globalchange  > 气候变化与战略
DOI: 10.1016/j.atmosenv.2020.117313
论文题名:
Stochastic perturbations and dimension reduction for modelling uncertainty of atmospheric dispersion simulations
作者: Girard S.; Armand P.; Duchenne C.; Yalamas T.
刊名: Atmospheric Environment
ISSN: 1352-2310
出版年: 2020
卷: 224
语种: 英语
英文关键词: Clustering algorithms ; Dispersion (waves) ; Principal component analysis ; Stochastic models ; Stochastic systems ; Uncertainty analysis ; Atmospheric dispersion ; Perturbation ; Time Warp ; Uncertainty propagation ; Wind field ; Atmospheric movements ; dispersion ; modeling ; perturbation ; simulation ; stochasticity ; wind field ; article ; atmospheric dispersion ; principal component analysis ; simulation ; stochastic model ; uncertainty
学科: Atmospheric dispersion ; Perturbation ; Time warp ; Uncertainty propagation ; Wind field
中文摘要: Decision of emergency response to releases of hazardous material in the atmosphere increasingly rely on numerical simulations. This paper presents two contributions for accounting for the uncertainty inherent to those simulations. We first focused on one way of modelling these uncertainties, namely by applying stochastic perturbations to the inputs of the numerical dispersion model. We devised a generic mathematical formulation for time dependent perturbation of both amplitude and dynamics of the inputs. It allows a more thorough exploration of possible outcomes than simpler perturbations found in the literature. We then improved on the current state of the art on dimension reduction of atmospheric data. Indeed, most statistical methods cannot cope with high dimensional data such as the maps simulated with atmospheric dispersion models. Principal component analysis, the most widely used method for dimension reduction, relies on a linearity hypothesis that is not verified by these sets of maps. We conducted a very encouraging experiment with auto-associative models, a non-linear extension of this method. © 2020 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/160488
Appears in Collections:气候变化与战略

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作者单位: 18 boulevard de Reuilly, Phimeca, France; CEA, DAM, DIF, Arpajon, F-91297, France; Centre d'affaires du Zénith, 34 rue de Sarliève, Cournon d'Auvergne, 63800, France

Recommended Citation:
Girard S.,Armand P.,Duchenne C.,et al. Stochastic perturbations and dimension reduction for modelling uncertainty of atmospheric dispersion simulations[J]. Atmospheric Environment,2020-01-01,224
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