Articles | Volume 28, issue 1
https://doi.org/10.5194/npg-28-1-2021
https://doi.org/10.5194/npg-28-1-2021
Research article
 | 
14 Jan 2021
Research article |  | 14 Jan 2021

A methodology to obtain model-error covariances due to the discretization scheme from the parametric Kalman filter perspective

Olivier Pannekoucke, Richard Ménard, Mohammad El Aabaribaoune, and Matthieu Plu

Viewed

Total article views: 1,959 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,377 510 72 1,959 81 73
  • HTML: 1,377
  • PDF: 510
  • XML: 72
  • Total: 1,959
  • BibTeX: 81
  • EndNote: 73
Views and downloads (calculated since 08 May 2020)
Cumulative views and downloads (calculated since 08 May 2020)

Viewed (geographical distribution)

Total article views: 1,959 (including HTML, PDF, and XML) Thereof 1,810 with geography defined and 149 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 19 Apr 2024
Download
Short summary
Numerical weather prediction involves numerically solving the mathematical equations, which describe the geophysical flow, by transforming them so that they can be computed. Through this transformation, it appears that the equations actually solved by the machine are then a modified version of the original equations, introducing an error that contributes to the model error. This work helps to characterize the covariance of the model error that is due to this modification of the equations.