This study investigates the statistical characteristics of raindrop size distributions (DSDs) in monsoon season with observations collected by the second-generation Particle Size and Velocity (Parsivel²) disdrometer located in Zhuhai, southern China. The characteristics are quantified based on convective and stratiform precipitation classified using the rainfall intensity and total number of drops. On average of the whole dataset, the DSD characteristic in southern China consists of a higher number concentration of relatively small-sized drops when compare with eastern China and northern China, respectively. In the meanwhile, the D_m and log₁₀N_w scatter plots prove that the convective rain in monsoon season can be identified as maritime-like cluster. The DSD is in good agreement with a three-parameter gamma distribution, especially for the medium to large raindrop size. Using filtered data observed by Parsivel² disdrometer, a new Z–R relationship, Z = 498R^1.3, is derived for convective rain in monsoon season in southern China. These results offer insights of the microphysical nature of precipitation in Zhuhai during monsoon season, and provide essential information that may be useful for precipitation retrievals based on weather radar observations.

This study assesses the performance of the latest version 05B (V5B) Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) Early and Final Runs over southern China during six extremely heavy precipitation events brought by six powerful typhoons from 2016 to 2017. Observations from a dense network composed of 2449 rain gauges are used as reference to quantify the performance in terms of spatiotemporal variability, probability distribution of precipitation rates, contingency scores, and bias analysis. The results show that: (1) both IMERG with gauge calibration (IMERG_Cal) and without gauge correction (IMERG_Uncal) generally capture the spatial patterns of storm-accumulated precipitation with moderate to high correlation coefficients (CCs) of 0.57–0.87, and relative bias (RB) varying from −17.21% to 30.58%; (2) IMERG_Uncal and IMERG_Cal capture well the area-average hourly series of precipitation over rainfall centers with high CCs ranging from 0.78 to 0.94; (3) IMERG_Cal tends to underestimate precipitation especially the rainfall over the rainfall centers when compared to IMERG_Uncal. The IMERG Final Run shows promising potentials in typhoon-related extreme precipitation storm applications. This study is expected to give useful feedbacks about the latest V5B Final Run IMERG product to both algorithm developers and the scientific end users, providing a better understanding of how well the V5B IMERG products capture the typhoon extreme precipitation events over southern China.

Short-term high-resolution quantitative precipitation forecasting (QPF) is very important for flash-flood warning, navigation safety, and other hydrological applications. This paper proposes a subpixel-based QPF algorithm using a pyramid Lucas–Kanade optical flow technique (SPLK) for short-time rainfall forecast. The SPLK tracks the storm on the subpixel level by using the optical flow technique and then extrapolates the precipitation using a linear method through redistribution and interpolation. The SPLK compares with object-based and pixel-based nowcasting algorithms using eight thunderstorm events to assess its performance. The results suggest that the SPLK can perform better nowcasting of precipitation than the object-based and pixel-based algorithms with higher adequacy in tracking and predicting severe storms in 0–2 h lead-time forecasting.

The South China Sea (SCS) is the largest and southernmost sea in China. Water vapor from the SCS is the primary source of precipitation over coastal areas during the summer monsoon season and may cause the uneven distribution of rainfall in southern China. Deep insight into the spatial variability of raindrop size distribution (DSD) is essential for understanding precipitation microphysics, since DSD contains abundant information about rainfall microphysics processes. However, compared to the studies of DSDs over mainland China, very little is known about DSDs over Chinese ocean areas, especially over the South China Sea (SCS). This study investigated the statistical characteristics of the DSD in summer monsoon seasons using the second-generation Particle Size and Velocity (Parsivel²) installed on the scientific research vessel that measured the size and velocity of raindrops over the SCS. In this study, the characteristics of precipitation over the SCS for daytime and nighttime rains were analyzed for different precipitation systems and upon different rain rates. It was found that: (1) rain events were more frequent during the late evening to early morning; (2) more than 78.2% of the raindrops’ diameters were less than 2 mm, and the average value of mass-weighted mean diameter ${\mathrm{D}}_{\mathrm{m}}$ (1.46 mm) of the SCS is similar to that over land in the southern China; (3) the stratiform precipitation features a relatively high concentration of medium to large-sized rain drops compared to other regions; (4) the DSD in the SCS agreed with a three-parameter gamma distribution for the small raindrop diameter. Furthermore, a possible factor for significant DSD variability in the ocean compared with the coast and large islands is also discussed.

