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| Titel |
Climate model bias correction and the role of timescales |
| VerfasserIn |
J. O. Haerter, S. Hagemann, C. Moseley, C. Piani |
| 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 ; 15, no. 3 ; Nr. 15, no. 3 (2011-03-28), S.1065-1079 |
| Datensatznummer |
250012701
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| Publikation (Nr.) |
 copernicus.org/hess-15-1065-2011.pdf |
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| Zusammenfassung |
| It is well known that output from climate models cannot be used to force
hydrological simulations without some form of preprocessing to remove the
existing biases. In principle, statistical bias correction methodologies
act on model output so the statistical properties of the corrected data
match those of the observations. However, the improvements to the
statistical properties of the data are limited to the specific timescale
of the fluctuations that are considered. For example, a statistical bias
correction methodology for mean daily temperature values might be detrimental to
monthly statistics. Also, in applying bias corrections derived from
present day to scenario simulations, an assumption is made on the stationarity
of the bias over the largest timescales.
First, we point out several conditions that have to be fulfilled by model data
to make the application of a statistical bias correction meaningful.
We then examine the effects of mixing fluctuations on different timescales
and suggest an alternative statistical methodology, referred to here
as a cascade bias correction method, that eliminates, or greatly reduces, the negative
effects. |
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