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| Titel |
Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction |
| VerfasserIn |
E. P. Maurer, T. Das, D. R. Cayan |
| 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. 6 ; Nr. 17, no. 6 (2013-06-07), S.2147-2159 |
| Datensatznummer |
250018895
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| Publikation (Nr.) |
 copernicus.org/hess-17-2147-2013.pdf |
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| Zusammenfassung |
| When correcting for biases in general circulation model (GCM) output, for
example when statistically downscaling for regional and local impacts
studies, a common assumption is that the GCM biases can be characterized by
comparing model simulations and observations for a historical period. We
demonstrate some complications in this assumption, with GCM biases varying
between mean and extreme values and for different sets of historical years.
Daily precipitation and maximum and minimum temperature from late 20th
century simulations by four GCMs over the United States were compared to
gridded observations. Using random years from the historical record we
select a "base" set and a 10 yr independent "projected" set. We compare
differences in biases between these sets at median and extreme percentiles.
On average a base set with as few as 4 randomly-selected years is often
adequate to characterize the biases in daily GCM precipitation and
temperature, at both median and extreme values; 12 yr provided higher
confidence that bias correction would be successful. This suggests that some
of the GCM bias is time invariant. When characterizing bias with a set of
consecutive years, the set must be long enough to accommodate regional low
frequency variability, since the bias also exhibits this variability. Newer
climate models included in the Intergovernmental Panel on Climate Change
fifth assessment will allow extending this study for a longer observational
period and to finer scales. |
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