On defining storm intervals: Extreme wave analysis using extremal index inferencing of the run length parameter
| Autor: | Charikleia Oikonomou, M. Gradowski, António Sarmento, C. Kalogeri |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Environmental Engineering
Index (economics) Meteorology 020209 energy Fetch Ocean Engineering Storm 02 engineering and technology Function (mathematics) 01 natural sciences Swell 010305 fluids & plasmas symbols.namesake 0103 physical sciences 0202 electrical engineering electronic engineering information engineering symbols Hindcast Pareto distribution Significant wave height Physics::Atmospheric and Oceanic Physics Mathematics |
| Zdroj: | Ocean Engineering. 217:107988 |
| ISSN: | 0029-8018 |
| Popis: | Extreme wave analysis is essential for the design and deployment of marine structures. Since extremes in natural phenomena tend to occur in clusters, it is necessary to de-cluster them in order to form a dataset of independent samples. There are several algorithms used to identify independent storms (clusters of significant wave height extremes), most of which have the disadvantage of relying on an arbitrarily selected de-clustering parameter. In this paper, an existing statistical method for systematic cluster size inferencing is used with runs de-clustering, and applied for the first time to extreme wave analysis. The Generalised Pareto Distribution (GPD) is fitted to an extreme wave dataset, and the return periods of significant wave height extremes are calculated using the resulting model function. The methodology proposed in this paper is illustrated using hindcast data for the winter months of two locations: one that is exposed to the long Atlantic swell off the west coast of France, and another in the North Sea that is characterised by short fetch. This work demonstrates how extremal index estimation may be used in conjunction with the well-known runs de-clustering algorithm to predict the return periods of significant wave height extremes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect