A bayesian approach for hydrometeor classification of polarimetric weather radar variables

Wen, G, Wang, X, Moran, W and May, P 2012, 'A bayesian approach for hydrometeor classification of polarimetric weather radar variables', in Proceedings of the IET International Conference on Radar Systems (RADAR 2012), Glasgow, United Kingdom, 22-25 October 2012, pp. 429-434.


Document type: Conference Paper
Collection: Conference Papers

Title A bayesian approach for hydrometeor classification of polarimetric weather radar variables
Author(s) Wen, G
Wang, X
Moran, W
May, P
Year 2012
Conference name RADAR 2012
Conference location Glasgow, United Kingdom
Conference dates 22-25 October 2012
Proceedings title Proceedings of the IET International Conference on Radar Systems (RADAR 2012)
Publisher IEEE
Place of publication United States
Start page 429
End page 434
Total pages 6
Abstract In this paper, hydrometeor type classification is studied using the observations of CP-2 polarimetric weather radar located in Brisbane, Australia. The problem is formulated in a Bayesian classification framework, where total ten bulk hydrometeor types are considered. The conditional measurement distribution which describe the probabilities of radar measurements corresponding to hydrometeor types is approximated by a multivariate Gaussian distribution with parameters characterized by the scattering properties of hydrometeors. Locations and boundaries of the melting layers are estimated using reflectivity, differential reflectivity and correlation coefficient. They are then incorporated into the classification process together with convection and stratiform classification. The proposed Bayesian classification algorithm is tested using the CP-2 polarimetric radar data over 100 scan volumes and results show the consistency with cloud microphysical models.
Subjects Signal Processing
Stochastic Analysis and Modelling
Keyword(s) Hydrometeor types
Bayesian classification
Melting layer
Polarimetric variables
DOI - identifier 10.1049/cp.2012.1729
Copyright notice © The Institution of Engineering and Technology 2012
ISBN 9781627481229
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