Predicting the Underwater Sound of Moderate and Heavy Rainfall from Laboratory Measurements of Radiation from Single Large Raindrops

Abstract

Large raindrops (greater than2.2 mm diameter) that strike and water surface at terminal velocity are capable of creating bubbles that radiate significant underwater acoustical energy. Previous studies have revealed a positive correlation between underwater sound spectral levels during rainfall and the number of large raindrops present. Therefore, laboratory measurements have been made of the underwater sound generated by large rain-drops. Using the laboratory measurements, smoothed energy density spectra for various sizes of large raindrops are determined. These spectra are then used to computer a predicted underwater sound spectrum due to rainfall for rainfall rates of 15 mm/hr and 100 mm/hr, assuming an exponential (Marshall-Palmer) raindrop size distribution. The resulting spectra are compared to underwater sound spectra measured at sea during periods with similar rainfall rates. The predicted rainfall spectra are comparable to the measured rainfall spectra. Possible reasons for differences are discussed. An inversion technique for obtaining the raindrop size distribution from the rainfall acoustical spectrum is presented. An alternate approach for obtaining the required inversion matrix is suggested for future work.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1992
Accession Number
ADA252748

Entities

People

  • Leo H. Ostwald Jr.

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Measurement
  • Acoustics
  • Bandpass Filters
  • Data Analysis
  • Drops
  • Energy
  • Frequency
  • Geometry
  • Inverse Problems
  • Measurement
  • Military Research
  • Probability
  • Radiation Patterns
  • Salt Water
  • Scattering
  • Surface Temperature
  • Surface Tension

Fields of Study

  • Physics

Readers

  • Acoustical Oceanography.
  • Atmospheric Remote Sensing.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.