Investigation of liquid cloud microphysical properties of deep convective systems: 1. parameterization raindrop size distribution and its application for stratiform rain estimation

To investigate liquid-phase (T > 3°C) cloud and precipitation microphysical properties within Deep Convective Systems (DCSs), eight DCS cases sampled by the University of North Dakota Citation II research aircraft during Midlatitude Continental Convective Clouds Experiment were selected. A full spectrum of raindrop size distribution (DSD) was constructed from 120 μm to 4000 μm through a combination of two-dimensional cloud probe (120 to 900 μm) and High Volume Precipitation Spectrometer (900 to 4000 μm) data sets. A total of 1126 five second DSDs have been used to fit to Gamma and Exponential functions within the stratiform rain (SR) regions of DCSs. The Gamma shape μ_Γ and slope λ_Γ parameters are then compared with those derived from surface disdrometer measurements. The similar μ_Γ-λ_Γ relationships but different μ_Γ and λ_Γ value ranges from two independent platforms at different elevations may represent the real nature of DSD shape information in clouds and at the surface. To apply the exponentially fitted DSD parameters to precipitation estimation using Next Generation Weather Radar (NEXRAD) radar reflectivity factor Z_e, the terms N_0E and λ_E have been parameterized as a function of Z_e using an empirical N_0E-λ_E relationship. The averaged SR rain rate retrieved from this study is almost identical to the surface measurements, while the NEXRAD Q2 precipitation is twice as large. The comparisons indicate that the new DSD parameterization scheme is robust, while the Q2 SR precipitation estimation based on Marshall-Palmer Z-R relationship, where a constant DSD intercept parameter (N_0E) was assumed, needs to be improved for heavy precipitation cases.