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Using an iterative rain‐cell tracking method to identify and track mesoscale convective system (MCS) precipitation during the warm seasons (May–October) of 2015–2020, we reveal the seasonal variation in the spatiotemporal distribution, rainfall characteristics, and the life cycle of MCS precipitation in different months over North China. Notable MCS precipitation centers are located around mountain slopes and downstream areas. The diurnal peak of MCS rainfall is manifested as a southeastern delay from afternoon in mountainous regions to midnight or morning over downstream plains. In May and June, MCS rainfall is distributed on the hillside of Taihang–Yan mountains and the Shandong Peninsula. MCS precipitation gets an early evening peak on mountain slopes and a nocturnal maximum over the North China Plain (NCP). In July and August, the MCS activities extend to NCP, and another MCS precipitation center exists over the Luliang Mountains in western North China, under the seasonal march of the monsoon flow. The local diurnal peaks to the east of 114°E are generally later than in May and June, and MCS precipitation gets a peak during midnight to early morning over the NCP. MCSs in July and August feature the strongest intensity. In September and October, the MCS precipitation shifts to high terrain of the Taihang Mountains and its west, with an early afternoon peak. MCSs have the largest size and the fastest propagation speed in September and October, but with the weakest intensity. Compared with short‐lived MCSs, long‐lived MCSs have stronger precipitation intensity, larger rainfall area, and faster propagation speed. In addition, the life cycle of long‐lived MCS precipitation represents asymmetric development and decay. Long‐lived MCSs occur with more pronounced upper troposphere warming and low‐level anomalous southwesterlies. Meanwhile, higher specific humidity in the low‐ and mid‐level troposphere provides a more favorable environment for the maintenance of MCS precipitation. [ABSTRACT FROM AUTHOR]

High-resolution meteorological datasets are urgently needed for understanding the hydrological cycle of the Tibetan Plateau (TP), where ground-based meteorological stations are sparse. Rapid advances in remote sensing create possibilities to represent spatiotemporal properties of precipitation at a high resolution. In this study, the hourly precipitation characteristics over the TP from two gridded precipitation products, one from global reanalysis (the fifth generation of the European Center for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate; ERA5) and the other is simulated by Global-to-Regional Integrated forecast SysTem (GRIST) global nonhydrostatic model, are compared against satellite-gauge merged precipitation analysis (China Merged Precipitation Analysis; CMPA) from 27 July to 31 August 2014, and a satellite-retrieved precipitation estimate from the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) is also evolved. Two aspects are mainly focused on: the spatial distribution and the elevation dependence of hourly precipitation characteristics (including precipitation amount, frequency, intensity, diurnal variations, and frequency–intensity structure). Results indicate that: (1) The precipitation amount, frequency, and intensity of CMPA and IMERG decrease with altitude in the Yarlung Tsangpo river valley (YTRV), but increase at first and then decrease with altitude (except for intensity) in the eastern periphery of TP (EPTP). ERA5 performed well on the variation of precipitation amount with altitude (especially in EPTP), but poorly on the frequency and intensity. GRIST is the antithesis of ERA5, but they all overestimate (underestimate) the frequency (intensity) at all heights; (2) With increasing altitude, the diurnal phase of precipitation of CMPA and IMERG shifted from night to evening in the two sub-regions. IMERG's diurnal phase is 1 to 3 h earlier than CMPA's, and the discrepancy decreases (increases) as the altitude increases in YTRV (EPTP). The diurnal phase of precipitation amount and frequency in ERA5 and GRIST is significantly earlier than CMPA, and the frequency peaks around midday except in the basin. GRIST's simulation of the diurnal variation in intensity at various altitudes is consistent with CMPA; (3) ERA5 and GRIST overestimate (underestimate) the frequency of weak (intense) precipitation, with ERA5's deviance being the most severe. The deviations increased with altitude. These findings provide intensive metrics to evaluate precipitation in complex terrain and are helpful for deepening the understanding of simulated biases for further improving performance in high-resolution simulation. [ABSTRACT FROM AUTHOR]