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| Titel |
Implementation and validation of a Wilks-type multi-site daily precipitation generator over a typical Alpine river catchment |
| VerfasserIn |
D. E. Keller, A. M. Fischer, C. Frei, M. A. Liniger, C. Appenzeller, R. Knutti |
| 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 ; 19, no. 5 ; Nr. 19, no. 5 (2015-05-06), S.2163-2177 |
| Datensatznummer |
250120704
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| Publikation (Nr.) |
 copernicus.org/hess-19-2163-2015.pdf |
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| Zusammenfassung |
Many climate
impact assessments require high-resolution precipitation time series that
have a spatio-temporal correlation structure consistent with observations,
for simulating either current or future climate conditions. In this respect,
weather generators (WGs) designed and calibrated for multiple sites are an
appealing statistical downscaling technique to stochastically simulate
multiple realisations of possible future time series consistent with the
local precipitation characteristics and their expected future changes. In
this study, we present the implementation and validation of a multi-site
daily precipitation generator re-built after the methodology described in
Wilks (1998). The generator consists of several Richardson-type WGs run with
spatially correlated random number streams. This study aims at investigating
the capabilities, the added value and the limitations of the precipitation
generator for a typical Alpine river catchment in the Swiss Alpine region
under current climate.
The calibrated multi-site WG is skilful at individual sites in representing
the annual cycle of the precipitation statistics, such as mean wet day
frequency and intensity as well as monthly precipitation sums. It reproduces
realistically the multi-day statistics such as the frequencies of dry and wet
spell lengths and precipitation sums over consecutive wet days. Substantial
added value is demonstrated in simulating daily areal precipitation sums in
comparison to multiple WGs that lack the spatial dependency in the stochastic
process. Limitations are seen in reproducing daily and multi-day extreme
precipitation sums, observed variability from year to year and in reproducing
long dry spell lengths. Given the performance of the presented generator, we
conclude that it is a useful tool to generate precipitation series consistent
with the mean climatic aspects and likely helpful to be used as a downscaling
technique for climate change scenarios. |
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