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Impact of Special Features of Numerically Predicted and Analysed Meteorological Data on the Results of Ozone Forecast by a PBL-CTM

  • J. Flemming
  • E. Reimer
  • R. Stern

Abstract

The Freie Universität Berlin and IVU1 develop a complex ozone forecast system, which combines statistical and fuzzy methods with regional Eulerian transport modelling. Each method is an independent forecast tool focussing on different spatial and temporal scales. The statistically and fuzzy based forecast is locally applied, whereas the Eulerian transport model predicts the large scale development of ozone patterns. The results of the transport modelling will be used as an additional parameter for the statistical and fuzzy methods in a framework of a neuro fuzzy module. Ideally, the combination of both approaches shall improve the forecast performance (Reimer and Dlabka, 1998).

Keywords

Cloud Cover Ozone Concentration Forecast Error Ozone Maximum Horizontal Grid Resolution 
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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References

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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • J. Flemming
    • 1
  • E. Reimer
    • 1
  • R. Stern
    • 1
  1. 1.Institut für MeteorologieFreie Universität BerlinBerlinGermany

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