Skip to main content
Have a personal or library account? Click to login
Parametric Kalman filter for chemical transport models Cover

Parametric Kalman filter for chemical transport models

Open Access
|Dec 2016

Figures & Tables

Fig. 1

Background error variance field (top) and length-scale field (bottom).

Fig. 2

Illustration of analysis error variance (left panel) and length-scale (right panel) for the assimilation of three observations: 0, 45 and 90, when the background correlation is homogeneous and Gaussian. The Kalman reference (continuous line) is compared with the PKF analysis using the first-order eq. (12) (dash dotted line) and the second-order eq. (13) (dashed line).

Fig. 3

Similar to Fig. 2 but when the background correlation is homogeneous and SOAR.

Fig. 4

Diagnosis of the analysis covariance matrix at iterations 1 (a), 15 (b), 30 (c) and 60 (d) in case of a pure advection process. KF time evolution (continuous line), the PKF (dashed line) and the PhKF (dash dotted line).

Fig. 5

Diagnosis of the analysis covariance matrix at iterations 1 (a), 15 (b), 30 (c) and 60 (d) in case of an advection–diffusion dynamics. KF time evolution (continuous line), the PKF (dashed line) and the PhKF (dash dotted line).

Language: English
Page range: 31547 - 31547
Submitted on: Mar 8, 2016
Accepted on: Sep 7, 2016
Published on: Dec 1, 2016
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2016 Olivier Pannekoucke, Sophie Ricci, Sebastien Barthelemy, Richard Ménard, Olivier Thual, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.