Lightning rods, while essential for protecting weather radars from direct lightning strikes, act as persistent non-meteorological scatterers that can interfere with signal transmission and reception and thereby degrade detection accuracy and product quality. Existing studies have mainly focused on X-band and C-band systems, and robust, measurement-based quantitative assessments for S-band dual-polarization radars remain scarce. In this study, a controllable tilting lightning rod, a high-precision Far-field Antenna Measurement System (FAMS), and an S-band dual-polarization weather radar (SAD radar) are jointly employed to systematically quantify lightning-rod impacts on antenna electromagnetic parameters under different rod elevation angles and azimuth configurations. Typical precipitation events were analyzed to evaluate the influence of the lightning rods on dual-polarization parameters. The results show that the lightning rod substantially elevates sidelobe levels, with a maximum enhancement of 4.55 dB, while producing only limited changes in the antenna main-beam azimuth and beamwidth. Differential reflectivity ($Z_{DR}$) is the most sensitive polarimetric parameter, exhibiting a persistent positive bias of about 0.24–0.25 dB in snowfall and mixed-phase precipitation, while no persistent azimuthal anomaly is evident during freezing rain; the co-polar correlation coefficient (${\rho }_{hv}$) is only marginally affected. Collectively, these results provide quantitative, far-field evidence of lightning-rod interference in S-band dual-polarization radars and provide practical guidance for more reasonable lightning-rod placement and configuration, as well as useful references for $Z_{DR}$-oriented polarimetric quality-control and correction strategies.

Dual-band weather radar networks enable complementary multi-radar observations, improving the accuracy, three-dimensional characterization, and early warning capability for severe convective weather. S-band radar provides strong penetration and long detection range but suffers from limited spatial resolution, whereas X-band radar offers high resolution with weaker penetration, posing challenges for dual-frequency data fusion. To address the resolution mismatch and fusion modeling issues between dual-band radars, this study proposes a super-resolution reconstruction method for S-band reflectivity based on dual-frequency radar observations. S-band and X-band radar data, together with key polarimetric parameters, are jointly incorporated into a deep neural network-based fusion model to enhance the spatial resolution of S-band reflectivity. Experimental results under typical severe weather conditions demonstrate that the proposed method achieves improved detail recovery and structural reconstruction, with the model achieving PSNR 30.84, SSIM 0.8755, and MAE 0.24178, which shows obvious advantages compared with other models and effectively enhances radar network data quality, and it outperforms single S-band super-resolution approaches in both objective metrics and subjective evaluations.

To address the limitations of the traditional cross-scanning method in absolute calibration of weather radars using metal spheres, including insufficient spatial coverage, limited target acquisition efficiency, and echo underestimation in inter-range bins, this study proposes a sector scanning field calibration method. In this approach, standard metal spheres are suspended from UAVs, and a three-dimensional scanning volume around their theoretical positions is constructed to enable high-density echo sampling. By applying drive backlash correction, quadratic Gaussian surface fitting, and three-dimensional ellipsoid model inversion, key radar parameters can be retrieved. Experimental results show that the improved sector scanning method enhances automation, accuracy, and robustness in field environments and minor target drifts. The experiments were conducted under low-wind and low-clutter conditions. The average calibration error of antenna pointing is 0.08°, the average error of echo intensity calibration is 0.3 dB, the average beamwidth error is 0.07°, the range resolution is 6.6 m, and the average radial ranging error is 14 m. These results indicate that the proposed method can meet the main calibration requirements of weather radars in the present experiments.