Improvements of polarimetric radar echo classifications

Several radar echo classifications based on polarimetric radar data have been developed during the past years. The main applications are rejection of non-meteorological data and hydrometeor classification. Most algorithms use a fuzzy logic approach and are applied on range gate resolution to obtain 3D polar classification data sets.

Due to random signal fluctuation and occasionally due to extreme scattering phenomena (e.g. Mie effects for large particles at small wavelength), significant mis-classification may occur, e.g. classification of rain in areas above the melting level, or rejection of hail shaft or the melting layer as non-meteorological echo due to an unusually low polarimetric correlation coefficient ρ_HV. While some horizontal fluctuations of the classification results can be overcome by horizontal averaging (of either the polarimetric data or of the classification probabilities), a couple of mis-classifications remain.

The presentation shows results from an improved radar echo classification algorithm. Therefore, consistency checks are applied to the results obtained from conventional algorithms. These checks include:

• vertical variability of hydrometeor type results, in particular between liquid and solid phase,
• unreasonable ground clutter classifications,
• unreasonable biological scatterer classifications.