Huiqi Li

Understanding the characteristics of the raindrop size distribution (DSD) is crucial to improve our knowledge of the microphysical processes of precipitation and to improve the accuracy of radar quantitative precipitation estimation (QPE). In this study, the spatial variability of DSD in different regions of Beijing and its influence on radar QPE are analyzed using 11 disdrometers. The DSD data are categorized into three regions: Urban, suburban, and mountainous according to their locations. The DSD exhibits evidently different characteristics in the urban, suburban, and mountain regions of Beijing. The average raindrop diameter is smaller in the urban region compared to the suburban region. The average rain rate and raindrop number concentration are lower in the mountainous region compared to both urban and suburban regions. The difference in DSD between urban and suburban regions is due to the difference in DSD for the same precipitation types, while the difference in DSD between mountain and plains (i.e., urban and suburban regions) is the combined effect of the convection/stratiform ratio and the difference of DSD for the same precipitation types. Three DSD-based polarimetric radar QPE estimators were retrieved and estimated. Among these three QPE estimators, R(Z_H), R(K_dp), and R(K_dp, Z_DR), R(K_dp, Z_DR) performs best, followed by R(K_dp), and R(Z_H) performs worst. R(K_dp) is more sensitive to the representative parameters, while R(Z_H) and R(K_dp, Z_DR) are more sensitive to observational error and systematic bias (i.e., calibration).

Based on the fifth-generation European Center for Medium-Range Weather Forecasts reanalysis data (ERA5), the real-time observation data from weather stations, and the radar products in Guangdong Province, we analyze the precipitation properties and formation mechanisms of the “5·31” extreme heavy rainfall process with record-breaking 3-h accumulated rainfall in South China during 2021. The results show that the extreme heavy rainfall process is caused by the joint actions of weather systems such as a weak upper-level short-wave trough, a surface stationary front, and a low-level southwesterly jet. Before the heavy precipitation process, there is large precipitable water content and deep warm clouds, which provides a potential for the occurrence and development of the heavy rainfall process in Longhua Town of Longmen County and its surrounding areas. Simultaneously, the low-level southwesterly jet provides abundant warm-wet water vapor for the heavy rainfall area. The vertical atmospheric environmental conditions, such as strong horizontal temperature gradient, high convective available potential energy, high-temperature difference between 850 hPa and 500 hPa, and low convective inhibition, maintain for a long duration in the heavy rainfall area, which are favorable for the occurrence and development of high-efficiency convective precipitation caused by water vapor condensation due to the uplift of low-level warm-wet airflows. The combined effects of the enhanced low-level southwesterly airflow, the stationary front, the mesoscale surface convergence line generated by cold pool outflows, the terrain influence, and the train effect of the precipitation echoes make heavy precipitation near Longhua last longer and stronger than other areas, leading to the extreme heavy rainfall with the record-breaking 3-h accumulated rainfall in Longhua.

A hailstorm with an inclined structure occurred in the western part of the South China coast on 27 March 2020. This study investigates the detailed evolution characteristics of this inclined structure using the Doppler radar data assimilation system (VDRAS) and the improved fuzzy logic hydrometeor classification algorithm (HCA). Obvious differential reflectivity (often referred to as ZDR) arc characteristics, ZDR column characteristics, and the specific differential phase (often referred to as KDP) of the column are observed using dual-polarization radar prior to hailfall. Both the ZDR column and KDP column reached their strongest intensities during the hailfall phase, with their heights exceeding the height of the −20 °C layer (7.997 km above ground level), displaying a cross-correlation coefficient (CC) valley during this phase. Meanwhile, two centers of strong reflectivity were found, with one (C1) being located at 2–4 km, and the other (C2) being located at 6–8 km. The maximum horizontal distance between the two centers is 8 km, suggesting a strongly inclined structure. This inclined structure was closely related to the interaction between upper-level divergent outflows and ambient horizontal winds. The updraft on the front edge of the hailstorm continued to increase, keeping C2 at the upper level. At the same time, large raindrops at the lower part of C2 are continuously lifted, leading to ice formation. These ice particles then fell obliquely from their high altitude, merging with C1.

On 1 June 2021, a heavy rainstorm hit the coast of South China (148.6 mm in 1 h, 361 mm over 12 h). The storm process was successively affected by two convective systems (CSs). The initial convection of the two CSs occurred at a similar location; however, they subsequently showed different evolution characteristics. Based on multi-source data, including dual-polarimetric radars, wind profiling radars, sounding, and automatic weather stations, we explored the differences in the key characteristics of these two CSs. It was found that the convection was initially triggered at a similar location for both CSs, closely related to the mesoscale boundary and the hilly terrain. After formation, CS1 moved eastward to the regions with lower surface temperature and weaker lower-level convergence but similar humidity, which means the environmental conditions for sustaining the CS became less favorable. As a result, CS1 dissipated rapidly and only lasted for about 90 min, resulting in 5% of the total precipitation of the overall storm. In contrast, during the lifespan of CS2, the southerly wind over the South China Sea became stronger. This caused an intense lower-level convergence zone along the coastal region of Guangdong Province, which provided favorable dynamic conditions for maintaining CS2. Favored by the strong coastal convergence and abundant moisture, new convective cells (CCs) were generated continuously and merged with CS2, acting as another favorable condition for its sustainment. Overall, CS2 lasted for 8 h, and its precipitation accounted for 95% of the total rainfall. In CS1, CCs showed a notable evaporation process below 4 km, manifested by the large raindrops. However, in CS2, the CCs had a higher concentration of small raindrops and higher ice and liquid water content. Since CS2 was close to the coastal region, the warm local environment promoted convection, leading to intense precipitation. In addition, the riming and melting processes were active, leading to a high precipitation efficiency and strong local precipitation during a short period of time.

On 22 June 2017, an extreme warm-sector rainfall event hit the western coastal area of South China, with maximum hourly and 12-h rainfall accumulations of 189.4 and 464.8 mm, respectively, which broke local historical records. Multisource observations were used to reveal multiscale processes contributing to the extreme rainfall. The results showed that a marine boundary layer jet (BLJ) coupled with a synoptic low-level jet (LLJ) inland played an important role in the formation of an extremely humid environment with a very low lifting condensation level of near-surface air. Under the favorable pre-convective conditions, convection was initialized at a mesoscale convergence line, aided by topographic lifting in the evening. During the nocturnal hours, the rainstorm developed and was maintained by a quasi-stationary mesoscale outflow boundary, which continuously lifted warm, moist air transported by the enhanced BLJ. When producing the extreme rainfall rates, the storm possessed relatively weak convection, with the 40 dBZ echo top hardly reaching 6 km. The extreme rainfall was produced mainly by the warm rain microphysical processes, mainly because the humid environment and the deep warm cloud layer facilitated the clouds’ condensational growth and collision–coalescence, and also reduced rain evaporation. As the storm evolved, the raindrop concentration increased rapidly from its initial stage and remained high until its weakening stage, but the mean raindrop size changed little. The extreme rain was characterized by the highest concentration of raindrops during the storm’s lifetime with a mean size of raindrops slightly larger than the maritime regime.