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JOURNAL OF GEOPHYSICAL RESEARCH,
VOL. 111,
D18302,
11 PP., 2006
doi:10.1029/2005JD006675
Ensemble-based air quality forecasts: A multimodel approach applied to ozone
Centre d'Enseignement et de Recherche en Environnement Atmosphérique, École Nationale des Ponts et Chaussées/Électricité de France Recherche et Développement, Marne la Vallée, France
Centre d'Enseignement et de Recherche en Environnement Atmosphérique, École Nationale des Ponts et Chaussées/Électricité de France Recherche et Développement, Marne la Vallée, France
The potential of ensemble techniques to improve ozone forecasts is investigated. Ensembles with up to 48 members (models) are generated using the modeling system Polyphemus. Members differ in their physical parameterizations, their numerical approximations, and their input data. Each model is evaluated during 4 months (summer 2001) over Europe with hundreds of stations from three ozone-monitoring networks. We found that several linear combinations of models have the potential to drastically increase the performances of model-to-data comparisons. Optimal weights associated with each model are not robust in time or space. Forecasting these weights therefore requires relevant methods, such as selection of adequate learning data sets, or specific learning algorithms. Significant performance improvements are accomplished by the resulting forecasted combinations. A decrease of about 10% of the root-mean-square error is obtained on ozone daily peaks. Ozone hourly concentrations show stronger improvements.
Received 16 September 2005; accepted 18 May 2006; published 21 September 2006.
Citation: (2006), Ensemble-based air quality forecasts: A multimodel approach applied to ozone, J. Geophys. Res., 111, D18302, doi:10.1029/2005JD006675.
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