Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 359896
Title Is regional air quality model diversity representative of uncertainty for ozone simulation?
Author(s) Vautard, R.; Loon, M. van; Schaap, M.; Bergstrom, R.; Bessagnet, B.; Brandt, J.; Builtjes, P.J.H.; Christensen, J.H.; Cuvelier, C.; Graff, A.; Jonson, J.E.; Krol, M.C.; Langner, J.; Roberts, P.; Rouil, L.; Stern, R.; Tarrason, L.; Thunis, P.; Vignati, E.; White, L.; Wind, P.
Source Geophysical Research Letters 33 (2006). - ISSN 0094-8276 - 5 p.
DOI https://doi.org/10.1029/2006GL027610
Department(s) Meteorology and Air Quality
WIMEK
Publication type Refereed Article in a scientific journal
Publication year 2006
Keyword(s) pollution model - western-europe - ensemble
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.
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