Prediction of streamwise and vertical wind speed fluctuation during dust storms in near-neutral atmospheric surface layer

Abstract

Due to the limitations of the existing atmospheric surface layer (ASL) turbulence prediction models during dust storms, therefore, this paper uses multi-scale signal reconstruction and HSM as the basic framework to propose a prediction model of streamwise and vertical wind speed fluctuation during dust storms in near-neutral ASL. The input of this model is only friction wind speed. In the reconstruction of large-scale signals, the random phase control and the introduction of structural inclination angle reflect the coherence of large-scale turbulent structures. Through the modification of the HSM method, turbulence events in different quadrants are introduced into the prediction model. The introduction of the influence of dust particles on turbulent fluctuation is achieved by modifying the characterization parameters of the Kaimal spectrum. The model proposed in this paper can not only reflect the coherence and inclination of large-scale turbulent structures, but also reflect the contribution of different turbulent events. In addition, the power spectrum predicted by the model, the event contribution ratio of different quadrants, and the turbulence intensity are in good agreement with the field observation results both qualitatively and quantitatively. These results show that the model can be used to predict the streamwise and vertical wind speed fluctuation.