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| Titel |
Pauci ex tanto numero: reduce redundancy in multi-model ensembles |
| VerfasserIn |
E. Solazzo, A. Riccio, 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 ; 13, no. 16 ; Nr. 13, no. 16 (2013-08-22), S.8315-8333 |
| Datensatznummer |
250085644
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| Publikation (Nr.) |
 copernicus.org/acp-13-8315-2013.pdf |
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| Zusammenfassung |
| We explicitly address the fundamental issue of member diversity in
multi-model ensembles. To date, no attempts in this direction have been documented
within the air quality (AQ) community despite the extensive use of
ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of
independence, undermining the significance of a multi-model ensemble, and
are the subject of this study. Shared, dependant biases among models do not
cancel out but will instead determine a biased ensemble. Redundancy derives from
having too large a portion of common variance among the members of the
ensemble, producing overconfidence in the predictions and underestimation of
the uncertainty. The two issues of common biases and redundancy are analysed
in detail using the AQMEII ensemble of AQ model results for four air
pollutants in two European regions. We show that models share large portions
of bias and variance, extending well beyond those induced by common inputs.
We make use of several techniques to further show that subsets of models can
explain the same amount of variance as the full ensemble with the advantage
of being poorly correlated. Selecting the members for generating skilful,
non-redundant ensembles from such subsets proved, however, non-trivial. We
propose and discuss various methods of member selection and rate the
ensemble performance they produce. In most cases, the full ensemble is
outscored by the reduced ones. We conclude that, although independence of
outputs may not always guarantee enhancement of scores (but this depends
upon the skill being investigated), we discourage selecting the members of
the ensemble simply on the basis of scores; that is, independence and skills
need to be considered disjointly. |
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