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首页> 外文期刊>Journal of Physical Oceanography >Uncertainty Propagation Using Polynomial Chaos Expansions for Extreme Sea Level Hazard Assessment: The Case of the Eastern Adriatic Meteotsunamis
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Uncertainty Propagation Using Polynomial Chaos Expansions for Extreme Sea Level Hazard Assessment: The Case of the Eastern Adriatic Meteotsunamis

机译：利用多项式混沌扩建对极端海平面危害评估的不确定性繁殖：东部亚得里亚特·梅德拉米斯的案例

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摘要

This study quantifies the hazard associated with extreme sea levels due to eastern Adriatic meteotsunamis-long waves generated by traveling atmospheric disturbances-and assesses the sensitivity of the ocean response to the disturbances responsible for those events. In this spirit, a surrogate model of meteotsunami maximum elevation based on generalized polynomial chaos expansion (gPCE) methods, is implemented. The approach relies on the definition of a synthetic pressure disturbance-depending on six different stochastic parameters known to be important for meteotsunami generation, which is used as forcing to produce series of meteotsunami simulations defined with sparse grid methods (up to 10 689 used in this study). The surrogate model and the sensitivity study are then obtained with a pseudo-spectral approximation (PSA) method based on the chosen meteotsunami simulations. This study mainly presents the developed methodology and discusses the feasibility of implementing such gPCE-based surrogate models to assess the hazard and to study the sensitivity of meteorologically driven extreme sea levels.
机译：本研究量化了由于通过旅行大气扰动产生的东部亚得里亚特杜诸滴度而导致与极端海平面相关的危害 - 并评估海洋反应对这些事件负责的干扰的敏感性。在这种精神下，实施了基于广义多项式混沌扩展（GPCE）方法的Meteotsunami最大高程的代理模型。该方法依赖于合成压力干扰的定义 - 取决于已知的六种不同的随机参数对于MeteotsunaMI生成很重要，这被用作强制生产具有稀疏网格方法定义的Meteotsunami模拟（最多10 689学习）。然后通过基于所选择的Meteotsunami模拟的伪光谱近似（PSA）方法获得替代模型和灵敏度研究。本研究主要介绍了发达的方法，并探讨了实施这种基于GPCE的代理模型的可行性，以评估危害，并研究气象驱动的极端海平面的敏感性。

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  • 来源
    《Journal of Physical Oceanography》 |2020年第4期|1005-1021|共17页
  • 作者

    CLEA DENAMIEL; XUN HUAN; JADRANKA SEPIC; IVICA VILIBIC;

  • 作者单位

    Institute of Oceanography and Fisheries Split Croatia;

    University of Michigan Ann Arbor Michigan;

    Institute of Oceanography and Fisheries Split Croatia;

    Institute of Oceanography and Fisheries Split Croatia;

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  • 正文语种 eng
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