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Hydrometeor classification from dual-polarized weather radar: Extending fuzzy logic from S-band to C-band data

Articolo
Data di Pubblicazione:
2006
Abstract:
A model-based fuzzy classification method for C-band polarimetric radar data, named Fuzzy Radar Algorithm for Hydrometeor Classification at C-band (FRAHCC), is presented. Membership functions are designed for best fitting simulation data at C-band, and they are derived for ten different hydrometeor classes by means of a scattering model, based on T-Matrix numerical method. The fuzzy logic classification technique uses a reduced set of polarimetric observables, i.e. copolar reflectivity and differential reflectivity, and it is finally applied to data coming from radar sites located in Gattatico and S. Pietro Capofiume in North Italy. The final purpose is to show qualitative accuracy improvements with respect to the use of a set of ten bidimensional MBFs, previously adopted and well suited to S-band data but not to C-band data.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
fuzzy mathematics; precipitation (climatology); radar imagery; weather forecasting; Eurasia; Europe; Italy; Southern Europe
Elenco autori:
Montopoli, Mario
Autori di Ateneo:
MONTOPOLI MARIO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/317214
Pubblicato in:
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Journal
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-33646338211&partnerID=40&md5=ddee8e57af285eca2655c4b33ded7eb7
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