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Future multivariate weather generation by combining Bartlett-Lewis and vine copula models

Jorn Van de Velde (UGent) , Matthias Demuzere (UGent) , Bernard De Baets (UGent) and Niko Verhoest (UGent)
(2023) HYDROLOGICAL SCIENCES JOURNAL. 68(1). p.1-15
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Abstract
The assessment of future extremes is hindered by the lack of long time series. Weather generators can alleviate this problem, but easily become complex. In this study, a weather generator combining Bartlett-Lewis models and vine copulas is presented. This combination allows for the generation of time series with statistics similar to those of the input. This model chain has never been assessed on the basis of future simulations. However, it could have value for extending climate simulations. The model chain was applied to historical observations and one climate model time series. The statistical moments and the correlation on the basis of the future simulations were comparable to those on basis of the historical observations. The results for the extremes were ambiguous, but still provided valuable information. The adequate performance for the statistical moments and the correlation indicates that the weather generator might be useful for the characterization of future extremes.
Keywords
weather generation, copulas, Bartlett-Lewis models, climate change, POINT PROCESS MODELS, RANDOM-VARIABLES, BIAS CORRECTION, TIME-SERIES, RAINFALL, CLIMATE, PRECIPITATION, CONSTRUCTIONS, DEPENDENCE, FLOODS

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Citation

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MLA
Van de Velde, Jorn, et al. “Future Multivariate Weather Generation by Combining Bartlett-Lewis and Vine Copula Models.” HYDROLOGICAL SCIENCES JOURNAL, vol. 68, no. 1, 2023, pp. 1–15, doi:10.1080/02626667.2022.2144322.
APA
Van de Velde, J., Demuzere, M., De Baets, B., & Verhoest, N. (2023). Future multivariate weather generation by combining Bartlett-Lewis and vine copula models. HYDROLOGICAL SCIENCES JOURNAL, 68(1), 1–15. https://doi.org/10.1080/02626667.2022.2144322
Chicago author-date
Van de Velde, Jorn, Matthias Demuzere, Bernard De Baets, and Niko Verhoest. 2023. “Future Multivariate Weather Generation by Combining Bartlett-Lewis and Vine Copula Models.” HYDROLOGICAL SCIENCES JOURNAL 68 (1): 1–15. https://doi.org/10.1080/02626667.2022.2144322.
Chicago author-date (all authors)
Van de Velde, Jorn, Matthias Demuzere, Bernard De Baets, and Niko Verhoest. 2023. “Future Multivariate Weather Generation by Combining Bartlett-Lewis and Vine Copula Models.” HYDROLOGICAL SCIENCES JOURNAL 68 (1): 1–15. doi:10.1080/02626667.2022.2144322.
Vancouver
1.
Van de Velde J, Demuzere M, De Baets B, Verhoest N. Future multivariate weather generation by combining Bartlett-Lewis and vine copula models. HYDROLOGICAL SCIENCES JOURNAL. 2023;68(1):1–15.
IEEE
[1]
J. Van de Velde, M. Demuzere, B. De Baets, and N. Verhoest, “Future multivariate weather generation by combining Bartlett-Lewis and vine copula models,” HYDROLOGICAL SCIENCES JOURNAL, vol. 68, no. 1, pp. 1–15, 2023.
@article{01GY733KDR15QKR7ZBNTQJ9FBQ,
  abstract     = {{The assessment of future extremes is hindered by the lack of long time series. Weather generators can alleviate this problem, but easily become complex. In this study, a weather generator combining Bartlett-Lewis models and vine copulas is presented. This combination allows for the generation of time series with statistics similar to those of the input. This model chain has never been assessed on the basis of future simulations. However, it could have value for extending climate simulations. The model chain was applied to historical observations and one climate model time series. The statistical moments and the correlation on the basis of the future simulations were comparable to those on basis of the historical observations. The results for the extremes were ambiguous, but still provided valuable information. The adequate performance for the statistical moments and the correlation indicates that the weather generator might be useful for the characterization of future extremes.}},
  author       = {{Van de Velde, Jorn and Demuzere, Matthias and De Baets, Bernard and Verhoest, Niko}},
  issn         = {{0262-6667}},
  journal      = {{HYDROLOGICAL SCIENCES JOURNAL}},
  keywords     = {{weather generation,copulas,Bartlett-Lewis models,climate change,POINT PROCESS MODELS,RANDOM-VARIABLES,BIAS CORRECTION,TIME-SERIES,RAINFALL,CLIMATE,PRECIPITATION,CONSTRUCTIONS,DEPENDENCE,FLOODS}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{1--15}},
  title        = {{Future multivariate weather generation by combining Bartlett-Lewis and vine copula models}},
  url          = {{http://doi.org/10.1080/02626667.2022.2144322}},
  volume       = {{68}},
  year         = {{2023}},
}
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