Please use this identifier to cite or link to this item:
Publisher DOI: 10.1088/1367-2630/18/1/013017
Title: Capturing rogue waves by multi-point statistics
Language: English
Authors: Hadjihosseini, Ali 
Wächter, Matthias 
Hoffmann, Norbert  
Peinke, Joachim 
Keywords: Stochastic process;complex systems;multi-point statistics;rogue wave;prediction
Issue Date: 12-Jan-2016
Publisher: IOP
Source: New Journal of Physics 1 (18): 013017- (2016)
Journal or Series Name: New journal of physics 
Abstract (english): As an example of a complex system with extreme events, we investigate ocean wave states exhibiting rogue waves. We present a statistical method of data analysis based on multi-point statistics which for the first time allows the grasping of extreme rogue wave events in a highly satisfactory statistical manner. The key to the success of the approach is mapping the complexity of multi-point data onto the statistics of hierarchically ordered height increments for different time scales, for which we can show that a stochastic cascade process with Markov properties is governed by a Fokker-Planck equation. Conditional probabilities as well as the Fokker-Planck equation itself can be estimated directly from the available observational data. With this stochastic description surrogate data sets can in turn be generated, which makes it possible to work out arbitrary statistical features of the complex sea state in general, and extreme rogue wave events in particular. The results also open up new perspectives for forecasting the occurrence probability of extreme rogue wave events, and even for forecasting the occurrence of individual rogue waves based on precursory dynamics.
DOI: 10.15480/882.2126
ISSN: 1367-2630
Institute: Strukturdynamik M-14 
Type: (wissenschaftlicher) Artikel
License: CC BY 3.0 (Attribution) CC BY 3.0 (Attribution)
Appears in Collections:Publications with fulltext

Files in This Item:
File Description SizeFormat
Hadjihosseini_2016_New_J._Phys._18_013017.pdfVerlags-PDF1,71 MBAdobe PDFThumbnail
Show full item record

Page view(s)

Last Week
Last month
checked on Oct 1, 2020


checked on Oct 1, 2020

Google ScholarTM


Note about this record


This item is licensed under a Creative Commons License Creative Commons