Quality Control of Reflectivity Field Using Co-polar Correlation Coefficient and Environmental Data

Dual Polarization radars provide information regarding the hydrometeor shape, size, and phase, which lead to an improved skill in differentiating between radar echoes of hydrometeors and those of non-hydrometeors.

In this work, an algorithm with physical rule-based decision tree approach was designed to classify meteorological and non-meteorological radar echoes. Because the co-polar correlation coefficient RhoHV measures the consistency of horizontal and vertical returns for each radar signal pulse, it provides information about spatial characteristics of the scatterers in the pulse volume. The proposed algorithm utilizes a basic RhoHV filter to segregate obvious meteorology and non-meteorological scatterers, and then employs a set of simple physical rules based on temperature soundings and spatial features of RhoHV and reflectivity to handle a small amount of echoes that are exceptions to the basic RhoHV filter. The methodology is tested across 138-hour of data from 29 polarimetric WSR-88D radars that represented various weather and non-weather echo regimes from different regions of the US. The algorithm was shown to be equally effective to a sophisticated hydrometeor classification scheme in terms of segregating meteorological and non-meteorological echoes with advantages of simplicity and computational efficiency. This simple scheme can also be used to mask out the non-meteorological contaminations in other radar moments.