Accuracy of rain rate estimation using polarimetric radar measurements has improved as a result of improved data quality and better characterization of rain microphysics. In the literature a variety of power-law relations between polarimetric radar measurements and rain rate are described due to dynamic or varying nature of rain microphysics. Is there a technique that could concurrently take advantage of data quality and also dynamically adapt to varying rain microphysics? Rain rate estimation using variational algorithm that uses event based error covariances of observational error and background rain climatology is applied to the epic Front Range rain event between 11 and 12 September 2013. The results show the variational algorithm consistently estimates more accurate rain rate than the current NEXRAD algorithm. The technique presented in this study is applicable only to rain and it is not applicable to mixed phase precipitation.
Quantitative Precipitation Estimation in Epic Colorado Flood Event of September 2013: Polarization Radar-based Variational Scheme