A Model for the Estimation of Rain Distributions.

Abstract

The adverse attenuation effects caused by rain or snow on electro-optical weapons and communication systems are important considerations in any military operation. Attenuation is a function of the E-O wavelength and the number, size, and type of precipitation or cloud particles. The amount (liquid-water-content) and type of precipitation in any given area may be predicted by meteorological modeling techniques or inferred through remote sensing, yet neither method currently has the ability to define the distribution parameters (numbers and sizes) of the precipitating particles. This report describes the development of a model that may be used to estimate the parameters of precipitable rain distributions from inputs of liquid-water-content and/or measurements of radar reflectivity coupled with standardized cloud physics relationships. The model is developed from an equation set based on an exponential distribution function. Aircraft-acquired data are used to verify the conformity of rain distributions to exponential shapes. Empirical relationships provided by these data verified the existence of a nondimensional predictable entity (Lambda D sub M = distribution slope times maximum drop size), which provides improved estimates of rain distributions from predicted or measured values of liquid-water-content and radar reflectivity. Tables listing the variations in the size distributions during three rain situations are given in Appendix A. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1983
Accession Number
ADA130080

Entities

People

  • R. O. Berthel
  • V. G. Plank

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Cloud Physics
  • Clouds
  • Communication Systems
  • Data Analysis
  • Diameters
  • Distribution Functions
  • Drops
  • Equations
  • Hydrometeors
  • Military Operations
  • Particle Size
  • Particles
  • Precipitation
  • Rain
  • Raindrops

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Business Analytics
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference