Abstract This study combines observational analyses with large‐eddy simulations (TaiwanVVM) to investigate the spatial distribution and underlying mechanisms of winter precipitation in northeastern Taiwan under the influence of the northeasterly monsoon. Through unsupervised machine learning, we identify four primary precipitation types (NC, YL‐NC, YL, NEC), among which YL and YL‐NC exhibit the highest proportion of extreme precipitation events. The results indicate that the direction of low‐level moisture transport and near‐surface stability (NSS) are critical factors influencing precipitation distribution. When moisture transport is predominantly northerly or easterly, the NC and NEC types emerge, respectively, whereas the YL‐NC and YL types occur under northeasterly flow. Furthermore, higher NSS is associated with more active stratocumulus cloud development, which affects precipitation intensity. The results from selected cases using TaiwanVVM further reveal the key roles of orographic lifting, blocked flow, and upstream convergence in precipitation formation. Along the northern coast, where terrain elevation is relatively low, precipitation is primarily driven by orographic lifting. In high‐NSS situations (YL‐NC and NC), vertical moisture mixing and vigorous stratocumulus development lead to stronger precipitation. In the Yilan Plain, different mechanisms dominate depending on the NSS in YL and YL‐NC. Under low NSS (YL type), the unstable boundary layer suggests that orographic lifting is the primary driver of precipitation; under high NSS (YL‐NC type), blocked flow develops, and its interaction with upstream wind convergence produces precipitation hotspots. When the wind direction shifts to easterly, flow around the eastern flank of the Central Mountain Range promotes line structure convection, affecting precipitation in the northeastern coast.
Huang et al. (Thu,) studied this question.