Enhancing Convective-scale Polarimetric Signatures through a Polar Coordinate Direct-Mosaicking Method for High-density Radar Networks

A multiradar mosaic is a key solution to the insufficient detection range of a single weather radar. In the traditional grid-preprocessed mosaicking method (GPM), radar polar coordinate data are interpolated into Cartesian grids to compensate for vertically undersampled regions in radar volume scans. However, such interpolation fails to accurately reconstruct the polarization parameters in these regions. Therefore, this study presentss a polar coordinate direct-mosaicking method (PDM) for the high-density radar network in South China, which directly operates on polar coordinate data and avoids initial interpolation. Based on typical precipitation cases from May to August 2021, three key issues in the PDM are addressed: First, horizontal reflectivity (Z_H) biases and differential reflectivity (Z_DR) offsets are corrected; second, the number of radars in the mosaicking process is evaluated, with five radars determined to be optimal; and third, the weights of different radar data are optimized by considering vertical and horizontal distances, along with the melting layer position. Compared with the GPM, the PDM yields a more accurate representation of the melting layer, with a smaller mean height error (192 m compared with 470 m) and a more realistic estimation of thickness (661 m compared with 1507 m). It also improves the continuity of polarimetric parameters within convective core regions. The case studies indicate that the PDM enables earlier identification of Z_DR columns and more accurate estimation of their heights. These advancements provide high-quality observational constraints for cloud microphysical research and offer potential for improving convective-scale data assimilation.