The estimation of extreme quantiles of wind velocity using L-moments in the peaks-over-threshold approach

• Published in: Structural safety Vol. 23; no. 2; pp. 179 - 192
• Main Authors: Pandey, M.D, Van Gelder, P.H.A.J.M, Vrijling, J.K
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 2001; New York, NY Elsevier Science
• Subjects: Applied sciences; Buildings. Public works; Climatology and bioclimatics for buildings; Exact sciences and technology; Extreme values; L-moments; loading; Monte Carlo simulations; Order statistics; Pareto distribution; Peaks-over-threshold method; Quantiles; Return period; Stresses. Safety; Structural analysis. Stresses; Tail index; Wind speed; Peaks-over-threshold method; Quantiles; Pareto distribution; Monte Carlo simulations; L-moments; Wind speed; Return period; Tail index; Order statistics; Extreme values; Structural design; Monte Carlo method; Parameter estimation; Wind velocity; Numerical simulation; Quantile; Method study
• ISSN: 0167-4730; 1879-3355
• DOI: 10.1016/S0167-4730(01)00012-1

The paper evaluates the effectiveness of the method of L-moments for estimating parameters of the Pareto distribution model of peaks over a sufficiently high threshold, and compares its performance against a widely used method of de Haan (de Haan L. Extreme value statistics. In: Galambos J, Lechner J, Simin E, editor. Extreme value theory and applications, vol. 1. 1994. p. 93–122). Monte Carlo simulations and actual wind speed data collected at various stations in the United States have been utilized in this study. In the de Haan method, the first two moments of peaks of log-transformed data are used for the parameter estimation, whereas the L-moment method utilizes linear combinations of expectations of order statistics of peaks in the original data. Despite the procedural differences, the paper shows that the de Haan and two L-moments based estimates of the tail shape parameter are in fairly close agreement in simulated data as well as in the US wind speed data. Furthermore, higher order estimates of the shape parameter are obtained using the L-skewness of peaks data. Such estimates appear to provide a more stable upper bound, which can be useful in identifying meaningful values of design quantiles.