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| Titel |
Improving pan-European hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations |
| VerfasserIn |
R. Rojas, L. Feyen, A. Dosio, D. Bavera |
| 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. 8 ; Nr. 15, no. 8 (2011-08-24), S.2599-2620 |
| Datensatznummer |
250012929
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| Publikation (Nr.) |
 copernicus.org/hess-15-2599-2011.pdf |
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| Zusammenfassung |
| In this work we asses the benefits of removing bias in climate forcing data
used for hydrological climate change impact assessment at pan-European scale,
with emphasis on floods. Climate simulations from the HIRHAM5-ECHAM5 model
driven by the SRES-A1B emission scenario are corrected for bias using a
histogram equalization method. As target for the bias correction we
employ gridded interpolated observations of precipitation, average, minimum,
and maximum temperature from the E-OBS data set. Bias removal transfer
functions are derived for the control period 1961–1990. These are
subsequently used to correct the climate simulations for the control period,
and, under the assumption of a stationary error model, for the future time
window 2071–2100. Validation against E-OBS climatology in the control period
shows that the correction method performs successfully in removing bias in
average and extreme statistics relevant for flood simulation over the
majority of the European domain in all seasons. This translates into
considerably improved simulations with the hydrological model of observed
average and extreme river discharges at a majority of 554 validation river
stations across Europe. Probabilities of extreme events derived employing
extreme value techniques are also more closely reproduced. Results indicate
that projections of future flood hazard in Europe based on uncorrected
climate simulations, both in terms of their magnitude and recurrence
interval, are likely subject to large errors. Notwithstanding the inherent
limitations of the large-scale approach used herein, this study strongly
advocates the removal of bias in climate simulations prior to their use in
hydrological impact assessment. |
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