Statistical dynamical model to predict extreme events and anomalous features in shallow water waves with abrupt depth change.

ABSTRACT: Understanding and predicting extreme events and their anomalous statistics in complex nonlinear systems are a grand challenge in climate, material, and neuroscience as well as for engineering design. Recent laboratory experiments in weakly turbulent shallow water reveal a remarkable transition from Gaussian to anomalous behavior as surface waves cross an abrupt depth change (ADC). Downstream of the ADC, probability density functions of surface displacement exhibit strong positive skewness accompanied by an elevated level of extreme events. Here, we develop a statistical dynamical model to explain and quantitatively predict the above anomalous statistical behavior as experimental control parameters are varied. The first step is to use incoming and outgoing truncated Korteweg-de Vries (TKdV)

SUBMITTER: Majda AJ 

PROVIDER: S-EPMC6410832 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature