Statistical Characteristics and Synoptic Situations of Long‐Duration Heavy Rainfall Events Over North China

Abstract

The spatiotemporal characteristics of long-duration heavy rainfall (LDHR) events are statistically analyzed using hourly surface observations over central-southern North China during the warm seasons of 2011-2018, revealing pronounced variabilities in the frequency and amount of LDHR. Two accumulated rainfall peaks are found in the western (WHRR) and eastern (EHRR) regions of central-southern North China. The LDHR occurrence frequency decreases westward, and the peaks of the LDHR amount, frequency and intensity in the WHRR and EHRR are observed at nighttime (2100-0200 Beijing Standard Time) or in the early morning (0300-0700 Beijing Standard Time). The rainfall amount exhibits a bimodal diurnal variation in the WHRR (determined mainly by the rainfall intensity), whereas a single rainfall frequency-related peak is found in the EHRR. Four types of LDHR events corresponding to different flow patterns, synoptic systems, and moisture transport mechanisms are classified according to their locations. The first is heavy rainfall in the WHRR with an upper-level jet favorable for an ascending motion near Taihang Mountain; topographic blocking of southerly flow is crucial for heavy rainfall formation. The second describes heavy rainfall in the EHRR attributable to the favorable configurations of upper-and lower-level systems. Heavy rainfall occurs over both the WHRR and the EHRR in the third type, including topographic blocking and convergence associated with low-pressure systems or shear lines and a mesoscale low vortex or shear line related to topographic effects and positive vorticity advection in front of a westerly trough. The fourth shows a scattered distribution of LDHR stations and is generally not comparable to the first three types.

Spatiotemporal patterns and evolution of heavy rainfall trajectories in China

“…In coastal areas, heavy rainfall events show the characteristics of long trajectories and wide extensions. The HRTs in NE and in N are mainly concentrated in the plains; in the NE, some of the HRTs follow the tributary valleys of the upper reaches of the Songhua River into the western side of the Da Hinggan Mountains, forming an area of concentrated HRTs in the valley areas of the Inner Mongolia Plateau (Figure 5a); in the N, Mount Taishan prevents the HRTs from moving further into northeast Shandong Province (Figure 6a), and the small‐scale area of concentrated HRTs formed in central Shanxi (Taiyuan) is contributed by persistent heavy rainfall events and prevented from moving northward by the Taihang Mountains (Kang et al ., 2020). Note that in Table 4, the standard deviation in spring of 4.34 (>1) in the N is much higher than that of other geographical divisions in spring.…”

“…Table 5 shows that the spatial distribution areas of persistent heavy rainfall events in SW and NWE are more fixed in a year, so there will be more severe secondary hazards in the areas of concentrated HRTs. Many studies have demonstrated the close relationship between heavy rainfall events and the Taihang Mountains in N. The Taihang Mountains can effectively trigger and amplify mesoscale convective systems, leading to a concentration of heavy rainfall events on the eastern side of the mountains (Sun, 2005;Kang et al, 2020), which is generally consistent with the results in this study for the area of concentrated HRTs in N. In addition, note that in N the areas of concentrated HRTs are formed in Beijing during both summer and fall, which has the same temporal distribution of intense hourly rainfall events in the warm season as obtained by Li et al (2017b). In Taiwan, the areas of concentrated HRTs occur on the western side of the Central Range in spring and on the eastern side in fall, which is also corroborated by the seasonal study of extreme rainfalls in Taiwan by Henny et al (2021).…”

“…Many physics‐based models of different synoptic scales, such as the Weather Research and Forecasting (WRF) Model, Regional Climate Model (RCM) and Global Coupled Models (GCMs), have been employed to predict future climate change and to assess the impact of climate change on precipitation (Peltier et al ., 2018; Ren et al ., 2020). In addition, the triggering and amplifying function of mountains for mesoscale convective systems (Alexander et al ., 2015; Eghdami and Barros, 2019) can impact heavy rainfall events regarding their magnitude of extreme precipitation events, the number of days (Lemus‐Canovas et al ., 2021) and the intensity of daily and subdaily extremes (Panziera et al ., 2018; Kang et al ., 2020). Current heavy rainfall studies almost always use indicators such as the amount and intensity of heavy rainfall and the number of heavy rainfall days to quantify the degree and trend of heavy rainfall spatiotemporal distribution and evolution (Lin and Yang, 2014; Ren et al ., 2015; Kong et al ., 2017; He and Zhai, 2018).…”

An investigation into trends in frequency and proportion of different durations of various types of extreme precipitation in Iran

“…This finding was contrary to our finding in the current study which probably concerns the different lengths of the data used in the studies. According to Kang et al (2020), extreme precipitation has been increasing in northern China for a long time. Regional differences have also been observed in some areas.…”

Radar Observed Structural Features and Evolution Mechanism of a Squall Line‐Like Rainband in a Linear Mesoscale Convective System

“…A large valley (named "V" here as in Figure 1), opening to east, is located at 38.4°N in the eastern Taihang Mountains, with more complex small-scale terrain on the mountain slopes. Many heavy rainfall events have been observed in valley "V" (Kang et al, 2020). Researchers tried to address the mechanisms responsible for the formation of MCSs, especially the impacts of the cold pool and terrain (Xia & Zhang, 2019;Xiao et al, 2017Xiao et al, , 2019.…”