Characterizing flow conditions of urban environments from wind-induced noise measurements: A semi-empirical wind noise model of the University of the District of Columbia campus

Abstract

In this work, the flow conditions within the University of the District of Columbia (UDC) urban campus are predicted from wind-induced noise. Wind-induced noise obtained from a collection of spatial distributed microphones are used to estimate the mean velocity airflow and wind noise distribution across the UDC campus. Wind speed and direction are estimated by fitting the second-order statistics of semi-empirical models of wind noise distribution from microphone measurements to analytical models in the least squares sense. The accuracy of the proposed is investigated for average microphone separation and time resolution. Comparisons of the wind speed and direction results to ultrasonic anemometer measurements are discussed.