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| Titel |
E pluribus unum*: ensemble air quality predictions |
| VerfasserIn |
S. Galmarini, I. Kioutsioukis, E. Solazzo |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 13, no. 14 ; Nr. 13, no. 14 (2013-07-29), S.7153-7182 |
| Datensatznummer |
250018785
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| Publikation (Nr.) |
 copernicus.org/acp-13-7153-2013.pdf |
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| Zusammenfassung |
In this study we present a novel approach for improving the air quality
predictions using an ensemble of air quality models generated in the context
of AQMEII (Air Quality Model Evaluation International Initiative). The
development of the forecasting method makes use of modelled and observed time
series (either spatially aggregated or relative to single monitoring
stations) of ozone concentrations over different areas of Europe and North
America. The technique considers the underlying forcing mechanisms on ozone
by means of spectrally decomposed previsions. With the use of diverse
applications, we demonstrate how the approach screens the ensemble members,
extracts the best components and generates bias-free forecasts with improved
accuracy over the candidate models. Compared to more traditional forecasting
methods such as the ensemble median, the approach reduces the forecast error
and at the same time it clearly improves the modelled variance. Furthermore,
the result is not a mere statistical outcome depended on the quality of the
selected members. The few individual cases with degraded performance are
also identified and analysed. Finally, we show the extensions of the
approach to other pollutants, specifically particulate matter and nitrogen
dioxide, and provide a framework for its operational implementation.
*One out of many |
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