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Robert M. Beauchamp, V. Chandrasekar, Haonan Chen, and Manuel Vega

value. From the observation in Fig. 10 , two radial reflectivity profiles are presented in Fig. 11 . The observations have been averaged for longer duration (576 ms vs 64 ms in Fig. 10 ) to reduce the effects of measurement fluctuations. The presented reflectivity observations are echoes from ice crystals in the observed convective cell in Fig. 10 . Figures 11a and 11c consider a radial covering 15.1°–16.2° for reflectivity and DFR, respectively. Figures 11b and 11d consider a radial

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Luciana K. Cunha, James A. Smith, Witold F. Krajewski, Mary Lynn Baeck, and Bong-Chul Seo

hydrometeor sampled by the radar ( Ryzhkov et al. 2005a ; Park et al. 2009 ) using fuzzy logic, and the top and bottom melting-layer boundaries ( Giangrande et al. 2008 ). The boundaries of the melting layer are defined based on lower- and upper-limit thresholds for reflectivity and correlation coefficient typically found in a melting layer. In the current system the following classes are defined: 1) biological, 2) ground clutter and anomalous propagation, 3) ice crystal, 4) dry snow, 5) wet snow, 6

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Haonan Chen, V. Chandrasekar, and Renzo Bechini

populated with adjacent bins are assigned to the same hydrometeor type. In total, 11 hydrometeor types are classified: large drops (LD), drizzle (DR), rain (RA), heavy rain (HR), rain–hail mixture (RH), hail (HA), graupel (GR), wet ice (WI), dry ice (DI), crystals (CR), and dendrites (DN). Ground clutter and nonmeteorological echoes are also classified as clutter (CL). Compared to conventional fuzzy-logic method, this region-based approach is appealing in terms of operational application and easy

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