Adaptive Wind Gust and Associated Gust-factor Model for the Gust-producing Weather over the Northern South China Sea

Abstract

Wind gusts are common environmental hazards that can damage buildings, bridges, aircraft, and cruise ships and interrupt electric power distribution, air traffic, waterway transport and port operations. Accurately predicting peak wind gusts in numerical models is essential for saving lives and preventing economic losses. This study investigates the climatology of peak wind gusts and their associated gust factors (GFs) using observations in the coastal and open ocean of the northern South China Sea (NSCS), where severe gust-producing weather occurs throughout the year. The stratified climatology demonstrates that the peak wind gust and GF vary with seasons and particularly with weather types. Based on the inversely proportional relationship between the GF and mean wind speed (MWS), a variety of GF models are constructed through least squares regression analysis. Peak gust speed (PGS) forecasts are obtained through the GF models by multiplying the GFs by observed wind speeds rather than forecasted wind speeds. The errors are thus entirely due to the representation of the GF models. The GF models are improved with weather-adaptive GFs, as evaluated by the stratified MWS. Nevertheless, these weather-adaptive GF models show negative bias for predicting stronger PGSs due to insufficient data representation of the extreme wind gusts. The evaluation of the above models provides insight into maximizing the performance of GF models. This study further proposes a stratified process for forecasting peak wind gusts for routine operations.