Nondimensional analysis of wind noise and atmospheric surface-layer properties

• Published in: The Journal of the Acoustical Society of America 2018-09, Vol.144 (3), p.1679-1679
• Main Authors: Hart, Carl R., Lyons, Gregory W., Hocut, Christopher M.
• Format: Article
• Language: English
• ISSN: 0001-4966; 1520-8524
• DOI: 10.1121/1.5067471

Wind noise is a prominent limitation to the signal to noise ratio of acoustic sensors. Realistic expectations of signal detectability can be generated by predicting the noise floor prior to a sensor deployment; however, a relationship must be established between the wind noise measured by a sensor and atmospheric surface-layer properties. Under conditions of horizontal homogeneity and quasi-steadiness, Monin-Obukhov similarity theory relates friction velocity, temperature scale, and roughness length to the near-surface profiles of mean wind speed and turbulent intensity, which in turn are known to govern wind noise. It is expected that the ratio of one-third octave band root-mean-square sound pressure to the turbulent flux of momentum, Strouhal number, and dimensionless elevation have a nondimensional relationship that collapses wind noise data as a function of Monin-Obukhov parameters. In order to establish such a relationship, we analyze a dataset of wind noise recorded in Spring 2018 within the Army Research Laboratory’s Meteorological Sensing Array on the Jornada Experimental Range, New Mexico. This dataset consists of continuous recordings of ambient noise at several sites on audio microphones up to 20 m above ground level, co-located with a suite of high-fidelity meteorological instruments, including sonic anemometers.