Evaluation of a Chemical Data Assimilation System

  • Jeremy D. Silver
  • Jesper H. Christensen
  • Michael Kahnert
  • Lennart Robertson
  • Jørgen Brandt
Conference paper
First Online:
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

An ensemble Kalman filter data assimilation system has been coupled to the Danish Eulerian Hemispheric Model (DEHM), a hemispheric-scale, offline, chemistry-transport model. We present an evaluation of the performance of the assimilation system in the framework of an Observing System Simulation Experiment (OSSE). This involves assimilating “pseudo-observations” derived from a reference simulation, and then comparing the assimilation run with the reference run. We focus on nitrogen dioxide and the pseudo-observations are generated to mimic the spatial/temporal pattern of retrievals from the Ozone Monitoring Instrument.

Keywords

Observation Operator Ozone Monitoring Instrument Average Kernel Ensemble Kalman Filter Background Error Covariance 
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.
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Notes

Acknowledgments

This work was funded by a program grant from the Danish Council for Technology and Innovation: Effects of climate changes on ecosystems – a global comparative analysis. We are grateful to the ECMWF for making the MACC reanalysis freely available. We acknowledge the free use of the tropospheric NO2 column data from the OMI sensor from www.temis.nl.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jeremy D. Silver
    • 1
  • Jesper H. Christensen
    • 1
  • Michael Kahnert
    • 2
  • Lennart Robertson
    • 2
  • Jørgen Brandt
    • 1
  1. 1.Department of Environmental ScienceAarhus UniversityAarhusDenmark
  2. 2.Research DepartmentSwedish Meteorological and Hydrological InstituteNorrköpingSweden

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