Weather radars have been used to quantitatively estimate precipitation since their development in the 1940s, yet these estimates are still prone to large uncertainties which dissuade the hydrological community in the UK from adopting these estimates as their primary rainfall data source. Recently dual polarisation radars have become more common, with the national networks in the USA, UK and across Europe being upgraded, and the benefits of dual polarisation radars are beginning to be realised for improving quantitative precipitation estimates (QPE).

The National Centre for Atmospheric Science (NCAS) mobile Doppler X-band dual polarisation weather radar is the first radar of its kind in the UK, and since its acquisition in 2012 has been deployed on several field campaigns in both the UK and abroad. The first of these campaigns was the Convective Precipitation Experiment (COPE) where the radar was deployed in Cornwall (UK) through the summer of 2013. This thesis has used the data acquired during the COPE field campaign to develop a processing chain for the X-band radar which leverages its dual polarisation capabilities.

The processing chain developed includes the removal of spurious echoes including second trip, ground clutter and insects through the use of dual polarisation texture fields, logical decision thresholds and fuzzy logic classification. The radar data is then corrected for the
effects of attenuation and partial beam blockage (PBB) by using the differential phase shift to constrain the total path integrated attenuation and calibrate the radar
azimuthally. A new smoothing technique has been developed to account for backscatter differential phase in the smoothing of differential phase shift which incorporates a long and a short averaging window in conjunction with weighting smoothing using the copolar correlation
coefficient. During the correction process it is shown that the calculation of PBB is insensitive to the variation in the ratio between specific attenuation and specific differential phase shift provided a consistent value is used. It is also shown that the uncertainty in attenuation correction is lower when using a constrained correction such
as the ZPHI approach rather than a direct linear correction using differential phase shift and is the preferred method of correction where possible.

Finally the quality controlled, corrected radar moments are used to develop a rainfall estimation for the COPE field campaign. Results show that the quality control and correction process increases the agreement between radar rainfall estimates and rain gauges when using horizontal reflectivity from a regression correlation of -0.01 to 0.34, with a reduction in the mean absolute percentage difference (MAPD) from 86% to 31%. Using dual polarisation
moments to directly estimate rainfall shows that rainfall estimates based on the theoretical conversion of specific attenuation to reflectivity produce the closest agreement to
rain gauges for the field campaign with a MAPD of 24%. Finally it is demonstrated that merging multiple dual polarisation rainfall estimates together improves the performance of the rainfall estimates in high intensity rainfall events while maintaining the overall accuracy of the rainfall estimates when compared to rain gauges.