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<p>Turbulent pressure fluctuations, commonly known as “wind noise”, induced by wind flow in the planetary boundary layer (PBL), close to the ground surface, are the dominant noise source in infrasound measurements, masking signals of interest and limiting detection capability. Therefore, selecting deployment sites with naturally low wind noise levels is critical for maximizing signal-to-noise ratios, independently of applying wind-noise reduction systems in <i>situ</i> or even noise filters in the data processing stage. Noise levels are expected to correlate with local topography, which influences wind flow patterns and turbulence. However, their relationship remains poorly quantified, and site selection still relies on qualitative assessments of topographic features and demands logistically intensive noise tests for long periods of time. To address this gap, the first stage in developing a quantitative framework linking wind noise levels to measurable topographic parameters for wind noise mapping and improved site selection is presented. Wind noise data were collected at multiple test sites in Mississippi and Alabama and analyzed in two frequency bands (0.1–1&#xa0;Hz and 1–10&#xa0;Hz). Root Mean Square (RMS) pressure levels were computed to average background pressure fluctuations. Kernel Density Estimation (KDE) was applied to estimate Probability Density Functions (PDFs) of RMS Pressures, and Cumulative Distribution Functions (CDFs) were generated to quantify the probability of noise levels falling below key detection thresholds. Preliminary results demonstrate clear differences in noise distributions between sites separated by distances as short as 20&#xa0;m, even within forested areas, indicating the need for high resolution noise level mapping.</p>

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Investigating Wind Noise Levels and Topography for Infrasound Array Deployment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月3日

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  • Céu Jesus,
  • Roger Waxler,
  • Carrick Talmadge,
  • Lance D. Yarbrough,
  • Claus Hetzer,
  • Hank Buchanan,
  • Naveen Thirunilath

摘要

Turbulent pressure fluctuations, commonly known as “wind noise”, induced by wind flow in the planetary boundary layer (PBL), close to the ground surface, are the dominant noise source in infrasound measurements, masking signals of interest and limiting detection capability. Therefore, selecting deployment sites with naturally low wind noise levels is critical for maximizing signal-to-noise ratios, independently of applying wind-noise reduction systems in situ or even noise filters in the data processing stage. Noise levels are expected to correlate with local topography, which influences wind flow patterns and turbulence. However, their relationship remains poorly quantified, and site selection still relies on qualitative assessments of topographic features and demands logistically intensive noise tests for long periods of time. To address this gap, the first stage in developing a quantitative framework linking wind noise levels to measurable topographic parameters for wind noise mapping and improved site selection is presented. Wind noise data were collected at multiple test sites in Mississippi and Alabama and analyzed in two frequency bands (0.1–1 Hz and 1–10 Hz). Root Mean Square (RMS) pressure levels were computed to average background pressure fluctuations. Kernel Density Estimation (KDE) was applied to estimate Probability Density Functions (PDFs) of RMS Pressures, and Cumulative Distribution Functions (CDFs) were generated to quantify the probability of noise levels falling below key detection thresholds. Preliminary results demonstrate clear differences in noise distributions between sites separated by distances as short as 20 m, even within forested areas, indicating the need for high resolution noise level mapping.