Assessment and tuning of the behaviour of a microphysical characterization scheme

The correct classification of prevailing bulk hydrometeor type within a radar resolution volume is a challenge task even if a full set of polarimetric radar observables is available. Indeed scattering and propagation effects from the variety of hydrometeors present interact each others and sometimes, if not often, tend to obscure the characteristic signature of each weather radar target type. This consideration is enforced when the atmospheric volume is sampled with a wavelength where bothMie scattering effects and attenuation start to become relevant. In this paper, we utilize the hydrometeor classification scheme developed at the National Severe Storms Laboratory (USA). Briefly, the scheme uses a fuzzy logic approach to combine different polarimetric variables and environmental temperature in order to determine the most likely type of prevalent hydrometeor in the radar volume. This means that the resulting classification is based on two characteristics: the volume polarimetric responses and the thermal value. The relative balance between these two is managed through the coefficients in the fuzzy scheme. We have observed that these parameters are crucial in order to get “physical reasonable result”, independently from the meteorological character of the event investigated. Our work is based on a reduced set of polarimetric variables (Z and ZDR) as input. Data used in this study were collected by a C-band radar over weather events ranging from convective to stratiform.