Assessment of Source–Receptor Relations by Inverse Modelling and Chemical Data Assimilation

  • Hendrik ElbernEmail author
  • Achim Strunk
  • Elmar Friese
  • Lars Nieradzik


Data assimilation and Inverse Modelling may serve various purposes by use of manifold techniques. A reasonable definition reads as follows: extracts the signal from noisy observations (filtering) interpolates in space and time (interpolation) and reconstructs state variables that are not sampled by the observation network (completeness).


Kalman Filter Emission Rate Data Assimilation Aerosol Optical Depth Assimilation Window 
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.



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 from ZAM of the Research Centre Jülich on an IBM Power 4.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hendrik Elbern
    • 1
    • 2
    Email author
  • Achim Strunk
    • 1
  • Elmar Friese
    • 1
  • Lars Nieradzik
    • 1
  1. 1.Rhenish Institute for Environmental Research at the University of CologneCologneGermany
  2. 2.Institute for Chemistry and Dynamics of the Geosphere – 2 (Troposphere)JülichGermany

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