Work

Disentangling Atmospheric Turbulence from Hydrometeor Aerodynamics: Radar Spectrum Width Peaks and Microphysical Signatures within Dendritic Growth Zones

Year: 2026
Type: preprint
Abstract: . The Doppler velocity spectrum width (σv) observed by dual-polarization weather radar is widely used as a proxy for atmospheric turbulence, including convectively induced turbulence (CIT) hazardous to aviation. However, σv also responds to the aerodynamic behavior of frozen hydrometeors, so its interpretation within the dendritic growth zone (DGZ) remains ambiguous. This study combines a spheroidal aerodynamic response model with quasi-vertical profile (QVP) observations from eight precipitation cases recorded by the S-band dual-polarization radar at the Yongin testbed. Simulations show that particle geometry governs how efficiently a wind perturbation is converted into radial-velocity variance: the whole plane-crystal series, from plates to dendrites, responds far more strongly than columnar or rimed habits. A quantitative procedure identified a σv peak zone in five cases, all stratiform. In four of them σv showed no systematic relationship with vertical wind shear (VWS) but a temperature-dependent negative relationship with differential reflectivity (ZDR); static stability and near-vertical radial-velocity observations argue against a thermally driven origin, while the ice-relative vapor density excess (Δρv) maximum was positively related to, and vertically adjacent to, the σv maximum. Beneath the peak, an aggregation index derived from ZH, ZDR, and KDP increased with σv magnitude, whereas a counterpart index for vapor-depositional growth did not. The cases separate into weak plate-dominated growth, strong dendritic growth, and one shear-driven peak unrelated to the DGZ. These results suggest that σv within growth layers is partly determined by the hydrometeors observed, so estimating turbulence inside precipitating systems requires knowledge of the microphysical state and hydrometeor type.
Author: Sung-Ho Suh
Language: English
Open Access status: green
OpenAlex ID: W7225614951
Cites: 47
Cited by:
Related to: 10