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https://doi.org/10.5194/hess-2019-557
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-557
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 16 Dec 2019

Submitted as: research article | 16 Dec 2019

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A revised version of this preprint is currently under review for the journal HESS.

Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogs

Damien Raynaud1, Benoit Hingray2, Guillaume Evin3, Anne-Catherine Favre1, and Jérémy Chardon1 Damien Raynaud et al.
  • 1Univ. Grenoble Alpes, Grenoble-INP, IGE UMR 5001, Grenoble, F-38000, France
  • 2Univ. Grenoble Alpes, CNRS, IGE UMR 5001, Grenoble, F-38000, France
  • 3Univ. Grenoble Alpes, Irstea, UR ETNA, Grenoble, France

Abstract. Natural risk studies such as flood risk assessments require long series of weather variables. As an alternative to observed series, which have a limited length, these data can be provided by weather generators. Among the large variety of existing ones, resampling methods based on analogues have the advantage of guaranteeing the physical consistency between local variables at each time step. However, they cannot generate values of predictands exceeding the range of observed values. Moreover, the length of the simulated series is typically limited to the length of the synoptic meteorology records used to characterize the large-scale atmospheric configuration of the generation day. To overcome those limitations, the stochastic weather generator proposed in this study combines two sampling approaches based on atmospheric analogues: (1) a synoptic weather generator in a first step, which recombines days in the 20th century to generate a 1000-year sequence of new atmospheric trajectories and (2) a stochastic downscaling model in a second step, applied to these atmospheric trajectories, in order to simulate long time series of daily regional precipitation and temperature. The method is applied to daily time series of mean areal precipitation and temperature in Switzerland. It is shown that the climatological characteristics of observed precipitation and temperature are adequately reproduced. It also improves the reproduction of extreme precipitation values, overcoming previous limitations of standard analog-based weather generators.

Damien Raynaud et al.

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Damien Raynaud et al.

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Short summary
This research paper proposes a weather generator combining two sampling approaches. A first generator recombines large-scale atmospheric situations. A second generator is applied to these atmospheric trajectories in order to simulate long time series of daily regional precipitation and temperature. The method is applied to daily time series in Switzerland. It reproduces adequately the observed climatology and improves the reproduction of extreme precipitation values.
This research paper proposes a weather generator combining two sampling approaches. A first...
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