A comparative study on quantitative precipitation estimation based on GPM satellite and X-band phased-array weather radar

This study investigates the performance of the Global Precipitation Measurement (GPM) satellite in comparison to the X-band Phased Array Weather Radar (XPAR) regarding precipitation measurement accuracy, focusing on radar echoes. A comparative analysis was conducted on two significant precipitation events that occurred in 2023 in Xiong’ an New Area, Hebei Province, China, utilizing data from XPAR, GPM, and ground-based observations. The results reveal that XPAR outperforms the GPM satellite in quantitative precipitation estimation, with a correlation coefficient of approximately 0.88 between XPAR data and ground observations, compared to 0.66 for GPM. Furthermore, the root mean square error (RMSE) and mean absolute error (MAE) for XPAR against ground observations were 1.2g mm and 0.64 mm, respectively, while for GPM, these values were significantly higher at 6.98 mm and 1.91 mm. findings highlight the superior capability of XPAR in accurately estimating precipitation, which is crucial for enhancing the detection and early warning of heavy rainfall events.