Enhanced Calibration Assessment of Chinese Ground-based Polarimetric Radars Using a Refined GPM DPR Volume-matching Method

Accurate calibration of China’s new generation ground-based polarimetric radar (GR) network is crucial yet challenging. Although application of the Dual-frequency Precipitation Radar (DPR) of the Global Precipitation Measurement Core Observatory for GR assessment is well-established, current methodologies are inherently limited. Focusing on three GRs in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA)—strategically selected for their high overlapping coverage (>65%) and distinct from single GR or less dense coverage studies—this work introduces key refinements by integrating innovative enhancements into the volume-matching method (VMM), reflecting a systematic approach to mitigating potential error sources. Specifically, we integrate: 1) a novel frequency correction method that adapts to DPR-observed precipitation phase and type, replacing assumption-based polynomial fitting; and 2) a precise beam time-difference matching approach (accuracy < 1 s) to minimize temporal mismatch errors, which improves upon coarser time averaging methods. Furthermore, we developed statistically robust, optimized threshold criteria based on systematic sensitivity analyses using 11 quality control factors, including precipitation type, bright band effects, and attenuation correction limitations. These criteria establish an enhanced protocol designed to minimize errors arising from instrumental, frequency, and scanning differences. Application of this enhanced methodology to the GBA GRs (2021–2023) yielded a significantly improved matching accuracy (correlation coefficient, CC: 0.90–0.95; standard deviation, STD: 1.2–1.6 dB). A unique contribution of this work is the quantitative estimation of historical calibration errors and operational stability, which was achieved by linking VMM results with operational GR calibration and maintenance records. This analysis revealed decreasing STD trends and identified specific calibration-related events, such as an underestimation of approximately 2.43 dB for the Shenzhen radar following calibration in 2023. Consequently, the refined methodology provides a robust framework for ongoing GR network monitoring and offers a validated pathway for authenticating China’s Fengyun-3G (FY-3G) satellite precipitation measurement radar (PMR) data.