https://doi.org/10.1140/epjs/s11734-024-01357-2
Regular Article
A numerical study for assessing the spectral wave characteristics during Hurricane Fiona
Vellore Institute of Technology, Vandalur-Kelambakkam Road, 600127, Chennai, Tamil Nadu, India
Received:
10
May
2024
Accepted:
1
October
2024
Published online:
15
October
2024
Designing marine facilities and issuing warning for any natural calamities relies on understanding the behavior of measured wave spectrum at a given location. These spectra also influence the wave parameters such as significant wave height (
) and peak wave period (
). Standard theoretical spectra (empirically developed) like JONSWAP and PM are typically used to fit observed spectra that at times mismatch and produces inconsistent wave parameter values. This paper attempts to investigate the spectral characteristics of waves using Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) during the severe hurricane Fiona, which hit a location in the Northeast Bahamas on September 20–23, 2022. The results include fitting the measured (single and multipeaked) spectra and acquiring its wave attributes during the pre-hurricane (September 16–19), hurricane, post-hurricane (September 24–27) periods and for September 20–23, 2021–2023. It was observed that 
of the spectra were double-peaked (swell-dominated), majorly attaining their peak frequency at 0.0925 Hz. It was found that the maximum reached to 9-10 m, which is four times (approximately) higher than the usual value recorded over the course of the hurricane period. The computed during September 20–23, 2021–2023, were then provided as an input to predict using supervised machine learning techniques like tree and random forest made with Orange software. Statistical error measures like RMSE, MAE, and MSE were computed and found to be minimal, achieving the better future trend of the and serves as a validation for the PCHIP by ensuring good accuracy.
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