Paper Info
Title
Bayesian classification of hydrometeors from polarimetric radars at S- and X- bands: algorithm design and experimental comparisons
Abstract
Dual-polarized weather radars are capable to detect and identify different classes of hydrometeors, within stratiform and convective storms exploiting polarimetric diversity. A model- supervised Bayesian method for hydrometeor classification (BRAHC), tuned for S- and X- band, is described in this study. The critical issue of X-band radar data processing is the path attenuation correction, usually negligible at S-band. During the IHOP experiment (Oklahoma, 2002) two dual-polarized radars, at S- and X- bands, were deployed and jointly operated with closely matched scanning strategies, giving the opportunity to perform experimental comparisons between coincident measurements at different frequencies. Results of hydrometeor classification and water content estimates at S- and X- bands are discussed and the impact of path attenuation correction is quantitatively analyzed.
Year
DOI
Venue
2007
10.1109/IGARSS.2007.4423765
Barcelona
Keywords
Field
DocType
Bayes methods,atmospheric precipitation,meteorological radar,radar polarimetry,storms,AD 2002,Bayesian classification,IHOP experiment,Oklahoma,algorithm design,convective storms,hydrometeors,path attenuation correction,polarimetric radars,stratiform,weather radars,Bayesian classification,attenuation correction,convective event,polarimetric radar,water content estimate
Meteorology,Convective storm detection,Polarimetry,Algorithm design,Naive Bayes classifier,Computer science,Remote sensing,Radar data processing,Correction for attenuation,Coincident,Bayesian probability
Conference
ISBN
Citations 
PageRank 
978-1-4244-1212-9
0
0.34
References 
Authors
3
4
Name
Order
Citations
PageRank
Marzano, F.S.17314.77
Scaranari, D.200.34
Mario Montopoli35917.34
G. Vulpiani4113.09