Constituent Assimilation

  • William LahozEmail author
  • Quentin Errera


Background. In the 1990s, following years of development of meteorological data assimilation by the Numerical Weather Prediction (NWP) community, the data assimilation methodology began to be applied to constituents, with a strong focus on stratospheric ozone (Rood 2005; Lahoz et al. 2007a). Because of its comparatively later application, constituent data assimilation is less mature than meteorological data (henceforth NWP) assimilation. Nevertheless, there has been substantial progress over the last 15 years, with the field evolving from initial efforts to test the methodology to later efforts focusing on products for monitoring ozone and other constituents. More recently, the production of ozone forecasts by a number of operational centres has become routine. A notable feature of the application of the data assimilation methodology to constituents has been the strong interaction between the NWP and research communities, for example, in the EU-funded ASSET project (Lahoz et al. 2007b). A list of acronyms can be found in Appendix.


Data Assimilation Numerical Weather Prediction Numerical Weather Prediction Model Total Column Ozone Ozone Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Thanks to R. Dragani, I. Štajner, C. Long, S. Eckermann, H. Eskes, S. Polavarapu and D. Jackson for providing updated information on constituent assimilation efforts at ECMWF, GMAO, NCEP, NRL, KNMI, Canada and the Met Office (UK), respectively.


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© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Norsk Institutt for Luftforskning, Norwegian Institute for Air Research, NILUKjellerNorway
  2. 2.Belgian Institute for Space Aeronomy, BIRA-IASBBrusselsBelgium

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