Abstract
The paper is focused on the formulation of an adequate criterion for associating wave storm events to the generating wind storm ones, and on the study of correlation between their characteristic parameters. In this context, the sea storm definition commonly used for storm identification from significant wave height data is adapted for wind storm, by processing wind speed data. A sensitivity analysis is proposed as function of the storm thresholds aiming at identifying optimal combination of wind speed and significant wave height thresholds allowing the association of relatively large number of events ensuring high correlation between wind and wave storm parameters. The analysis is carried out using as input data wind speeds and significant wave heights from four meteorological (buoys and anemometers) stations of the National Data Buoy Center moored off the East Coast of the United States. Results reveal that an optimal threshold combination is achieved assuming both wind speed and significant wave height threshold as 1.5 time their respective averages.
Highlights
Wind peaks are extrapolated from long wind speed time series with a systematic selection method without any consideration of climatic aspects, and are used for long-term statistical estimations and design value calculation; among these selection criteria are: Gumbel’s method [28] in which the largest values per fixed time period is selected; its extension with the selection of the r-largest value over a given time duration [29]; the method of independent storms [30,31] that uses a period of wind speeds below a selected threshold to separate storms; and the Peak-over-threshold (POT) method that extracts maxima from sample data series to produce a series of extreme values above a chosen, adequately high, threshold [32,33]
An optimal combination of such thresholds is suggested as a result of the proposed analysis
It is possible to associate a large number of correlated wind and wave storm events
Summary
The study of offshore climate plays a key role for any activity developed in offshore sea environment, including navigation, oil and gas, and offshore wind and wave farms. The paper is organized as follows: section 2 describes the data used and the site, section 3 introduces the storms identification and association criterion, section 4 shows data analysis on the basis of the proposed criterion, and section 5 illustrates some concluding remarks Results of this analysis are useful for survivability, reliability, and operability assessments of combined wind and wave systems, which take advantage of the complementarity of these resources. In this regard, the understanding of how nonstationary wind and wave events follow each other, their shift in terms of beginning time, time lag between peaks, and correlation over common time window where both persist over certain ranges of values, represent key elements in the development of combined technologies. They can provide preliminary information on how to couple wind and wave states over longer time interval than those commonly considered in response assessments of offshore wind systems, for which wind and waves represent the main load factors
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