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Author Spotlight: In Vitro Co-Culture System of Pine Shoots and Pinewood Nematode for Studying Host Volatile Response
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Wind noise under a pine tree canopy.

Richard Raspet1, Jeremy Webster2

  • 1National Center for Physical Acoustics, Department of Physics and Astronomy, The University of Mississippi, Box 1848, University, Mississippi 38677.

The Journal of the Acoustical Society of America
|February 21, 2015
PubMed
Summary
This summary is machine-generated.

Infrasonic wind noise is lower in forests. This study predicts wind noise spectra in pine forests using meteorological data, showing good agreement with measurements.

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Area of Science:

  • Acoustics
  • Environmental Science
  • Meteorology

Background:

  • Infrasonic wind noise levels are significantly lower in vegetated areas compared to open spaces.
  • Understanding wind noise within forests is crucial for various applications, including environmental monitoring and acoustic studies.

Purpose of the Study:

  • To measure and analyze infrasonic wind noise levels, turbulence spectra, and wind velocity profiles within a pine forest.
  • To develop a predictive model for wind noise spectra in forests based on meteorological parameters.
  • To compare predicted wind noise spectra with measured data to validate the model.

Main Methods:

  • Field measurements of wind noise, turbulence, and wind velocity were conducted in a pine forest.
  • A predictive model for wind noise spectra was developed, integrating turbulence-shear and turbulence-turbulence interactions.
  • The model was validated by comparing its predictions against four sets of measured data.

Main Results:

  • The wind noise spectrum in the forest comprises low-frequency noise from turbulence-shear interaction above the trees and high-frequency noise from turbulence-turbulence interaction within the canopy.
  • Convection velocity of low-frequency noise matched the wind speed above the trees.
  • High-frequency noise was found to be near-stationary, generated by slow-moving turbulence near the ground.
  • The predictive model demonstrated good agreement with the measured wind noise spectra.

Conclusions:

  • The developed model accurately predicts wind noise spectra in pine forests.
  • The findings contribute to a better understanding of acoustic propagation within forested environments.
  • The prediction method can be utilized for meteorological estimates to forecast wind noise levels under similar forest conditions.