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Is regional air quality model diversity representative of uncertainty for ozone simulation?

  • Robert Vautard
  • , M. Van Loon
  • , M. Schaap
  • , R. Bergström
  • , B. Bessagnet
  • , J. Brandt
  • , P. J.H. Builtjes
  • , J. H. Christensen
  • , C. Cuvelier
  • , A. Graff
  • , J. E. Jonson
  • , M. Krol
  • , J. Langner
  • , P. Roberts
  • , L. Rouil
  • , R. Stern
  • , L. Tarrasón
  • , P. Thunis
  • , E. Vignati
  • , L. White
  • P. Wind
  • UVSQ
  • European Monitoring and Evaluation Programme
  • University of Oslo
  • Netherlands Organisation for Applied Scientific Research (TNO)
  • Swedish Meteorological and Hydrological Institute
  • INERIS Institut National de l'Environnement Industriel et des Risques
  • Aarhus University
  • European Commission-Directorate General Joint Research Centre
  • European Commission Joint Research Centre
  • Federal Environment Agency
  • SRON - Netherlands Institute for Space Research
  • Conservation of Clean Air and Water in Europe
  • Shell Global Solutions
  • Institute National de l'Environnement Industrial et des Risques
  • Institut für Meteorologie
  • Free University of Berlin
  • Conservation of Clean Air and Water in Europe

Research output: Contribution to journal › Article › peer-review

30 Citations (Scopus)

Abstract

We examine whether seven state-of-the-art European regional air quality models provide daily ensembles of predicted ozone maxima that encompass observations. Using tools borrowed from the evaluation of ensemble weather forecasting, we analyze statistics of simulated ensembles of ozone daily maxima over an entire summer season. Although the model ensemble overestimates ozone, the distribution of simulated concentrations is representative of the uncertainty. The spread of simulations is due to random fluctuations resulting from differences in model formulations and input data, but also to the spread between individual model systematic biases. The ensemble average skill increases as the spread decreases. The skill of the ensemble in giving probabilistic predictions of threshold exceedances is also demonstrated. These results allow for optimism about the ability of this ensemble to simulate the uncertainty of the impact of emission control scenarios.

Original languageEnglish
Article numberL24818
JournalGeophysical Research Letters
Volume33
Issue number24
DOIs
Publication statusPublished - 28 Dec 2006
Externally publishedYes

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