Wednesday, 30 August 2023: 11:15 AM
Great Lakes BC (Hyatt Regency Minneapolis)
Strong electric fields in a thunderstorm are capable of vertically aligning ice crystals above the melting layer, typically between levels of lightning channel development. These storm regions which may be associated with potentially damaging lightning channels should be investigated using polarimetric weather radar. This study proposes a novel approach to detect and track ice alignment signatures (IAS) in thunderstorms using spectral polarimetry. Polarimetric-variable spectra can be used to study microphysical properties in relation to the dynamics within a radar resolution volume by combining Doppler and polarimetric measurements. The polarimetric spectrum densities unveil additional information about the characteristics of groups of scatterers moving at different Doppler velocities in a radar volume. Previous studies have identified IAS using different polarimetric variables signatures depending on the polarimetric modes such as negative specific differential phase (KDP) and differential reflectivity (ZDR) streaks with simultaneous transmission of the H and V polarized waves (SHV) radar, and linear depolarization ratio (LDR) and co-polar to cross-polar correlation coefficient (ρ_xh, ρ_xv) streaks with a fast alternating pulse transmission of H and V (FHV). While IASs are commonly observed above stratiform regions of precipitation, they are more difficult to detect within convective cores where graupel and ice crystals coexist. However, spectral polarimetric analysis that unfolds the polarimetric variables as a function of radial velocity can increase the contrast of IAS in observations and separates covered weak signals, leading to a higher probability of detection.
In this study, we propose to use spectral polarimetry to uncover previously unseen alignment regions at the bottom of the freezing layer where small ice crystals are nucleated and aligned by electric fields, indicating widespread ice alignment near the thunderstorm convective cores. Our observational analysis, using IAS cases from the NCAR S-Pol radar collected during the Plains Elevated Convection at Night (PECAN) Experiment, is complemented by a one-dimensional radar simulation based on T-matrix to understand the causes of IAS in polarimetric variables spectrum. By comparing these observations with polarimetric radar simulations, we further our understanding that the IAS observed in previous studies using radar bulk moments are actually path-dependent radar wave accumulative depolarization signatures. This implies that IAS from weak ice backscattering signal can be sorted by ice aggregates or even larger graupel and hail signals in the same layer, particularly at closer ranges in the ice nucleation layer. Spectral polarimetry analysis allows for the uncovering of this hidden signal due to its ability to separate different types of particles in the spectrum. A case study is presented, where a weak spectrum region associated with high sρ_xv observed approximately 20 km away from the radar was observed. We speculate such spectral signatures are caused by small ice crystal alignment. Moreover, this signature cannot be observed in ρ_xv because the coexisting and stronger aggregates dominate the radar signals. Our innovative approach provides valuable insights into microphysical and electrical processes in thunderstorms and has the potential to improve detection of lightning signatures associated with severe weather.
Figure reference: https://drive.google.com/file/d/11ClRmpKdrzMCOiBGy_EibCBTp7th77Fc/view?usp=share_link
In this study, we propose to use spectral polarimetry to uncover previously unseen alignment regions at the bottom of the freezing layer where small ice crystals are nucleated and aligned by electric fields, indicating widespread ice alignment near the thunderstorm convective cores. Our observational analysis, using IAS cases from the NCAR S-Pol radar collected during the Plains Elevated Convection at Night (PECAN) Experiment, is complemented by a one-dimensional radar simulation based on T-matrix to understand the causes of IAS in polarimetric variables spectrum. By comparing these observations with polarimetric radar simulations, we further our understanding that the IAS observed in previous studies using radar bulk moments are actually path-dependent radar wave accumulative depolarization signatures. This implies that IAS from weak ice backscattering signal can be sorted by ice aggregates or even larger graupel and hail signals in the same layer, particularly at closer ranges in the ice nucleation layer. Spectral polarimetry analysis allows for the uncovering of this hidden signal due to its ability to separate different types of particles in the spectrum. A case study is presented, where a weak spectrum region associated with high sρ_xv observed approximately 20 km away from the radar was observed. We speculate such spectral signatures are caused by small ice crystal alignment. Moreover, this signature cannot be observed in ρ_xv because the coexisting and stronger aggregates dominate the radar signals. Our innovative approach provides valuable insights into microphysical and electrical processes in thunderstorms and has the potential to improve detection of lightning signatures associated with severe weather.
Figure reference: https://drive.google.com/file/d/11ClRmpKdrzMCOiBGy_EibCBTp7th77Fc/view?usp=share_link
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner