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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Skill and uncertainty of a regional air quality model ensemble
Vautard, R. ; Schaap, M. ; Bergström, R. ; Bessagnet, B. ; Brandt, J. ; Builtjes, P.J.H. ; Krol, M.C. - \ 2009
Atmospheric Environment 43 (2009)31. - ISSN 1352-2310 - p. 4822 - 4832.
2003 heat-wave - climate-change - pollution model - western-europe - surface ozone - aerosol - simulations - summer - validation - transport
Recently several regional air quality projects were carried out to support the negotiation under the Clean Air For Europe (CAFE) programme by predicting the impact of emission control policies with an ensemble of models. Within these projects, CITYDELTA and EURODELTA, the fate of air quality at the scale of European cities or that of the European continent was studied using several models. In this article we focus on the results of EURODELTA. The predictive skill of the ensemble of models is described for ozone, nitrogen dioxide and secondary inorganic compounds, and the uncertainty in air quality modelling is examined through the model ensemble spread of concentrations. For ozone daily maxima the ensemble spread origin differs from one region to another. In the neighbourhood of cities or in mountainous areas the spread of predicted values does not span the range of observed data, due to poorly resolved emissions or complex-terrain meteorology. By contrast in Atlantic and North Sea coastal areas the spread of predicted values is found to be larger than the observations. This is attributed to large differences in the boundary conditions used in the different models. For NO2 daily averages the ensemble spread is generally too small compared with observations. This is because models miss highest values occurring in stagnant meteorology in stable boundary layers near cities. For secondary particulate matter compounds the simulated concentration spread is more balanced, observations falling nearly equiprobably within the ensemble, and the spread originates both from meteorology and aerosol chemistry and thermodynamics
Evaluation of long-term ozone simulations from seven regional air quality models and their ensemble
Loon, M. van; Vautard, R. ; Schaap, M. ; Bergström, R. ; Bessagnet, B. ; Brandt, J. ; Krol, M.C. - \ 2007
Atmospheric Environment 41 (2007)10. - ISSN 1352-2310 - p. 2083 - 2097.
tropospheric ozone - pollution model - european cities - western-europe - impact - variability - citydelta - summer
Long-term ozone simulations from seven regional air quality models, the Unified EMEP model, LOTOS-EUROS, CHIMERE, RCG, MATCH, DEHM and TM5, are intercompared and compared to ozone measurements within the framework of the EuroDelta experiment, designed to assess air quality improvement at the European scale in response to emission reduction scenarios for 2020. Modelled ozone concentrations for the year 2001 are evaluated. The models reproduce the main features of the ozone diurnal cycle, but generally overestimate daytime ozone. LOTOS-EUROS and RCG have a more pronounced diurnal cycle variation than observations, while the reverse occurs for TM5. CHIMERE has a large positive bias, which can be explained by a systematic bias in boundary conditions. The other models and the ¿ensemble model¿, whose concentrations are by definition averaged over all models, represent accurately the diurnal cycle. The ability of the models to simulate day-to-day daily ozone average or maxima variability is examined by means of percentiles, root mean square errors and correlations. In general, daily maxima are better simulated than daily averages, and summertime concentrations are better simulated than wintertime concentrations. Summertime correlations range between 0.5 and 0.7 for daily averages and 0.6 and 0.8 for daily maxima. Two health-related indicators are used, the number of days of exceedance of the threshold for the daily maximal 8-h ozone concentration and the SOMO35. Both are well reproduced in terms of frequency, but the simultaneity of occurrence of exceedance days between observations and simulations is not well captured. The advantage of using an ensemble of models instead of a single model for the assessment of air quality is demonstrated. The ensemble average concentrations almost always exhibit a closer proximity to observations than any of the models. We also show that the spread of the model ensemble is fairly representative of the uncertainty in the simulations.
Is regional air quality model diversity representative of uncertainty for ozone simulation?
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. - \ 2006
Geophysical Research Letters 33 (2006). - ISSN 0094-8276 - 5 p.
pollution model - western-europe - ensemble
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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