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  4. Simulation of rainfall time series from different climatic regions using the direct sampling technique
 
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Simulation of rainfall time series from different climatic regions using the direct sampling technique

Auteur(s)
Oriani, Fabio 
Centre d'hydrogéologie et de géothermie 
Straubhaar, Julien 
Centre d'hydrogéologie et de géothermie 
Renard, Philippe 
Centre d'hydrogéologie et de géothermie 
Mariethoz, Grégoire 
Centre d'hydrogéologie et de géothermie 
Date de parution
2014
In
HYDROLOGY AND EARTH SYSTEM SCIENCES
Vol.
8
No
18
De la page
3015
A la page
3031
Mots-clés
  • LOW-FREQUENCY VARIABI...

  • DAILY PRECIPITATION

  • STOCHASTIC GENERATION...

  • CONDITIONAL SIMULATIO...

  • ATMOSPHERIC

Résumé
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.
URI
https://libra.unine.ch/handle/123456789/23428
DOI
10.5194/hess-18-3015-2014
Autre version
http://dx.doi.org/10.5194/hess-18-3015-2014
Type de publication
Resource Types::text::journal::journal article
Dossier(s) à télécharger
 main article: 2023-01-10_110_7261.pdf (6.05 MB)
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