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contributor authorPark, Hyang Suk
contributor authorRyzhkov, A. V.
contributor authorZrnić, D. S.
contributor authorKim, Kyung-Eak
date accessioned2017-06-09T16:27:11Z
date available2017-06-09T16:27:11Z
date copyright2009/06/01
date issued2009
identifier issn0882-8156
identifier otherams-68112.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4209635
description abstractThis paper contains a description of the most recent version of the hydrometeor classification algorithm for polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). This version contains several modifications and refinements of the previous echo classification algorithm based on the principles of fuzzy logic. These modifications include the estimation of confidence factors that characterize the possible impacts of all error sources on radar measurements, the assignment of the matrix of weights that characterizes the classification power of each variable with respect to every class of radar echo, and the implementation of a class designation system based on the distance from the radar and the parameters of the melting layer that are determined as functions of azimuth with polarimetric radar measurements. These additions provide considerable flexibility and improve the discrimination between liquid and frozen hydrometeors. The new classification scheme utilizes all available polarimetric variables and discerns 10 different classes of radar echoes. Furthermore, a methodology for the new fuzzy logic classification scheme is discussed and the results are illustrated using polarimetric radar data collected with the Norman, Oklahoma (KOUN), WSR-88D prototype radar during a mesoscale convective system event on 13 May 2005.
publisherAmerican Meteorological Society
titleThe Hydrometeor Classification Algorithm for the Polarimetric WSR-88D: Description and Application to an MCS
typeJournal Paper
journal volume24
journal issue3
journal titleWeather and Forecasting
identifier doi10.1175/2008WAF2222205.1
journal fristpage730
journal lastpage748
treeWeather and Forecasting:;2009:;volume( 024 ):;issue: 003
contenttypeFulltext


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