloads (calculated since 06 Oct 2021)
Cumulative views and downloads (calculated since 06 Oct 2021)

Viewed (geographical distribution)

Total article views: 3,421 (including HTML, PDF, and XML) Thereof 3,205 with geography defined and 216 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 04 Nov 2024
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.
Read more