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| Titel |
Simulating future precipitation extremes in a complex Alpine catchment |
| VerfasserIn |
C. Dobler, G. Bürger, J. Stötter  |
| 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 ; 13, no. 2 ; Nr. 13, no. 2 (2013-02-08), S.263-277 |
| Datensatznummer |
250017566
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| Publikation (Nr.) |
 copernicus.org/nhess-13-263-2013.pdf |
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| Zusammenfassung |
| The objectives of the present investigation are (i) to study the effects of
climate change on precipitation extremes and (ii) to assess the uncertainty
in the climate projections. The investigation is performed on the Lech
catchment, located in the Northern Limestone Alps. In order to estimate the
uncertainty in the climate projections, two statistical downscaling models
as well as a number of global and regional climate models were considered.
The downscaling models applied are the Expanded Downscaling (XDS) technique
and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS
model, which is driven by analyzed or simulated large-scale synoptic fields,
has been calibrated using ECMWF-interim reanalysis data and local station
data. LARS-WG is controlled through stochastic parameters representing local
precipitation variability, which are calibrated from station data only.
Changes in precipitation mean and variability as simulated by climate models
were then used to perturb the parameters of LARS-WG in order to generate
climate change scenarios. In our study we use climate simulations based on
the A1B emission scenario. The results show that both downscaling models
perform well in reproducing observed precipitation extremes. In general, the
results demonstrate that the projections are highly variable. The choice of
both the GCM and the downscaling method are found to be essential sources of
uncertainty. For spring and autumn, a slight tendency toward an increase in
the intensity of future precipitation extremes is obtained, as a number of
simulations show statistically significant increases in the intensity of
90th and 99th percentiles of precipitation on wet days as well as the
5- and 20-yr return values. |
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