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| Titel |
On the importance of observational data properties when assessing regional climate model performance of extreme precipitation |
| VerfasserIn |
M. A. Sunyer, H. J. D. Sørup, O. B. Christensen, H. Madsen, D. Rosbjerg, P. S. Mikkelsen, K. Arnbjerg-Nielsen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 17, no. 11 ; Nr. 17, no. 11 (2013-11-01), S.4323-4337 |
| Datensatznummer |
250085981
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| Publikation (Nr.) |
 copernicus.org/hess-17-4323-2013.pdf |
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| Zusammenfassung |
In recent years, there has been an increase in the number of climate studies
addressing changes in extreme precipitation. A common step in these studies
involves the assessment of the climate model performance. This is often
measured by comparing climate model output with observational data. In the
majority of such studies the characteristics and uncertainties of the
observational data are neglected.
This study addresses the influence of using different observational data sets
to assess the climate model performance. Four different data sets covering
Denmark using different gauge systems and comprising both networks of point
measurements and gridded data sets are considered. Additionally, the
influence of using different performance indices and metrics is addressed. A
set of indices ranging from mean to extreme precipitation properties is
calculated for all the data sets. For each of the observational data sets, the
regional climate models (RCMs) are ranked according to their performance
using two different metrics. These are based on the error in representing
the indices and the spatial pattern.
In comparison to the mean, extreme precipitation indices are highly
dependent on the spatial resolution of the observations. The spatial pattern
also shows differences between the observational data sets. These differences
have a clear impact on the ranking of the climate models, which is highly
dependent on the observational data set, the index and the metric used. The
results highlight the need to be aware of the properties of observational
data chosen in order to avoid overconfident and misleading conclusions with
respect to climate model performance. |
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