Tree-based Genetic Programming Approach to Infer Microphysical Parameters of the DSDs from the Polarization Diversity Measurements

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@Article{Islam2012,

• author = "Tanvir Islam and Miguel A. Rico-Ramirez and Dawei Han",
• title = "Tree-based Genetic Programming Approach to Infer Microphysical Parameters of the DSDs from the Polarization Diversity Measurements",
• journal = "Computer \& Geosciences",
• volume = "48",
• pages = "20--30",
• year = "2012",
• ISSN = "0098-3004",
• DOI = "doi:10.1016/j.cageo.2012.05.028",
• URL = "http://www.sciencedirect.com/science/article/pii/S0098300412001847?v=s5",
• keywords = "genetic algorithms, genetic programming, Drop size distribution (DSD) retrievals, Polarimetric radar, Dual polarisation radar, Disdrometer raindrop spectra, Precipitation microphysics, Shape and size parameters",
• abstract = "The use of polarisation diversity measurements to infer the microphysical parametrisation has remained an active goal in the radar remote sensing community. In view of this, the tree-based genetic programming (GP) as a novel approach has been presented for retrieving the governing microphysical parameters of a normalised gamma drop size distribution model- D0 (median drop diameter), Nw (concentration parameter), and ?\mu (shape parameter) from the polarisation diversity measurements. A large number of raindrop spectra acquired from a Joss-Waldvogel disdrometer has been used to develop the GP models, relating the microphysical parameters to the T-matrix scattering simulated polarization measurements. Several functional formulations retrieving the microphysical parameters-D0 [f(ZDR), f(ZH, ZDR)], log10Nw [f(ZH, D0), f(ZH, ZDR, D0), and ?\mu f(ZDR, D0), f(ZH, ZDR, D0)], where ZH represents reflectivity and ZDR represents differential reflectivity, have been investigated, and applied to a S-band polarimetric radar (CAMRA) for evaluation. It has been shown that the GP model retrieved microphysical parameters from the polarisation measurements are in a reasonable agreement with disdrometer observations. The calculated root mean squared errors (RMSE) are noted as 0.23-0.25 mm for D0, 0.74-0.85 for log10Nw (Nw in mm-1 mm-3), and 3.30-3.36 for ?. The GP model based microphysical retrieval procedure is further compared with a physically based constrained gamma model for D0 and log10Nw estimates. The close agreement of the retrieval results between the GP and the constrained gamma models support the suitability of the proposed genetic programming approach to infer microphysical parametrisation.",

}

Genetic Programming entries for Tanvir Islam Miguel A Rico-Ramirez Dawei Han

Citations