DocumentCode :
805692
Title :
Polarimetric Weather Radar Retrieval of Raindrop Size Distribution by Means of a Regularized Artificial Neural Network
Author :
Vulpiani, Gianfranco ; Marzano, Frank Silvio ; Chandrasekar, V. ; Berne, Alexis ; Uijlenhoet, Remko
Author_Institution :
Dept. of Phys., L´´Aquila Univ.
Volume :
44
Issue :
11
fYear :
2006
Firstpage :
3262
Lastpage :
3275
Abstract :
The raindrop size distribution (RSD) is a critical factor in estimating rain intensity using advanced dual-polarized weather radars. A new neural-network algorithm to estimate the RSD from S-band dual-polarized radar measurements is presented. The corresponding rain rates are then computed assuming a commonly used raindrop diameter speed relationship. Numerical simulations are used to investigate the efficiency and accuracy of this method. A stochastic model based on disdrometer measurements is used to generate realistic range profiles of the RSD parameters, while a T-matrix solution technique is adopted to compute the corresponding polarimetric variables. The error analysis, which is performed in order to evaluate the expected errors of this method, shows an improvement with respect to other methodologies described in the literature. A further sensitivity evaluation shows that the proposed technique performs fairly well even for low specific differential phase-shift values
Keywords :
atmospheric techniques; geophysics computing; meteorological radar; neural nets; radar polarimetry; rain; S-band dual-polarized radar measurements; T-matrix solution technique; disdrometer measurements; dual-polarized weather radars; error analysis; neural-network algorithm; phase shift; polarimetric weather radar retrieval; rain intensity; rain rates; raindrop diameter speed relationship; raindrop size distribution; regularized artificial neural network; sensitivity evaluation; stochastic model; Artificial neural networks; Electromagnetic wave polarization; Meteorological radar; Numerical simulation; Performance evaluation; Radar measurements; Radar polarimetry; Rain; Reflectivity; Stochastic processes; Artificial neural network; radar polarimetry; raindrop size distribution (RSD); regularization;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2006.878438
Filename :
1717720
Link To Document :
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