Four dimensional data assimilation experiments with International Consortium for Atmospheric Research on Transport and Transformation ozone measurements - Université Toulouse III - Paul Sabatier - Toulouse INP Accéder directement au contenu
Article Dans Une Revue Journal of Geophysical Research: Atmospheres Année : 2007

Four dimensional data assimilation experiments with International Consortium for Atmospheric Research on Transport and Transformation ozone measurements

T. Chai
  • Fonction : Auteur
G. R. Carmichael
  • Fonction : Auteur
Y. Tang
  • Fonction : Auteur
A. Sandu
  • Fonction : Auteur
M. Hardesty
  • Fonction : Auteur
P. Pilewskie
  • Fonction : Auteur
S. Withlow
  • Fonction : Auteur
E.V. Browell
  • Fonction : Auteur
M.A. Avery
  • Fonction : Auteur
J. T. Merrill
  • Fonction : Auteur
A.M. Thompson
  • Fonction : Auteur
E. Williams
  • Fonction : Auteur

Résumé

Ozone measurements by various platforms during the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) operations in the summer of 2004 are assimilated into the STEM regional chemical transport model (CTM). Under the four-dimensional variational data assimilation (4D-Var) framework, the model forecast (background) error covariance matrix is constructed using both the so-called NMC (National Meteorological Center, now National Centers for Environmental Prediction) method and the observational (Hollingworth-Lönnberg) method. The inversion of the covariance matrix is implemented using truncated singular value decomposition (TSVD) approach. The TSVD approach is numerically stable even with severely ill conditioned vertical correlation covariance matrix and large horizontal correlation distances. Ozone observations by different platforms (aircraft, surface, and ozonesondes) are first assimilated separately. The impacts of the various measurements are evaluated on their ability to improve the predictions, defined as the information content of the observations under the current framework. In the end, all observations are assimilated into the CTM. The final analysis matches well with observations from all platforms. Assessed with all the observations throughout the boundary layer and midtroposphere, the model bias is reduced from 11.3 ppbv for the base case to −1.5 ppbv. A reduction of 10.3 ppbv in root mean square error is also seen. In addition, the potential of improving air quality forecasts by chemical data assimilation is demonstrated. The effect of assimilating ozone observations on model predictions of other species is also shown.
Fichier principal
Vignette du fichier
Journal of Geophysical Research Atmospheres - 2007 - Chai - Four%u2010dimensional data assimilation experiments with.pdf (5.99 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-00563708 , version 1 (16-06-2022)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

T. Chai, G. R. Carmichael, Y. Tang, A. Sandu, M. Hardesty, et al.. Four dimensional data assimilation experiments with International Consortium for Atmospheric Research on Transport and Transformation ozone measurements. Journal of Geophysical Research: Atmospheres, 2007, 112, pp.D12S15. ⟨10.1029/2006JD007763⟩. ⟨hal-00563708⟩
65 Consultations
8 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More