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| Titel |
De praeceptis ferendis: good practice in multi-model ensembles |
| VerfasserIn |
I. Kioutsioukis, S. Galmarini |
| 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 ; 14, no. 21 ; Nr. 14, no. 21 (2014-11-11), S.11791-11815 |
| Datensatznummer |
250119148
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| Publikation (Nr.) |
 copernicus.org/acp-14-11791-2014.pdf |
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| Zusammenfassung |
| Ensembles of air quality models have been formally and empirically shown to
outperform single models in many cases. Evidence suggests that ensemble error
is reduced when the members form a diverse and accurate ensemble. Diversity
and accuracy are hence two factors that should be taken care of while
designing ensembles in order for them to provide better predictions.
Theoretical aspects like the bias–variance–covariance decomposition and the
accuracy–diversity decomposition are linked together and support the
importance of creating ensemble that incorporates both these elements. Hence,
the common practice of unconditional averaging of models without prior
manipulation limits the advantages of ensemble averaging. We demonstrate the
importance of ensemble accuracy and diversity through an inter-comparison of
ensemble products for which a sound mathematical framework exists, and
provide specific recommendations for model selection and weighting
for multi-model ensembles. The sophisticated ensemble averaging
techniques, following proper training, were shown to have higher skill across
all distribution bins compared to solely ensemble averaging forecasts. |
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