Field measurement analysis of wind parameters and nonstationary characteristics in mountainous terrain: Focusing on cooling windstorms

Jiang, Fanying; Zhang, Mingjin; Li, Yongle; Yan, Tingyuan; Zhang, Jinxiang

doi:10.1016/j.jweia.2022.105175

Cited by 18 publications

(2 citation statements)

References 54 publications

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“…As awareness has increased of the potential disasters of downbursts, researchers have carried out extensive investigations on thunderstorm wind characteristics through field measurements (Chaudhuri et al, 2020;Jiang et al, 2022), wind tunnel tests (Asano et al, 2019;Fang et al, 2023) and numerical simulations (Selvam and Holmes, 1992;Iida et al, 2015). Specifically, the collaborative team of Hangan and Romanic have conducted extensive research on the climatic environment of downbursts and their interaction with boundary layer winds by comparing downburst models with full-size downbursts (Romanic et al, 2020(Romanic et al, , 2022Canepa et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Observation of downburst wind characteristics using the Doppler profiler and near-ground measurements

He,

Cai,

Wang

et al. 2024

Nat Hazards

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A downburst is a strong downdraft that causes radiating, catastrophic winds at or near the ground. Relevant research conducted in the past decades shows that downbursts not only bring damage to the built environment but also have surprisingly destructive effects on aircraft and other flying objects. However, due to the complexity of atmospheric phenomena and limited measurement datasets, many uncertainties remain to be clarified in the understanding and modelling of the downburst wind field.To further explore the evolution characteristics of thunderstorms, this study uses data recorded during thunderstorms by a Doppler profiler of the Hong Kong Observatory and a near-ground anemometer installed at the Hong Kong International Airport to conduct a detailed feature analysis of the vertical profile and turbulence characteristics of downbursts within the atmospheric boundary layer. Based on long-term field measurements during thunderstorm events, the occurrence of a thunderstorm should be determined by a combination of simultaneous variations in multiple meteorological factors, including wind speed and direction, vertical wind speed, and signal-to-noise ratio (SNR). During thunderstorms, extreme wind speeds occurred in the lower atmosphere and the height of the local peaks seems to be stable in the thunderstorm wind profiles. In addition, both methods, which consider a constant mean component (stationary) and a slowly varying mean component (non-stationary), are used to decompose the measured wind speed and are then compared to investigate the turbulence characteristics of downbursts. It is found that although the gust factor and turbulence intensity show some deviation due to the influence of atmospheric stratification instability, this effect does not appear to be reflected in the turbulence integral scale.

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Section: Introductionmentioning

confidence: 99%

Observation of downburst wind characteristics using the Doppler profiler and near-ground measurements

He,

Cai,

Wang

et al. 2024

Nat Hazards

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“…Various methods have been developed to derive the slowly-varying trends of wind velocities, among which the empirical mode decomposition (EMD) and the discrete wavelet transform (DWT) are two popular and efficient approaches. Jiang et al (2022) used the DWT to extract the time-varying mean wind velocity and selected the best wavelet decomposition level according to the turbulence energy. Cai et al (2021) employed the EMD to extract the time-varying mean wind velocity and used quantitative methods to determine the optimal time-varying mean wind velocity.…”

mentioning

confidence: 99%

Identification of modal parameters of long-span bridges under various wind velocities

Yan

et al. 2022

ABEN

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The modal parameters identification of bridges under non-stationary environmental excitation has caught the attention of researchers. This paper studies the non-stationarity of wind velocity, and extracts the time-varying mean wind velocity based on a discrete wavelet transform and recursive quantitative analysis. The calculated turbulence intensity and turbulence integral scale under the non-stationary model are smaller than those under the stationary model, especially the turbulence integral scale. The empirical wavelet transform is used to identify the modal parameters of long-span bridges, and the power spectral density spectrum is proposed as a replacement for the Fourier spectrum as the basis of the frequency band selection. The bridge modal parameters are then compared using the covariance-driven stochastic subspace system identification method (SSI-COV) and the Hilbert transform method based on an improved empirical wavelet transform (EWT-HT). Both methods can accurately identify the modal frequency, and the absolute difference between these two methods is equal to 0.003 Hz. The wind velocity results in a change of less than 1% in the modal frequency. The absolute difference between the modal damping ratios identified using SSI-COV and EWT-HT is significant and can reach 0.587%. The modal damping ratios are positively correlated with the mean wind velocities, which aligns with the quasi-steady assumption. In addition, the applicability of SSI-COV and EWT-HT is also evaluated using the standard deviation, coefficient of variation, and range dispersion indicators. The results show that the EWT-HT is more applicable to the identification of the modal parameters of long-span bridges under non-stationary wind velocities.

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Determination of extreme wind speed under different wind directions and attack angles with mixed wind climates in mountain terrain

Jiang,

Zhang,

Zhang

et al. 2023

Stoch Environ Res Risk Assess

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Field measurement analysis of wind parameters and nonstationary characteristics in mountainous terrain: Focusing on cooling windstorms

Cited by 18 publications

References 54 publications

Observation of downburst wind characteristics using the Doppler profiler and near-ground measurements

Observation of downburst wind characteristics using the Doppler profiler and near-ground measurements

Identification of modal parameters of long-span bridges under various wind velocities

Determination of extreme wind speed under different wind directions and attack angles with mixed wind climates in mountain terrain

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