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| Titel |
Stochastic bias-correction of daily rainfall scenarios for hydrological applications |
| VerfasserIn |
I. Portoghese, E. Bruno, N. Guyennon, V. Iacobellis |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 11, no. 9 ; Nr. 11, no. 9 (2011-09-22), S.2497-2509 |
| Datensatznummer |
250009674
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| Publikation (Nr.) |
 copernicus.org/nhess-11-2497-2011.pdf |
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| Zusammenfassung |
The accuracy of rainfall predictions provided by climate models is crucial
for the assessment of climate change impacts on hydrological processes. In
fact, the presence of bias in downscaled precipitation may produce large
bias in the assessment of soil moisture dynamics, river flows and
groundwater recharge.
In this study, a comparison between statistical properties of rainfall
observations and model control simulations from a Regional Climate Model
(RCM) was performed through a robust and meaningful representation of the
precipitation process. The output of the adopted RCM was analysed and
re-scaled exploiting the structure of a stochastic model of the point
rainfall process. In particular, the stochastic model is able to adequately
reproduce the rainfall intermittency at the synoptic scale, which is one of
the crucial aspects for the Mediterranean environments. Possible alteration
in the local rainfall regime was investigated by means of the historical
daily time-series from a dense rain-gauge network, which were also used for
the analysis of the RCM bias in terms of dry and wet periods and storm
intensity. The result is a stochastic scheme for bias-correction at the
RCM-cell scale, which produces a realistic representation of the daily
rainfall intermittency and precipitation depths, though a residual bias in
the storm intensity of longer storm events persists. |
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