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Inverse Modelling and Combined State-Source Estimation for Chemical Weather

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Data Assimilation

Abstract

Air quality data assimilation aims to find a best estimate of the control parameters (see theory chapter) for those processes of the atmosphere which govern the chemical evolution of biologically relevant height levels, typically located in the the lowermost atmosphere. As in data assimilation (see theory chapters), we have to resort to numerical models to complement usually sparse observation networks; these models serve as system constraints. Several research groups are developing data assimilation methods similar to those applied to meteorological applications. Techniques range from nudging to advanced spatio–temporal methods such as four-dimensional variational (4D-Var) data assimilation and various simplifications of the Kalman filter (KF).

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Acknowledgments

The authors are indebted to the BERLIOZ and VERTIKO project members for measurement data, and to Dr. A. Richter (IFE University of Bremen) and Dr. H. Eskes (KNMI) for satellite retrievals. The work was mainly supported from the German Ministry for Research and Technology in the frame of the AFO2000 project SATEC4D. Computing facilities were granted by ZAM, the Research Centre Jülich, on a Cray T3E and IBM Power 4.

Author information

Authors and Affiliations

  1. Research Centre Jülich, Rhenish Institute for Environmental Research at the University of Cologne and at ICG-2, Cologne, Germany

    Hendrik Elbern

  2. Helmholtz Virtual Institute for Inverse Modelling of Atmospheric Chemical Composition (IMACCO), Cologne, Germany

    Hendrik Elbern

  3. Research Centre Jülich, Rhenish Institute for Environmental Research at the University of Cologne (RIU), Cologne, Germany

    Achim Strunk & Lars Nieradzik

  4. Helmholtz Virtual Institute for Inverse Modelling of Atmospheric Chemical Composition (IMACCO), Cologne, Germany

    Achim Strunk & Lars Nieradzik

Authors
  1. Hendrik Elbern
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  2. Achim Strunk
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  3. Lars Nieradzik
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Corresponding author

Correspondence to Hendrik Elbern .

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Editors and Affiliations

  1. Dept. Meteorology, University of Reading, Earley Gate, Reading, RG66BB, United Kingdom

    William Lahoz

  2. Arapahoe Avenue 373, Boulder, 80302, Colorado, USA

    Boris Khattatov

  3. Atmospheric Science & Technology, Directorate, Environment Canada, Trans-Canada Highway 2121, Dorval, H9P 1J3, Québec, Canada

    Richard Menard

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Elbern, H., Strunk, A., Nieradzik, L. (2010). Inverse Modelling and Combined State-Source Estimation for Chemical Weather. In: Lahoz, W., Khattatov, B., Menard, R. (eds) Data Assimilation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74703-1_19

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