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Polarimetric radars make it possible to retrieve information on hydrometeors types, sizes and concentrations. Additional information on cloud electrification can be obtained from Lightning Mapping Arrays (LMAs). To study the development time and height of the hydrometeors and electrification require tracking their evolution within the lifecycle of convective cells. A new methodology for multi-cell identification and tracking (MCIT) is presented in this study. The algorithm in this study is different from traditional tracking methods; this new algorithm is applied to time series of radar volume scans. It tracks local maxima of vertically integrated liquid (VIL) water by identifying the two cells in consecutive radar scans that have maximum common VIL. The vertical profile of the polarimetric variables is used for constructing the time-height cross section of the cells' microphysical properties around the peak reflectivity as a function of height. The LMA sources that occur within the cell area are integrated as a function of height as well for each time step, as determined by the radar volume scans. The result of the tracking can provide insights on the evolution of storms, hydrometer types, precipitation initiation and cloud electrification under different thermodynamic and aerosol conditions. The details of the MCIT algorithm, its products and their performance for different type of storms are described in this paper.

In this study, severe hail cases in Oklahoma/USA are investigated by analyzing the data simultaneously collected by two closely located polarimetric weather radars operating at S and C bands. Polarimetric radar variables measured in the presence of hail at C band are quite different from the ones at S band due to more pronounced effects of resonance scattering and much stronger impact of attenuation. The differences are particularly strong in melting hail below the freezing level, but they can be substantial even at higher altitudes where hail is dry or grows in wet regime. As a consequence, the algorithms for hail detection and determination of its size developed at S band can't be directly applied to C band. Differences between vertical profiles of radar reflectivity Z, differential reflectivity Z DR , and cross-correlation coefficient ρ hv in hail-bearing parts of the storms have been examined for large and giant hail. It is shown that in the presence of hail, Z DR (C) is usually higher than Z DR (S) and ρ hv (C) hv (S). The height of radar resolution volume with respect to the freezing level has to be taken into account in polarimetric hail detection/sizing. It is also demonstrated that giant hail is commonly associated with pronounced depression of ρ hv in the areas of hail generation above the freezing level and the corresponding drop in ρ hv at C band is much stronger than at S band. These results are compared to C-band polarimetric data collected in hail-bearing thunderstorms in Austria, where additional small hail size reports are available.

A hail storm at Villingen-Schwenningen, southwest Germany, on 28.06.2006 was simulated using the Hebrew University Cloud Model (HUCM) with spectral (bin) microphysics. The model allows the simulation of hail stones with diameters up to 6.8 cm. To investigate whether the amount of hail is sensitive to atmospheric instabilities, the simulations were performed for two different temperature gradients within the boundary layer. The response of precipitation, the hail mass and hail size distribution to aerosol was investigated in the simulations with cloud condensation nuclei (CCN) concentrations ranging between 100 cm − 3 and 6000 cm − 3 (at the supersaturation of 1%). An increase in the surface temperature by one degree leads to an increase in accumulated rain by ~ 80% and nearly doubles the mass of hail falling to the surface. An increase in CCN concentration from 100 cm − 3 to 3000 cm − 3 leads to a certain increase in accumulated rain and to a dramatic increase in the hail mass, as well as to the increase in the hail diameter from a few mm to 1–4 cm. The mechanisms by means of which aerosols affect precipitation and hail stones size are discussed. It is shown that formation of hail increases the precipitation efficiency of deep convective clouds.