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Current study advocates novel Gaidai hazards assessment methodology that may be utilized for excessive wave-heights spatiotemporal risk analysis, thus advancing climate change studies. Gaidai hazards assessment methodology being particularly suitable for multivariate dynamic environmental ocean systems, that have been MC (i.e., Monte Carlo) numerically simulated, either physically measured across a representative time period, resulting in synchronous quasi-ergodic timeseries. Offshore waves affect reliable production and operational safety of offshore and marine structures. Current study presents two reliability methods: first, state-of-the-art spatiotemporal reliability methodology, designed for multi-dimensional dynamic systems, to be presented in the current study; second, novel deconvolution extrapolation technique to follow. Primary target being accurate environmental ocean system's hazard hazards assessment. Classic risk assessment methods, dealing with measured timeseries may not always possess advantages of dealing efficiently with the environmental ocean system's high dimensionality, along with nonlinear cross-correlation patterns between various environmental ocean system's components. In-situ significant wave-height measured dataset, measured in different offshore areas, to be analyzed in the current study by means of application of advocated reliability methodology. Offshore waves representing complex highly-nonlinear, cross-correlated environmental dynamic system. Global climate change being also an important factor, affecting offshore wave-heights. Primary purpose of the current study had been to benchmark novel hazards assessment methodology, while utilizing efficiently underlying raw measured dataset. Methods put forth in the current study may be utilized for hazard hazards assessments for a large variety of nonlinear high dimensional environmental ocean systems.
Gaidai et al. (Mon,) studied this question.