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Titel |
Simulation of rainfall time series from different climatic regions using the direct sampling technique |
VerfasserIn |
F. Oriani, J. Straubhaar, P. Renard, G. Mariethoz |
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 ; 18, no. 8 ; Nr. 18, no. 8 (2014-08-14), S.3015-3031 |
Datensatznummer |
250120434
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Publikation (Nr.) |
copernicus.org/hess-18-3015-2014.pdf |
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Zusammenfassung |
The direct sampling technique, belonging to the family of multiple-point
statistics, is proposed as a nonparametric alternative to the classical
autoregressive and Markov-chain-based models for daily rainfall time-series
simulation. The algorithm makes use of the patterns contained inside the
training image (the past rainfall record) to reproduce the complexity of the
signal without inferring its prior statistical model: the time series is
simulated by sampling the training data set where a sufficiently similar
neighborhood exists. The advantage of this approach is the capability of
simulating complex statistical relations by respecting the similarity of the
patterns at different scales. The technique is applied to daily rainfall
records from different climate settings, using a standard setup and without
performing any optimization of the parameters. The results show that the
overall statistics as well as the dry/wet spells patterns are simulated
accurately. Also the extremes at the higher temporal scale are reproduced
adequately, reducing the well known problem of overdispersion. |
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