Abstract/Summary

This thesis presents novel uses of routinely measured dual polarisation radar variables to improve our understanding of the microphysics of mixed-phase clouds and rainfall. Fundamentally, a new variable L = - log10(1-Ρhv) is defined, which has preferable statistical properties to the co-polar correlation coefficient (Ρhv) and allows rigorous confidence intervals on Ρhv to be derived. The use of this variable also removes biases introduced by averaging many Ρhv samples and allows, for the first time, Ρhv to be used quantitatively. An emphasis is placed on how these variables can be used to retrieve microphysical information in embedded mixed-phase regions, which are particularly poorly understood at present. Using a combination of differential reflectivity (ZDR) and differential Doppler velocity (DDV), new statistics of the frequency of occurrence of mixed-phase clouds are presented. During a 3 month observational campaign, it is estimated that embedded mixed-phase clouds occur 26% of the time. A technique to remove the ambiguity of interpreting ZDR measurements when pristine oriented crystals are present amongst larger aggregate crystals is also presented. By combining L and ZDR, the contribution to the radar signal from pristine oriented crystals (C) and their \intrinsic" ZDR (ZPDRI) that would otherwise be hidden is retrieved.The results show that elevated ZDR above the melting layer was typically the result of pristine oriented crystals with ZPD RI between 3 and 7 dB, with varying contributions to the radar reflectivity. The retrieval provides an insight into the microphysics of embedded mixed-phase clouds using dual polarisation radar not before possible. Finally, the possibility of using L to measure the shape parameter (µ) in the gamma drop size distribution to improve rain rate retrievals is also investigated. It is shown that including drop oscillations is essential for this application. In a convective rain case study, µ appears to be substantially larger than 0 (an exponential DSD), and would result in an overestimated rain rate by up to 50% compared to if a simple exponential DSD is assumed. The potential to retrieve µ with operational radars is also discussed.