Assessing specific differential phase (K-DP)-based quantitative precipitation estimation for the record- breaking rainfall over Zhengzhou city on 20 July 2021

Although radar-based quantitative precipitation estimation (QPE) has been widely investigated from various perspectives, very few studies have been devoted to extreme-rainfall QPE. In this study, the performance of specific differential phase (K-DP)-based QPE during the record-breaking Zhengzhou rainfall event that occurred on 20 July 2021 is assessed. Firstly, the OTT Parsivel disdrometer (OTT) observations are used as input for T-matrix simulation, and different assumptions are made to construct R(K-DP) estimators. K-DP estimates from three algorithms are then compared in order to obtain the best K-DP estimates, and gauge observations are used to evaluate the R(K-DP) estimates. Our results generally agree with previous known-truth tests and provide more practical insights from the perspective of QPE applications. For rainfall rates below 100 mm h(-1), the R(K-DP) agrees rather well with the gauge observations, and the selection of the K-DP estimation method or controlling factor has a minimal impact on the QPE performance provided that the controlling factor used is not too extreme. For higher rain rates, a significant underestimation is found for the R(K-DP), and a smaller window length results in a higher K-DP and, thus, less underestimation of rain rates. We show that the QPE based on the "best K-DP estimate " cannot reproduce the gauge measurement of 201.9 mm h(-1) with commonly used assumptions for R(K-DP), and the potential factors responsible for this result are discussed. We further show that the gauge with the 201.9 mm h(-1) report was in the vicinity of local rainfall hot spots during the 16:00-17:00 LST period, while the 3 h rainfall accumulation center was located southwest of Zhengzhou city.