Convective Mode of Tornadic Storms in Northeastern China: A Preliminary Study

This study presents a comprehensive analysis of 132 tornadic events in northeastern China from 2004 to 2023, utilizing radar and ERA5 reanalysis data to investigate the climatology, environmental drivers, and synoptic linkages with Northeast China cold vortices (NCCVs) of tornadic storms under different convective modes. Results reveal that discrete storms account for 70% of events, with clustered cells (CC) being the most frequent mode, while significant tornadoes (EF2+) are primarily associated with isolated cells (IC) and broken lines (BL). The storm mode distribution in northeastern China resembles that of the central United States but with a higher proportion of CC and lower IC. In contrast, southern China exhibits a higher frequency of quasi-linear (QL) modes (>50%), similar to European patterns. Although no single parameter clearly differentiates between all tornado modes, distinct morphological characteristics emerge through specific parameter combinations: NL modes are characterized by high 0–1 km storm-relative helicity (SRH1) and humidity but low 0–6 km shear (SR6), whereas IC modes display contrasting features with low SRH1 and high CAPE. Notably, 83% of tornadoes are associated with NCCVs, preferentially forming in southeastern/southwestern quadrants. Strong tornadoes favor southeastern quadrants, while NCCV intensity correlates with tornadic distance from vortex centers. Three characteristic synoptic configurations emerge: (T1) strong deep vortices with vertically aligned cold troughs, generating southeast-dominant tornado clusters characterized by a high proportion of BL and QL modes; (T2) weaker vortices featuring sub-synoptic troughs, with southern-distributed events dominated by a predominance of the CC mode; (T3) transverse-trough systems exhibiting CAPE–SRH decoupling and reduced tornadic activity. This study enhances our understanding of tornadoes in northeastern China, informing future research on formation mechanisms, prediction methods, and disaster prevention strategies.