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Bulk Hydrometeor Classification and Quantification Using Polarimetric Radar Data: Synthesis of Relations

Bulk Hydrometeor Classification and Quantification Using Polarimetric Radar Data: Synthesis of... A new synthesis of information forming the foundation for rule-based systems to deduce dominant bulk hydrometeor types and amounts using polarimetric radar data is presented. The information is valid for a 10-cm wavelength and consists of relations that are based on an extensive list of previous and recent observational and modeling studies of polarimetric signatures of hydrometeors. The relations are expressed as boundaries and thresholds in a space of polarimetric radar variables. Thus, the foundation is laid out for identification of hydrometeor types (species), estimation of characteristics of hydrometeor species (size, concentrations, etc.), and quantification of bulk hydrometeor contents (amounts). A fuzzy classification algorithm that builds upon this foundation will be discussed in a forthcoming paper. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Meteorology American Meteorological Society

Bulk Hydrometeor Classification and Quantification Using Polarimetric Radar Data: Synthesis of Relations

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References (178)

Publisher
American Meteorological Society
Copyright
Copyright © 1999 American Meteorological Society
ISSN
1520-0450
DOI
10.1175/1520-0450(2000)039<1341:BHCAQU>2.0.CO;2
Publisher site
See Article on Publisher Site

Abstract

A new synthesis of information forming the foundation for rule-based systems to deduce dominant bulk hydrometeor types and amounts using polarimetric radar data is presented. The information is valid for a 10-cm wavelength and consists of relations that are based on an extensive list of previous and recent observational and modeling studies of polarimetric signatures of hydrometeors. The relations are expressed as boundaries and thresholds in a space of polarimetric radar variables. Thus, the foundation is laid out for identification of hydrometeor types (species), estimation of characteristics of hydrometeor species (size, concentrations, etc.), and quantification of bulk hydrometeor contents (amounts). A fuzzy classification algorithm that builds upon this foundation will be discussed in a forthcoming paper.

Journal

Journal of Applied MeteorologyAmerican Meteorological Society

Published: Feb 18, 1999

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