Morphology-Based Zero-Isodop Extraction and Velocity Correction for Multifold Velocity-Aliased Weather Radar

Radial velocity data of Doppler weather radars are crucial for wind field retrieval and nowcasting, but multifold velocity aliasing in short-wavelength radar systems (e.g., X/Ku-band) severely restricts their application. Conventional velocity dealiasing methods relying on velocity continuity fail in such scenarios due to unreliable initial reference velocity determination. To resolve this challenge, the morphology-based zero iso-Doppler contour (zero-isodop) extraction and velocity correction algorithm (MZI-VCA) is proposed for multifold velocity-aliased weather radar. The method first constructs a large-scale uniform horizontal wind model to characterize aliased zero-isodop distributions, then applies morphological operations combined with depth-first search (DFS) for candidate isodop extraction in plan position indicator (PPI) images, and finally identifies the zero-isodop through spatial structure metrics. Leveraging the extracted zero-isodop, dealiasing is performed under spatial continuity constraints. Validations using both simulated multifold aliasing data (derived from S-band radar) and Ku-band weather radar observations demonstrate that MZI-VCA achieves superior performance compared with the traditional dealiasing method, unfold radar velocity (UNRAVEL) algorithm. MZI-VCA achieves a 100% dealiasing success rate in correcting double- and triple-fold aliasing, with a success rate of 90.74% across all diverse multifold scenarios tested in 108 simulated volume scans. In contrast, UNRAVEL fails to resolve multifold aliasing, exhibiting only a 6.92% probability of detection (POD). The systematic method establishes a new framework for resolving multifold velocity aliasing in short-wavelength radar systems.