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DOI	10.5194/hess-24-4339-2020
	Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues
	Raynaud D.; Hingray B.; Evin G.; Favre A.-C.; Chardon J.
发表日期	2020
ISSN	1027-5606
起始页码	4339
结束页码	4352
卷号	24 期号:9
英文摘要	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 weather 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 meteorological records used to characterize the large-scale atmospheric configuration of the generation day. To overcome these 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 of 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 analogue-based weather generators. © 2020 Author(s).
语种	英语
scopus关键词	Cell proliferation; Floods; Precipitation (meteorology); Risk assessment; Stochastic models; Stochastic systems; Time series; Areal precipitation; Daily time series; Extreme precipitation; Flood risk assessments; Meteorological extremes; Meteorological records; Resampling method; Stochastic weather generator; Atmospheric temperature; assessment method; downscaling; extreme event; flood; long-term change; precipitation (climatology); risk assessment; sampling; simulation; synoptic meteorology; weather; Switzerland
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159314
作者单位	Raynaud, D., Univ. Grenoble Alpes, Grenoble-INP, Ige Umr 5001, Grenoble, 38000, France; Hingray, B., Univ. Grenoble Alpes, Cnrs, Ige Umr 5001, Grenoble, 38000, France; Evin, G., Inrae, Ur Etna, 2 rue de la Papeterie-BP 76, St-Martin-d'Hères, 38402, France; Favre, A.-C., Univ. Grenoble Alpes, Grenoble-INP, Ige Umr 5001, Grenoble, 38000, France; Chardon, J., Univ. Grenoble Alpes, Grenoble-INP, Ige Umr 5001, Grenoble, 38000, France
推荐引用方式 GB/T 7714	Raynaud D.,Hingray B.,Evin G.,et al. Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues[J],2020,24(9).
APA	Raynaud D.,Hingray B.,Evin G.,Favre A.-C.,&Chardon J..(2020).Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues.Hydrology and Earth System Sciences,24(9).
MLA	Raynaud D.,et al."Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues".Hydrology and Earth System Sciences 24.9(2020).