Articles | Volume 22, issue 1
https://doi.org/10.5194/hess-22-655-2018
https://doi.org/10.5194/hess-22-655-2018
Research article
 | 
25 Jan 2018
Research article |  | 25 Jan 2018

Stochastic generation of multi-site daily precipitation focusing on extreme events

Guillaume Evin, Anne-Catherine Favre, and Benoit Hingray

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Cited articles

Ailliot, P., Allard, D., Monbet, V., and Naveau, P.: Stochastic weather generators: an overview of weather type models, Journal de la Société Frano̧aise de Statistique, 156, 101–113, 2015.
Allard, D. and Bourotte, M.: Disaggregating daily precipitations into hourly values with a transformed censored latent Gaussian process, Stoch. Environ. Res. Risk. Assess., 29, 453–462, 2015.
Baxevani, A. and Lennartsson, J.: A spatiotemporal precipitation generator based on a censored latent Gaussian field, Water Resour. Res., 51, 4338–4358, 2015.
Bennett, B., Thyer, M., Leonard, M., Lambert, M., and Bates, B.: A comprehensive and systematic evaluation framework for a parsimonious daily rainfall field model, J. Hydrol., 556, 1123–1138, https://doi.org/10.1016/j.jhydrol.2016.12.043, 2018.
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Short summary
This research paper proposes a multi-site daily precipitation model, named GWEX, which aims to reproduce the statistical features of extremely rare events at different temporal and spatial scales. Recent advances and various statistical methods (regionalization, disaggregation) are considered in order to obtain a robust and appropriate representation of the most extreme precipitation fields. Performances are shown with an application to 105 stations, covering a large region in Switzerland.
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