Special Issue on Non-Synoptic Winds

Non-synoptic winds, which depart from large-scale synoptic winds, have been observed to play a significant role in causing damage, particularly in specific geographic regions. These non-synoptic winds, such as tornadoes, waterspouts, thunderstorm downbursts, microbursts, and other local wind phenomena, display distinct spatial and temporal characteristics in the wind field, differing from the well-established knowledge of large-scale synoptic winds. The main differences rely on the three-dimensionality, stationarity, uniformity, specific wind profile, and associated statistics. These variations have been observed to result in different aerodynamic loads on structures. As awareness of the impact of non-synoptic winds grows, there has been a growing recognition of the importance of understanding and addressing non-synoptic winds in recent years. This Special Issue is devoted to advancing the understanding of the characteristics of non-synoptic winds and their impacts on various aspects, including structures, communities, vegetation, and ecosystems. Within this special edition, a diverse array of topics related to non-synoptic winds are covered. Shen et al. (2024) reconstructed the wind speed field in mountainous regions by employing Artificial Intelligence technology, i.e., Full Convolutional Neural Network (FCNN). They established a mapping relation between terrain, wind angle, height, and the corresponding velocity fields of three velocity components within a specific terrain range. Zhao et al. (2024) derived the vertical velocity component based on the horizontal velocities extracted from the radar-measured data using mass continuity principles. Subsequently, they investigated the tornadic wind fields by integrating the derived vertical velocity component into the inlet condition of CFD simulations. Xu et al. (2024) analyzed the similarity in the interaction of downburst with wave between a prototype and a scaled model. They proposed a method to mitigate scale effects in experimental simulations of the downburstgenerated wave and validated this approach through numerical simulations. Liu and Hong (2024) analyzed recorded tri-directional thunderstorm wind components by separating them into lower frequency time-varying mean wind speed and high-frequency fluctuating wind components in three orthogonal directions. They evaluated the coherence between each pair of fluctuating winds and developed empirical spectral models and lagged coherence models for the tri-directional fluctuating wind components. Zou et al. (2024) investigated tornadic flow structures and aerodynamic pressures around a high-speed train by employing the improved delated detached eddy simulation. They validated their numerical simulations by comparing them with field observations and wind tunnel data, focusing particularly on aerodynamic loads on the high-speed train at various heights and radial locations. Tao et al. (2024) conducted a probabilistic analysis of gust factors and turbulence intensities of tropical cyclones based on field observations. They established empirical probabilistic models based on this analysis and validated the proposed models by comparing them with measured data. Yao and El Damatty (2024) proposed a simplified procedure to estimate the critical tornado-induced longitudinal force transmitted from the conductor to a tower for transmission line structure. They conducted a parametric study at the critical tornado position to evaluate the effects of different conductor parameters on the longitudinal response.