Abstract
Accurate estimation of precipitation at high spatial and temporal resolution of weather radars is an open problem in hydrometeorological applications. The use of dual polarization gives the advantage of multiparameter measurements using orthogonal polarization states. These measurements carry significant information, useful for estimating rain-path signal attenuation, drop size distribution (DSD), and rainfall rate. This study evaluates a new self-consistent with optimal parameterization attenuation correction and rain microphysics estimation algorithm (named SCOP-ME). Long-term X-band dual-polarization measurements and disdrometer DSD parameter data, acquired in Athens, Greece, have been used to quantitatively and qualitatively compare SCOP-ME retrievals of median volume diameter D0 and intercept parameter NW with two existing rain microphysical estimation algorithms and the SCOP-ME retrievals of rain rate with three available radar rainfall estimation algorithms. Error statistics for rain rate estimation, in terms of relative mean and root-mean-square error and efficiency, show that the SCOP-ME has low relative error if compared to the other three methods, which systematically underestimate rainfall. The SCOP-ME rain microphysics algorithm also shows a lower relative error statistic when compared to the other two microphysical algorithms. However, measurement noise or other signal degradation effects can significantly affect the estimation of the DSD intercept parameter from the three different algorithms used in this study. Rainfall rate estimates with SCOP-ME mostly depend on the median volume diameter, which is estimated much more efficiently than the intercept parameter. Comparisons based on the long-term dataset are relatively insensitive to path-integrated attenuation variability and rainfall rates, providing relatively accurate retrievals of the DSD parameters when compared to the other two algorithms.
