In order to mitigate effects of DSD variability, we suggest the extension of the algorithm R(KDP) with the coefficient A depending on differential reflectivity ZDR averaged over sufficiently large spatial / temporal domain. Different functions A(ZDR) are recommended for light, moderate, and heavy rain. These functions have been derived empirically by comparing one-hour rain accumulations obtained from the Cimarron polarimetric radar and 42 gauges comprising a dense micronetwork in Central Oklahoma. Twenty rain events have been examined.
The use of average values of ZDR instead of point ZDR estimates greatly reduces the influence of statistical errors in ZDR measurements on the overall performance of the suggested algorithm. The result is a much less biased estimate of rainfall compared to the algorithm R(KDP) without noticeable increase in statistical errors.
We have compared also polarimetric variables measured by the radar with the ones computed from 2D-video-disdrometer assuming the Pruppacher - Pitter shapes of raindrops. It was found that specific differential phase measured by the radar is somewhat smaller on average than KDP estimated from the disdrometer. The reasons for such a discrepancy are analyzed.