Comparing Weibull distribution method and Gram–Charlier series method within the context of estimating low-occurrence strong wind speed of idealized building cases

Abstract

Understanding low-occurrence strong wind speed (LOSWS) distributions at the pedestrian level is important. However, the robustness of the statistical methods for estimating LOSWSs under different conditions remains uncertain. In this study, the performances of the Weibull distribution method and Gram–Charlier series (GCS) method were compared. Their accuracies for isolated building and building array cases were analyzed. It was found that the constant peak factor (PF) of the Gaussian distribution showed acceptable accuracy only when the exceedance probability q = 10%. For q = 0.1%, the PF of the three-parameter Weibull distribution (3W) was more accurate than that of GCS-3rd. For fitting probability density functions, GCS-6th exhibited better flexibility than the two-parameter Weibull distribution (2W) and 3W. However, large leading terms leaded to oscillations at several points in GCS-6th. Regarding the estimation accuracy of LOSWSs, the 2W and 3W methods are superior to the GCS methods when the available orders of statistics are equal. Although the GCS methods showed higher accuracy than the 3W method in some regions, the oscillations at specific points in the GCS methods may lead to lower accuracy on average. The present findings can serve as an illuminating reference for further applications of these statistical methods.