Raindrop size distribution (DSD) over the complex terrain of Guangdong Province, southern China, was studied using six disdrometers operated by the Guangdong Meteorology Service during the period 1 March 2018 to 30 August 2022 (~5 years). To analyze the long-term DSD characteristics over complex topography in southern China, three stations on the windward side, Haifeng, Enping and Qingyuan, and three stations on the leeward side, Meixian, Luoding and Xuwen, were utilized. The median mass-weighted diameter (D_m) value was higher on the windward than on the leeward side, and the windward-side stations also showed greater D_m variability. With regard to the median generalized intercept (log₁₀N_w) value, the log₁₀N_w values decreased from coastal to mountainous areas. Although there were some differences in D_m, log₁₀N_w and liquid water content (LWC) frequency between the six stations, there were still some similarities, with the D_m, log₁₀N_w and LWC frequency all showing a single-peak curve. In addition, the diurnal variation of the mean log₁₀N_w had a negative relationship with D_m diurnal variation although the inverse relationship was not particularly evident at the Haifeng site. The diurnal mean rainfall rate also peaked in the afternoon and exceeded the maximum at night which indicated that strong land heating in the daytime significantly influenced the local DSD variation. What is more, the number concentration of drops, N(D), showed an exponential shape which decreased monotonically for all rainfall rate types at the six observation sites, and an increase in diameter caused by increases in the rainfall rate was also noticeable. As the rainfall rate increased, the N(D) for sites on the windward side (i.e., Haifeng, Enping and Qingyuan) were higher than for the sites on the leeward side (i.e., Meixian, Luoding and Xuwen), and the difference between them also became distinct. The abovementioned DSD characteristic differences also showed appreciable variability in convective precipitation between stations on the leeward side (i.e., Meixian, Luoding and Xuwen) and those on the windward side (Haifeng and Enping, but not Qingyuan). This study enhances the precision of numerical weather forecast models in predicting precipitation and verifies the accuracy of measuring precipitation through remote sensing instruments, including weather radars located on the ground.

Version 5B Integrated Multi-satellite Retrievals for GPM (IMERG) products were evaluated with rain gauge observations as reference over the Nanliu River basin in Southern China since March 2014 to December 2016 through the Xinanjiang hydrologic model. The IMERG products include the early run satellite-only IMERG product (IMERGERUncal), final run satellite-only and gauge-corrected IMERG products (IMERGFRUncal and IMERGFRCal, respectively). Direct comparison with the gauge observations indicates that both early run and final run IMERG products have good performances in capturing the precipitation at spatial and temporal characteristics. IMERGFRUncal and IMERGERUncal show compatible capabilities to detect rainfall in a daily scale with highly correlative coefficient (CC) about 0.67, relative bias (RB) about −20.79%, and root mean square error (RMSE) about 10.68 mm. IMERGFRCal performed a little better than IMERGFRUncal and IMERGERUncal with higher CC (0.7) and lower magnitude of RB (4.90%). Simulated stream flows with daily IMERG products as forcing data show a large deviation from the observed stream flows with low Nash-Sutcliffe index (NSCE) < 0.3, indicating that all of these IMERG products have limited potentials of hydrological utilization in this basin. Particularly, IMERGFRCal shows relatively poor NSCE (0.28) and underestimates the stream flow by 7.83%. IMERGFRUncal and IMERGERUncal exhibit better performance than IMERGFRCal in the hydrological simulation with higher NSCE (0.30 and 0.29, respectively) and larger deviations with RBs about −56.73% and −59.49%, respectively. This result manifests that the IMERG products users need to be cautious when using IMERG products for hydrological applications in this basin. Additionally, this study is expected to offer insights into IMERG’ potentials in the hydrological utility and thus provide useful feedbacks to the IMERG algorithm developers and the users.