**1. Introduction**

Torrential rainfall events are one of the most severe disasters around the world [1,2]. The extreme rainfall and induced floods, landslides, debris flows gravely threaten life and property. The precipitation microphysics such as raindrop size distribution (DSD) serves as a fundamental bridge in deriving radar quantitative precipitation estimation (QPE) algorithms, which is critical for improving the accuracy of precipitation estimation and predictions [3,4]. Accurate precipitation estimates are also important input to the flash flood guidance systems for flood forecast, as well as subsequent warning operations and emergency management decision-making [5]. Therefore, a better understanding of precipitation microphysics and accurate quantitative precipitation estimation for extreme rain are important for flood warning and emergency management decision-making.

Under the influence of the East Asian monsoon, the Indian monsoon, the western Pacific subtropical high, as well as Tibetan Plateau, southern China is severely affected by heavy rain events during warm seasons (May to September), which usually cause floods and landslides [6–8]. From 27 August to 1 September 2018, an extremely heavy rainfall occurred over Guangdong province, especially in the south and east parts of Guangdong. There were two different extreme rainfall centers on 29 August and 30 August, respectively: one was located around Doumen station in Zhuhai, and the other was located at Gaotan station in Huidong. A record-breaking daily precipitation of 1056.7 mm was observed at Gaotan station on 30 August. This heavy rainfall caused catastrophic floods in many cities such as Huizhou, Shantou, Zhuhai, affecting more than 1 million people, causing directed financial losses around USD 144 million (https://www.thepaper.cn/newsDetail\_forward\_2404157). Moreover, a recent study has shown that extreme precipitation shows an increasing trend in south China during the last several decades [9], which highlights the importance of accurate precipitation measurement and modeling.

However, it is always a challenge to obtain accurate precipitation estimation. Gauges, weather radars, and satellite-based sensors are three main methods to measure precipitation [10]. Gauges can provide the most direct and precise precipitation observations. However, they are limited to fixed locations, and the networks of gauges are sparse. Therefore, interpolation is required to produce areal rainfall mapping and the interpolation method could lead to significant errors [11]. Satellite rainfall data has the advantage of large-scale spatial coverage, so the derived spatial distribution of rainfall is more complete. However, the satellite data also suffers from various sources of errors, including systematic error, random error, etc. Additionally, the spatial and temporal resolutions are very low, which has posed great difficulty in capturing the structure and evolution of small scale but strong storms [12]. In such cases, the only practical way to achieve a comprehensive estimation of precipitation is weather radar, which can provide real-time high-resolution monitoring over large areas [13,14].

Eight weather radars in the Guangdong area have completed dual-polarization upgrades in 2017 to improve disaster warning and forecasting capabilities. Compared to traditional single-polarization radar, the dual-polarization radar can measure polarimetric parameters including differential reflectivity *Zdr*, differential phase shift φ*dp*, and co-polar correlation coefficient ρ*HV*[14]. These parameters can be used to reveal microphysical properties of different hydrometeors [15–18] and improve quantitative precipitation estimation [14,19]. Meanwhile, several disdrometers have been installed in Guangdong province. Though they provide point measurements, the accumulation of time decreases the spatial variability of local precipitation microphysics [20]. Therefore, these disdrometers can provide detailed knowledge of local DSD information, which is critical in understanding the microphysical characteristics of precipitation and improving microphysical parameterization schemes in the numerical weather prediction models [4,21].

The primary purpose of this study is to conduct a comprehensive analysis of this extreme event from 27 August to 1 September 2018, based on various in situ and remote sensing observations including rain gauges, polarimetric radars, disdrometers, and reanalysis data so as to gain a better understanding of the epic flood events as such, especially to explore the potential of polarimetric radars to resolve the microphysics and quantify the precipitation. This study is also part of our effort in improving precipitation monitoring, forecast, and associated hydrologic responses in southern China. The paper is organized as follows. The study domain and dataset are described in Section 2. The synoptic environment of this extreme rainfall event is detailed in Section 3. The rainfall pattern and microstructural characteristics of this rainstorm observed by gauge and disdrometers, as well as the associated polarimetric radar signatures are detailed in Section 4. Section 5 summarizes the main findings of this study and suggests future directions of this research.

#### **2. Data and Methodology**

#### *2.1. Data*

The observational data used in this study include rainfall measurements from a dense gauge network, two S-band polarimetric radars, and two second-generation Particle Size and Velocity (Parsivel2) disdrometers in Guangdong. The instrument locations and the two special gauge stations (Gaotan and Doumen) are shown in Figure 1. The National Centers for Environmental Prediction (NCEP) final operational model global analysis data (NCEP-FNL) available every 6 h with a resolution of 0.25◦ × 0.25◦ at 31 vertical levels (http://rda.ucar.edu/datasets/ds083.2//#!access) are used to resolve the synoptic condition [22], along with the sounding data collected at 00:00 and 12:00 UTC at Qingyuan (QY) and Shantou (ST) (No. 59280, and No. 59316 from the University of Wyoming: http://weather.uwyo.edu/upperair/sounding.html).

**Figure 1.** The topography of Guangdong province and geographical locations of instruments used in this study. The red circles are the 150-km coverage range rings from the radars. The red square, triangle, star, and pentagon represent the locations of radar, disdrometer, special gauge, and sounding, respectively. The small black circles stand for the gauges. The instrument names are abbreviated version of location names: DM (Doumen), GT (Gaotan), HD (Huidong), QY (Qingyang), ST (Shantou), ZH (Zhuhai).
