[A-AS03] Extreme Events and Mesoscale Weather: Observations and Modeling

[AAS03-17] Comparison of microphysical characteristics between warm-sector and frontal heavy rainfall in South China

*LU FENG¹、SHENG HU¹、XIAN TONG LIU¹、HUI QI LI¹、HUI XIAO¹、XIAO HUI LI²、RUI ZE LAI¹、QING LIN³ (1.Guangzhou Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou 510080, China、2.Jiangmen Meteorological Observatory, China Meteorological Administration, Jiangmen, Guangdong 529000, China、3.Guangdong Provincial Meteorological Observatory, China Meteorological Administration, Guangzhou 510080, China)

キーワード：heavy rainfall, raindrop size distribution (DSD), 2-dimensional video disdrometer (2DVD), the south of China

During the April-June raining season, warm-sector heavy rainfall (WR) and frontal heavy rainfall (FR) often occur in the south of China, causing natural disasters. In this study, the microphysical characteristics of WR and FR events from 2016 to 2022 are analyzed by using 2-dimensional video disdrometer (2DVD) data in the south of China. The microphysical characteristics of WR and FR events are quite different. Compared with FR events, WR events have higher concentration of D < 5.3 mm (especially D < 1 mm), leading to higher rain rates. The mean values of D_m and lgNw of WR events are higher than that of FR events. The microphysical characteristics in different rain rate classes (C1: R ~ 5-20 mm h^-1, C2: R ~ 20-50 mm h^-1, C3: R ~ 50-100 mm h^-1, and C4: R > 100 mm h^-1) for WR and FR events are also different. Raindrops from C3 contribute the most to the precipitation of WR events, and raindrops from C2 contribute the most to the precipitation of FR events. For C2 and C3, compared with FR events, WR events have higher concentration of D < 1 mm and D ~3-4.5 mm. Moreover, the shape and slope (μ-Λ) relationships and the radar reflectivity and rain rate (Z-R) relationships of WR and FR events are quite different in each rain rate class. The investigation of the difference in microphysical characteristics between WR and FR events provide useful information for radar-based quantitative precipitation estimation and numerical prediction.