Very large waves populate world oceans and challenge seafarers and offshore structures, but their long-term and global assessment is uneasy because of the scarcity of observations and their narrow time-coverage. Modern model reanalysis datasets with high spatio-temporal extent and resolution represent a valuable tool for this scope. In this paper, we use for the first time reanalysis datasets to provide a long-term and global statistical assessment of the maximum wave parameters, namely crest, crest-to-trough and envelope heights. In particular, we rely on the ERA-Interim directional wave spectra that are used to estimate the parameters of the probability distributions of wave maxima. To represent the customary single-point observations we use time extreme statistical models, while to account for the three-dimensional geometry and short-crestedness of stormy ocean waves, the statistical models are extended to space-time. In order to evaluate the accuracy of the reanalysis-based wave maxima estimates we verify them against buoy and stereo-video wave observations gathered in the North Pacific Ocean. We then provide the global assessment of maximum crest, crest-to-trough and envelope heights during typical and extreme conditions, showing the regions attaining the largest values, which we show are located in the mid-latitude storm belts, in particular in the North Atlantic Ocean. With respect to previous wave climate studies that focused on the significant wave height only, in this study we quantify the maximum wave height extent, also highlighting the role of mean wave steepness and kurtosis (measures of nonlinearity) and spectral bandwidth (measure of irregularity). Beside this, we show that the contribution of the short-crestedness is significant and that taking it into account may be relevant for the safety of navigation, ship routing and marine structural design.

Maximum wave heights from global model reanalysis

Barbariol F;Cavaleri L;Sclavo M;Benetazzo A
2019

Abstract

Very large waves populate world oceans and challenge seafarers and offshore structures, but their long-term and global assessment is uneasy because of the scarcity of observations and their narrow time-coverage. Modern model reanalysis datasets with high spatio-temporal extent and resolution represent a valuable tool for this scope. In this paper, we use for the first time reanalysis datasets to provide a long-term and global statistical assessment of the maximum wave parameters, namely crest, crest-to-trough and envelope heights. In particular, we rely on the ERA-Interim directional wave spectra that are used to estimate the parameters of the probability distributions of wave maxima. To represent the customary single-point observations we use time extreme statistical models, while to account for the three-dimensional geometry and short-crestedness of stormy ocean waves, the statistical models are extended to space-time. In order to evaluate the accuracy of the reanalysis-based wave maxima estimates we verify them against buoy and stereo-video wave observations gathered in the North Pacific Ocean. We then provide the global assessment of maximum crest, crest-to-trough and envelope heights during typical and extreme conditions, showing the regions attaining the largest values, which we show are located in the mid-latitude storm belts, in particular in the North Atlantic Ocean. With respect to previous wave climate studies that focused on the significant wave height only, in this study we quantify the maximum wave height extent, also highlighting the role of mean wave steepness and kurtosis (measures of nonlinearity) and spectral bandwidth (measure of irregularity). Beside this, we show that the contribution of the short-crestedness is significant and that taking it into account may be relevant for the safety of navigation, ship routing and marine structural design.
2019
Istituto di Scienze Marine - ISMAR
Ocean waves; Global wave climate; Wave maxima; ERA-Interim; Wave observations
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/368064
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