On Sampling Between Data of Significant Wave Height for Long-Term Analysis With Equivalent Triangular Storm Model

Abstract

This work proposes an analysis of storms in Pacific and Atlantic Ocean, which is carried out by applying the Boccotti’s Equivalent Triangular Storm (ETS) model. The ETS model represents any actual storm by means of two parameters. The former gives the storm intensity, which is equal to the maximum significant wave height during the actual storm; the latter represents the storm duration and it is such that the maximum expected wave height is the same in the actual storm and in the equivalent triangular storm. Data from buoys of the NOAA-NDBC (National Data Buoy Center, USA) are used in the applications, by considering different sampling Δt between two consecutive records, which varies between 1 and 6 hours. The sensitivity of the ETS model with the variation of Δt is investigated for the long-term modeling of severe storms. The results show that the structure of storms is strongly modified as Δt increases: both the intensity and the duration may change significantly. The effects of this results for long term statistics are investigated by means of the return period R(Hs > h) of a storm in which the maximum significant wave height exceeds the threshold h, which is evaluated by using data with different sampling Δt between two consecutive records. Finally for different values of the return period R, the return value of significant wave height and the mean persistence Dm(h), giving the mean time during which the significant wave height is greater than fixed threshold (in the storms where the threshold is exceeded), are calculated.