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|Title:||Is Regional Air Quality Model Diversity Representative of Uncertainty for Ozone Simulation?|
|Authors:||VAUTARD R.; VAN LOON M.; SCHAAP M.; BERGSTRØM R.; BESSAGNET B.; BRANDT J.; BUILTJES P.; KRISTENSEN J.; CUVELIER CORNELIS; GRAFF A.; JONSON J.E.; KROL M.; LANGNER J.; ROBERTS P.; ROUIL L.; STERN R.; TARRASON LEONOR; THUNIS PHILIPPE; VIGNATI ELISABETTA; WHITE L.; WIND P.|
|Citation:||GEOPHYSICAL RESEARCH LETTERS vol. 33 p. L24818-1 L24818-5|
|Publisher:||AMER GEOPHYSICAL UNION|
|Type:||Articles in periodicals and books|
|Abstract:||We examine whether an ensemble of seven state-of-the-art European regional air quality models provide a spread of ozone daily maxima that is representative of the simulated uncertainty. Using tools borrowed from the evaluation of ensemble weather forecasting, we analyze statistics of ozone daily maxima over an entire summer season. Although the ensemble has an average positive bias, the distribution of simulated concentrations is representative of the uncertainty. The ensemble spread is partly due to fluctuations resulting from differences in model formulations and input data, but also to the spread between individual model average biases. The variability of the uncertainty is fairly well reproduced by the ensemble. The skill of the ensemble in predicting uncertainty and its variability is also demonstrated by evaluating the reliability of probabilistic prediction of threshold exceedances. These results let us hope that the ensemble can be used for evaluation of the impact of emission reduction policies and its uncertainty.|
|JRC Institute:||Sustainable Resources|
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