Comparison of Monsoon Raindrop Size Distribution Between Inland and Coastal in South China

The raindrop size distribution (DSD) is a significant characteristic of precipitation physics, which plays a crucial role in improving the accuracy of radar quantitative precipitation estimation and prediction. There is an effect of atmospheric circulation and weather systems in South China, with frequent precipitation and differences in regional features, resulting in a limited understanding of the DSD characteristics and their impact mechanisms in the region. In this study, six ground-based two-dimensional video disdrometers (2DVDs) were used to analyze the DSD of inland and coastal in South China during the five-year (2016–2020) monsoon seasons (April to September), ERA5 reanalysis data and MODIS cloud property products were also used to investigate the dynamics and microphysical characteristics of monsoon precipitation. Compared to inland rainfall, coastal rainfall has a higher concentration of small, medium, and diameter of less than 4.7 mm large raindrops. Considering the contributions to precipitation, the inland and coastal rainfall are dominated by convective rain, accounting for 74.8% and 84.7% of the total rainfall, respectively. The coastal rainfall has a higher the mass-weighted mean diameter (D_m) value than the inland rainfall D_m for both the stratiform and convective rainfall. The logarithmic mean of the generalized intercept parameter (log₁₀N_w) in inland stratiform rain is greater than that in coastal areas, while convective rain is relatively small. Due to the impact of precipitation types and climate conditions, The Z-R relationship between inland and coastal rainfall also shows obvious differences. Compared to inland areas, there is more frequent convective activity, relatively moist near-surface conditions, and lower cloud droplet number concentrations, which contribute to larger D_m of raindrops in coastal areas. This study deepens the understanding of changes in South China′s coastal and inland DSD and provides support for improving numerical weather forecasting in the region.