22 Sep 2022
22 Sep 2022

Toward a multivariate formulation of the PKF assimilation: application to a simplified chemical transport model

Antoine Perrot1, Olivier Pannekoucke1,2,3, and Vincent Guidard1 Antoine Perrot et al.
  • 1CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
  • 2CERFACS, Toulouse, France
  • 3INPT-ENM, Toulouse, France

Abstract. This contribution explores a new approach to forecast multivariate covariances for atmospheric chemistry through the use of the parametric Kalman filter (PKF). In the PKF formalism, the error covariance matrix is modelized by a covariance model relying on parameters, for which the dynamics is then computed. The PKF has been formulated in univariate cases, and a multivariate extension for chemical transport models is explored here. To do so, a simplified two-species chemical transport model over a 1D domain is introduced, based on the nonlinear Lotka-Volterra equations, which allows to propose a multivariate pseudo covariance model. Then, the multivariate PKF dynamics is formulated and its results are compared with a large ensemble Kalman filter (EnKF) in several numerical experiments. In these experiments, the PKF accurately reproduces the EnKF. Eventually, the PKF is formulated for a more complex chemical model composed of six chemical species (Generic Reaction Set). Again, the PKF succeeds at reproducing the multivariate covariances diagnosed on the large ensemble.

Antoine Perrot et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-928', Annika Vogel, 20 Oct 2022
  • RC2: 'Comment on egusphere-2022-928', Anonymous Referee #2, 27 Oct 2022
  • RC3: 'Comment on egusphere-2022-928', Anonymous Referee #3, 31 Oct 2022

Antoine Perrot et al.

Antoine Perrot et al.


Total article views: 322 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
225 76 21 322 2 3
  • HTML: 225
  • PDF: 76
  • XML: 21
  • Total: 322
  • BibTeX: 2
  • EndNote: 3
Views and downloads (calculated since 22 Sep 2022)
Cumulative views and downloads (calculated since 22 Sep 2022)

Viewed (geographical distribution)

Total article views: 292 (including HTML, PDF, and XML) Thereof 292 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 27 Jan 2023
Short summary
This work is a theoretical contribution that provides equations for understanding uncertainty prediction applied in air quality where multiple chemical species can interact. A simplified minimal test-bed is introduced that shows the ability our equations to reproduce the statistics estimated from an ensemble of forecast. While the latter estimation is the state of the art, solving equations is numerically less costly, depending on the number of chemical species, and motivates this research.