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

Jerry M. Straka School of Meteorology and Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Dusan S. Zrnić National Severe Storms Laboratory, Norman, Oklahoma

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Alexander V. Ryzhkov Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and National Severe Storms Laboratory, Norman, Oklahoma

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Print Publication:
01 Aug 2000
DOI:
https://doi.org/10.1175/1520-0450(2000)039<1341:BHCAQU>2.0.CO;2
Page(s):
1341–1372
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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.

Corresponding author address: Dr. Dusan S. Zrnić, National Severe Storms Laboratory, 1313 Halley Circle, Norman, OK 73069.

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.

Corresponding author address: Dr. Dusan S. Zrnić, National Severe Storms Laboratory, 1313 Halley Circle, Norman, OK 73069.

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