Performance Evaluation and Improvement of CMFD's Precipitation Products Over Shanghai City, China

Precipitation products with high resolution for urban areas remain an important and challenging issue. The main purposes of this study are to evaluate the accuracy of the China Meteorological Forcing Data Set (CMFD) in the Shanghai megacity and to improve the accuracy of the CMFD precipitation. With the rain gauge observations for the 2013-2018 period, we evaluate the error and detection ability of CMFD at the sub-daily, daily, and monthly scales, and examine the spatial variation of CMFD performance over the region. The Geographic Differential Analysis (GDA) method is used to calibrate the CMFD precipitation data set. The results show that the performance of CMFD precipitation varies from sub-daily to monthly time scales with better accuracy at the monthly scale in the study region. The CMFD can capture the spatial variability over the region with less error in the north and outliers in the center. The GDA-based calibration framework can significantly improve the capability of CMFD products, especially at the sub-daily and daily scales. The calibrated CMFD can provide reliable precipitation estimates and capture more extreme precipitation events. The improved CMFD products can provide a key basis for applications related to hydrological and meteorological hazard monitoring and assessment in the Shanghai area. The overall framework is scalable and could be readily generalized to other regions, and the calibrated product can be used in the research of urban natural disaster risks and other studies.