Using Fully-Polarimetric Radar Observations and Microphysical Modeling to Understand Ice Precipitation Processes

Abstract:

While dual-polarization radars give us many useful variables to understand precipitation processes, fully polarimetric radars allow us to utilize the full backscattering covariance matrix. This allows for estimation of the co-to-cross-polar correlation coefficient and cross-polar differential phase. These variables are not as widely understood and applied as the dual-polarization variables, but may shed new light on cloud and precipitation processes.

This study uses the Ka-band Scanning Polarimetric Radar (KASPR) located at Stony Brook University on Long Island, New York, to observe ice precipitation processes in a winter storm. In conjunction with the radar observations, a one-dimensional bulk microphysical model is used to simulate microphysical processes occurring within the cloud. This model utilizes an adaptive habit approach to evolve hydrometeors’ two primary axis lengths. The model approximates the hydrometeors as oblate and prolate spheroids to represent the habit as plate-like or column-like, respectively.

Comparing and contrasting the radar observations with the model results illustrates the physical processes captured in the observed radar signals. Synthesizing the information provided by radar observations with the results of the microphysical model allows us to gain a better understanding of the meaning of the fully polarimetric radar variables. By modeling the ice crystal habit evolution and mixing ratios of pristine ice and aggregates, we can better understand the observed signals in cross-polar variables. A signal in cross-polar differential phase was observed to be co-located with a region of slower falling ice within a broader region of larger aggregates, potentially highlighting a secondary mode of ice generation. The microphysical model will be used to understand the processes contributing to ice production in this case. Such combination of this microphysical model and radar observations helps close the gap in understanding how fully polarimetric radar variables can be useful in better understanding ice processes.