Probabilistic structure analysis of fluctuating wind speed based on field measurement of super typhoon Doksuri

Abstract

Based on field measurement of super typhoon Doksuri from an observation array positioned within typhoon landing zones in China, the probabilistic structure of fluctuating wind speed under extreme wind conditions is investigated. To this end, the newly proposed stochastic Fourier amplitude spectrum model is employed. For validation purposes, a comparative study against classical power spectral density (PSD) models is carried out. Moreover, the relevance between elemental random variables of the model and wind conditions is addressed using a statistical ensemble-based method. Utilizing the wind speed data recorded during the typhoon landfall process and synoptic wind seasons, it is revealed that the stochastic Fourier amplitude spectrum can effectively capture the probabilistic structure of fluctuating wind speed in typhoon environments; however, classical PSD models fail to depict the transition of energy spectrum accurately and thus tend to overestimate the energy in the low frequency range (≤0.3 Hz). This study demonstrates the applicability of the stochastic Fourier amplitude spectrum model under extreme wind conditions, facilitating a comprehensive understanding of the fluctuating wind speed with probabilistic information beyond low-order moments; in addition, the model exhibits a significant potential to the stochastic response analysis and reliability assessment for wind-sensitive structures.