Polarimetric Characteristics of Enhanced Warm-Rain Precipitation Growth Processes

Accurate radar quantitative precipitation estimation (QPE) in precipitation events characterized by enhanced warm-rain precipitation growth processes is particularly challenging due to the atypical Drop Size Distributions associated with these events. Radar QPE in these warm-rain enhanced events can be improved if the precipitation is accurately identified/classified prior to precipitation estimation. This classification procedure can be improved by incorporating polarimetric radar data, which enable a more microphysically-based precipitation classification than is possible using single-polarization data. However, prior to implementing such a classification scheme the behavior of the polarimetric radar variables in warm-rain enhanced precipitation events must first be documented.

Taking advantage of the 2013 NEXRAD dual-polarization upgrade, the three dimensional profiles of the polarimetric radar variables: Z, Zdr, Kdp, and ρhv were analyzed for a variety of warm-rain enhanced precipitation events over the CONUS for the 2013 and 2014 warm seasons. The analysis focused on both the values of the polarimetric variables and their variation with height, and significant results are as follows: Nearly all warm-rain enhanced events were characterized by relatively low values of Z, Zdr and Kdp compared to reference (non warm-rain) cases with similar rain rates. The vast majority of cases were characterized by Z, Zdr, and Kdp increasing toward the surface below the environmental freezing/melting level. Most events also, displayed a steep decrease in reflectivity with height above the freezing level coincident with low echo top heights, and subfreezing Zdr and Kdp values near 0. The microphysical characteristics were also visualized using a parameter space of Kdp, Z, and Zdr, and the warm-rain events were generally found to lie in a particular quadrant of this parameter space. These early results seem to support the conclusion that polarimetric radar data can be used to identify and classify precipitation associated with enhanced warm-rain growth processes, and these results could have important implications for radar QPE.