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• W2912647535 abstract "Significance Understanding and predicting extreme events and their anomalous statistics in complex nonlinear systems are a grand challenge in applied sciences as well as for engineering design. Recent controlled laboratory experiments in weakly turbulent shallow water with abrupt depth change exhibit a remarkable transition from nearly Gaussian statistics to extreme anomalous statistics with large positive skewness of the surface height. We develop a statistical dynamical model to explain and quantitatively predict the anomalous statistical behavior. Incoming and outgoing waves are modeled by the truncated Korteweg–de Vries equations statistically matched at the depth change. The statistical matching of the known nearly Gaussian incoming Gibbs state completely determines the predicted anomalous outgoing Gibbs state and successfully captures key features of the experiment." @default.
• W2912647535 created "2019-02-21" @default.
• W2912647535 creator A5051877960 @default.
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• W2912647535 date "2019-02-13" @default.
• W2912647535 modified "2023-10-16" @default.
• W2912647535 title "Statistical dynamical model to predict extreme events and anomalous features in shallow water waves with abrupt depth change" @default.
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• W2912647535 doi "https://doi.org/10.1073/pnas.1820467116" @default.
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